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*\~/!U#ғߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{ߺ^׽u~{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From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD WorkflowsWeb Services Standards2BPEL (aka WSBPEL and BPEL4WS) details multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager features loop and control logic, synchronous/asynchronous communication composition and concurrent execution WS-Eventing, WS-Notification&PP5PP}P PdPP&5}  dN 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0` 33` Sf3f` 33g` f` www3PP` ZXdbmo` \ғq>9y`Ӣ` 3f3ff` 3f3FKf` hk]wwwfܹ` ff>>\`Y{ff` R>&- {p_/̴>?" dU@ <6?" 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3380___PPT10.wC $ 0 (4(  (d ( c $(K   %  ( s *%  0)  %   H ( 0޽h ? 3380___PPT10.x4$ 0 04(  0d 0 c $(K   %  0 s *%  @)  %   H 0 0޽h ? ̙3380___PPT10.0T  0 8L(  8p 8 0 ?)K   %  8 6%   ?+  %   B 8 s *޽h ? ̙33$  0 @D4(  Dd D c $(K   %  D s *%  m)  %   H D 0޽h ? a(80___PPT10.fE`db\$  0 T4(  Td T c $(K   %  T s *@%  0)  %   H T 0޽h ? 3380___PPT10.Dϳ 0 `L(  `p ` 0 ?)K   %  ` 6T%   ?+  %   B ` s *޽h ? ̙33$ 0 l4(  ld l c $(K   %  l s *%  0)  %   H l 0޽h ? 3380___PPT10.D@I 0 t((  t^ t S (K   %  t c $8%  m)  %   H t 0޽h ? a(80___PPT10.h\$ 0 04(  d  c $(K   *   s *T *  m)  *   H  0޽h ? a(80___PPT10.E`韗 0 PX(  d  c $(K     s **  0(   B.This is a restatement of Canonical Problem #3.H  0޽h ? 33r@AE8G@MPEB9:j|4~`Ȇ LJPv;xt0̗`nlJ(1c9( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed BlackOh+'0T hp  PowerPoint Presentation Ken KennedyLavanya457Microsoft PowerPoint@n@c%@LP@rGSg  )'    """)))UUUMMMBBB999|PP3f333f3333f3ffffff3f̙3ff333f333333333f33333333f33f3ff3f3f3f3333f33̙33333f333333f3333f3ffffff3f33ff3f3f3f3fff3ffffffffff3ffff̙fff3fffff3fff333f3f3ff3ff33f̙̙3̙ff̙̙̙3f̙3f333f3333f3ffffff3f̙3f3f3f333f3333f3ffffff3f̙3f3ffffffffff!___www4'A x(xKʦ """)))UUUMMMBBB999|PP3f3333f333ff3fffff3f3f̙f3333f3333333333f3333333f3f33ff3f3f3f3333f3333333f3̙33333f333ff3ffffff3f33f3ff3f3f3ffff3fffffffff3fffffff3f̙ffff3ff333f3ff33fff33f3ff̙3f3f3333f333ff3fffff̙̙3̙f̙̙̙3f̙3f3f3333f333ff3fffff3f3f̙3ffffffffff!___www⼼mmImrrsrrsrImImmmJJrrrI⼙BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBmmmmmmCmmCCCCCmmCmCmmCmmmCmmmmmCmCmݵmݓoBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHBkBHB 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH0IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, ligh  !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~                           ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m n o p q r s t u v w x y z { | } ~                            ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m n o p q r s t u v w x y z { | } ~                            ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m n o p q r s t u v w x y z { | } ~                            ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m n o p q r s t u v w x y z { | } ~                            ! " # $ % & ' ( ) * + , - . / 0 1 2 3 4 5 6 7 8 9 : ; < = > ? @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z [ \ ] ^ _ ` a b c d e f g h i j k l m n o p q r s t u v w x y z { | } ~        !"#$%&'()*+,-./0123456789:;<=>?@ABCEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnpqrstuvwxyz{|}~Root EntrydO)#@PicturesCurrent UserMSummaryInformation(DTo DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH0IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD WorkflowsWeb Services StandardsvBPEL (aka WSBPEL and BPEL4WS) details multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager features loop and control logic, synchronous/asynchronous communication composition and concurrent execution WS-Eventing, WS-Notification IU s WS Messenger bridges the gap&PP5PP}P PdPP"P&5}  d"` 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 p<(  p~ p s *Ȼ    ~ p s *p O   H p 0޽h ? lb___PPT10i.cP;+D=' q = @B +r41p9( / 0DDTimesmbolomanhh w՜.+,D՜.+,h$    On-screen ShowRice Universityp %TimesCLB Helvetica Condensed BlackComic Sans MSZapf DingbatsArial MS PGothicGenevaTahomaTimes New Roman StarSymbol굴림 WingdingsBlankLEAD Workflow OrchestrationOutline.Linked Environments for Atmospheric DiscoveryStatic ForecastingDynamic Adaptive LEAD SystemLEAD Control and Data Flow Service Oriented LEAD Workflows+Business Process Execution Language (BPEL)&LEAD Site Visit Experimental Ensemble"Characteristics of LEAD WorkflowsAdapting Workflow StructureOutlineLEAD ArchitectureLEAD ArchitectureVirtual Grid provides LEAD …& Root EntrydO)#@PicturesCurrent UserMSummaryInformation(DTtning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD WorkflowsWeb Services Jargon vBPEL (aka WSBPEL and BPEL4WS) details multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager features loop and control logic, synchronous/asynchronous communication composition and concurrent execution WS-Eventing, WS-Notification IU s WS-Messenger bridges the gap&PP5PP}P PdPP"P&5}  d"N 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 p<(  p~ p s *Ȼ    ~ p s *p O   H p 0޽h ? lb___PPT10i.cP;+D=' q = @B +rpL1s9( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH0IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD WorkflowsWeb Services Standards vBPEL (aka WSBPEL and BPEL4WS) details multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager features loop and control logic, synchronous/asynchronous communication composition and concurrent execution WS-Eventing, WS-Notification IU s WS-Messenger bridges the gap&PP5PP}P PdPP"P&5}  d"N 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 p<(  p~ p s *Ȼ    ~ p s *p O   H p 0޽h ? lb___PPT10i.cP;+D=' q = @B +rTQ T1y9( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH0IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz|}~4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)hBPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager features loop and control logic, synchronous/asynchronous communication composition and concurrent execution WS-Eventing, WS-Notification IU s WS-Messenger bridges the gapPP5PP}P PdPP"P5}  d"N 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 p<(  p~ p s *Ȼ    ~ p s *p O   H p 0޽h ? lb___PPT10i.cP;+D=' q = @B +rETƍ!T{18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH0IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d<f 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 p<(  p~ p s *Ȼ    ~ p s *p #   H p 0޽h ? lb___PPT10i.cP;+D=' q = @B +rt)18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH0IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-reA18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH0IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-@=  0 W<O<-/;(  r . S W O%   #  6t\ #" `Bj___PPTMAC11D<   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography <___PPT10R___PPT94, NetRad Radar ingest@0###G  6a #" `WD<~___PPTMAC11XP   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography D___PPT10$b___PPT9D< Fetch data productsP0### # o  6m #" ` D<~___PPTMAC11XP   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography D___PPT10$b___PPT9D< Convert to format for assimP0 ## # # rB  <DԔ"BrB  <DԔ"W  6i #" `G 0( z___PPTMAC11TL   hnamd` Arial&Monotype Typography   pnamdhHiragino Kaku Gothic Pro W3Dainippon Screen Mfg. Co., Ltd.     hnamd` Arial&Monotype Typography <___PPT10R___PPT94, tAssimilate into 3D grid@0###rB   <DԔ" < F B`     U 0   6 #" `2G ` RJB___PPTMAC11   hnamd` Arial&Monotype Typography  TForecast model execution 0#   6 #" `BD` j___PPTMAC11D<   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography <___PPT10R___PPT94, nPlan ensemble run @0# ##nB   0D"2nB  0D"2=nB  0D"2gnB  0D"g2gnB  0D"2nB  0D"26 nB  0D"G  nB  0D"G D nB  0D"G  nB  0D"G = =nB  0D"G g gnB  0D"G  nB  0D"G  6   6 #" `` ph___PPTMAC11ld   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography L___PPT10,$r___PPT9TL "Store results to personal catalog`#0# # # # #  6P #" ` ` V___PPTMAC110(   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography 4___PPT10 B___PPT9$ aAnalyze final product00##nB  0D"==Z  c $"` uE Z  c $"` K ; Z  c $"`   Z   c $"` <Z ! c $"`@ @0Z " c $"` V Z # c $"`a/Z $ c $"`F72 % 0б "``B___PPTMAC11   hnamd` Arial&Monotype Typography 0___PPT106___PPT9 G BPEL Workflow a^ & 67dB ' <D-SdB (@ <D:M dB )@ <D:F dB * <D& dB + <D dB , <Ds dB - <Dy m H  0޽h ? $%& 33___PPT10i.9q<+D=' q = @B +rD= 7{18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-(>  0 ?=7=.1<(  r . S W O%   #  6t\ #" `Bj___PPTMAC11D<   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography <___PPT10R___PPT94, NetRad Radar ingest@0###G  6a #" `WD<~___PPTMAC11XP   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography D___PPT10$b___PPT9D< Fetch data productsP0### # o  6m #" ` D<~___PPTMAC11XP   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography D___PPT10$b___PPT9D< Convert to format for assimP0 ## # # rB  <DԔ"BrB  <DԔ"W  6i #" `G 0( z___PPTMAC11TL   hnamd` Arial&Monotype Typography   pnamdhHiragino Kaku Gothic Pro W3Dainippon Screen Mfg. Co., Ltd.     hnamd` Arial&Monotype Typography <___PPT10R___PPT94, tAssimilate into 3D grid@0###rB   <DԔ" < F B`     U 0   6 #" `2G ` RJB___PPTMAC11   hnamd` Arial&Monotype Typography  TForecast model execution 0#   6 #" `BD` j___PPTMAC11D<   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography <___PPT10R___PPT94, nPlan ensemble run @0# ##nB   0D"2nB  0D"2=nB  0D"2gnB  0D"g2gnB  0D"2nB  0D"26 nB  0D"G  nB  0D"G D nB  0D"G  nB  0D"G = =nB  0D"G g gnB  0D"G  nB  0D"G  6   6 #" `` ph___PPTMAC11ld   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography L___PPT10,$r___PPT9TL "Store results to personal catalog`#0# # # # #  6P #" ` ` V___PPTMAC110(   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography 4___PPT10 B___PPT9$ aAnalyze final product00##nB  0D"==Z  c $"` uE Z  c $"` K ; Z  c $"`   Z   c $"` <Z ! c $"`@ @0Z " c $"` V Z # c $"`a/Z $ c $"`F72 % 0б "``B___PPTMAC11   hnamd` Arial&Monotype Typography 0___PPT106___PPT9 G BPEL Workflow a^ & 67dB ' <D-SdB (@ <D:M dB )@ <D:F dB * <D& dB + <D dB , <Ds dB - <Dy m  1 H`"p 8c?  hSource: Beth Plale  H  0޽h ? $%& 33___PPT10i.9q<+D=' p = @B +rs{O{N18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-rf5+18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 0FppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-!  0L0   **! (  x  c $ O%     H 88}4> }8 *Real-time Resource Monitoring (NWS-HAPI)+0+      H 88'-(+ oSteer the workflow, etc0      HX 88$M( .Workflow (triggered by real-time data arrival)/0/      N) 88"`(l(U3 "LEAD Monitoring and Orchestration *#0!      Z2 88"`*e/ P0    f  0Z"`$ (   T4 88$ s' mTarget Resource Set0       T" 88̙"`/fb(1 tResource Behavior Prediction0    lB   6"`14f   0Z"`$(`   s *"`*#-lB  6"`1M"04  HtI 883 7 |$Application Code Analysis (SvPablo)%0%    lB  6"`41 H4  HT 883 m6 hHistorical data0    2   fH4zI+31?"`6- r0   f^ 1?+  . EWorkflow Engine   fDK 1?+ _ / FDecision Process   fg 1?+ ./ ? Scheduler    Hr 88 " *Real-time Resource Monitoring (NWS-HAPI)$+0+      H\u 883 uSteer the workflow, etc$0          !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz|}~  HH 88 u .Workflow (triggered by real-time data arrival)$/0/       N 88"``2  "LEAD Monitoring and Orchestration $#0#      Z 88"`  V$0    f  0Z"`_V  T 88Z r sTarget Resource Set$0      Tp 88̙"` 1  ,Application and Resource Behavior Prediction$-0-    lB  6"`  f  0Z"` ,U`   s *"`E.lB ! 6"`- x  " Hd 88 Vf  $Application Code Analysis (SvPablo)$%0%    lB # 6"`5 f  $ HH 88 x M nHistorical data$0    2 %  fH4zI+31?"`  &  fP 1?6V  KWorkflow Engine  '  fp 1? U  LDecision Process  (  f 1? [P  E Scheduler  ` ) s *"` X   * H 88  Weather, application change$0    H  0޽h ? lby___PPT10Y+D=' = @B +ri+dE+18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-rڅ 18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r d18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB"CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r tC018( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-7  0 66  "D6(     C B CPDEF  @@PP @#" `\  ~  s *trO%  r ~  s *tr" r L `0| # UCq %  08r#" ``B|j___PPTMAC11D<   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography <___PPT10R___PPT94, NetRad Radar ingest@0###I  0 r#" ``W|D<~___PPTMAC11XP   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography D___PPT10$b___PPT9D< Fetch data productsP0### # W  0r#" `` |D<~___PPTMAC11XP   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography D___PPT10$b___PPT9D< #Convert to format for assimilationP$0 ### # zB   <DԔ"BYYzB   <DԔ"WYY    0hr#" `G `0|( z___PPTMAC11TL   hnamd` Arial&Monotype Typography   pnamdhHiragino Kaku Gothic Pro W3Dainippon Screen Mfg. Co., Ltd.     hnamd` Arial&Monotype Typography <___PPT10R___PPT94, tAssimilate into 3D grid@0###zB   <DԔ" YG YL B`  # s c*  0Pr#" `2G ` RJB___PPTMAC11   hnamd` Arial&Monotype Typography  Tforecast model execution 0#   0r#" `BD` j___PPTMAC11D<   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography <___PPT10R___PPT94, nPlan ensemble run @0# ##nB  0D"2nB  0D"2=nB  0D"2gnB  0D"g2gnB  0D"2nB  0D"26 nB  0D"G  nB  0D"G D nB  0D"G  nB  0D"G = =nB  0D"G g gnB  0D"G  nB  0D"G  6   0r#" `` ph___PPTMAC11ld   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography L___PPT10,$r___PPT9TL "Store results to personal catalog`#0# # # # #  0Dr#" ` ` V___PPTMAC110(   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography 4___PPT10 B___PPT9$ aAnalyze final product00##nB   0D"== " <<f8c?"`."F  It took an MS student 6 months, working with a research scientist, to learn how to modify the operational forecast system for her needs and run it using real data. <8P 2^3H  0޽h ? 33___PPT10i.4q++D=' = @B +rw0"iS0Ӡ18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-7  0 66  "6(     C B CPDEF  @@PP @#" `\  ~  s *trO%  r ~  s *tr" r L `0| # UCq %  08r#" ``B|j___PPTMAC11D<   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography <___PPT10R___PPT94, NetRad Radar ingest@0###I  0 r#" ``W|D<~___PPTMAC11XP   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography D___PPT10$b___PPT9D< Fetch data productsP0### # W  0r#" `` |D<~___PPTMAC11XP   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography D___PPT10$b___PPT9D< #Convert to format for assimilationP$0 ### # zB   <DԔ"BYYzB   <DԔ"WYY    0hr#" `G `0|( z___PPTMAC11TL   hnamd` Arial&Monotype Typography   pnamdhHiragino Kaku Gothic Pro W3Dainippon Screen Mfg. Co., Ltd.     hnamd` Arial&Monotype Typography <___PPT10R___PPT94, tAssimilate into 3D grid@0###zB   <DԔ" YG YL B`  # s c*  0Pr#" `2G ` RJB___PPTMAC11   hnamd` Arial&Monotype Typography  Tforecast model execution 0#   0r#" `BD` j___PPTMAC11D<   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography <___PPT10R___PPT94, nPlan ensemble run @0# ##nB  0D"2nB  0D"2=nB  0D"2gnB  0D"g2gnB  0D"2nB  0D"26 nB  0D"G  nB  0D"G D nB  0D"G  nB  0D"G = =nB  0D"G g gnB  0D"G  nB  0D"G  6   0r#" `` ph___PPTMAC11ld   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography L___PPT10,$r___PPT9TL "Store results to personal catalog`#0# # # # #  0Dr#" ` ` V___PPTMAC110(   hnamd` Arial&Monotype Typography    hnamd` Arial&Monotype Typography 4___PPT10 B___PPT9$ aAnalyze final product00##nB   0D"== " <<f8c?"`."y  YCenter for Analysis and Prediction of Storms (CAPS, OU): It took an MS student 6 months, working with a research scientist, to learn how to modify the operational forecast system for her needs and run it using real data>8P;H  0޽h ? 33___PPT10i.4q++D='  = @B +r18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-rJ18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz|}~!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-rJJl18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-N  0 e ]  (  f2  0̙>"`  r  S  O%   2  <0 jJ"` E4 QData Assimilation$0'2  < jJ"`  CWRF$0'2  <| jJ"`,,  CWRF$0'RB @ s *DjJRB   s *DjJRB   s *DjJ! RB  @ s *DjJ x 2   <( jJ"`   E IDV$0'RB   s *DjJRB @ s *DjJ    Z o?"0@NNN?N D& &0'  <h "`  fIU (chinkapin) "   0 "`OK I c UNC (dante)   "2  <L jJ"`   GARPSPLT$0'  0D "`  kUnidata (lead1)&  "   <L "`  p d OU (aquaman)   "XB  0LDjJ' g h  c @A lead-adas-wrf1 p f  0A?"`K yH  0޽h ? 33___PPT10i.Bw[+D=' = @B +rK|18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-.  0 E= (  f2  0̙>"`  r  S  O%   2  <0 jJ"` E4 QData Assimilation$0'2  < jJ"`  CWRF$0'2  <| jJ"`,,  CWRF$0'RB @ s *DjJRB   s *DjJRB   s *DjJ! RB  @ s *DjJ x 2   <( jJ"`   E IDV$0'RB   s *DjJRB @ s *DjJ    Z o?"0@NNN?N D& &0'  <h "`  fIU (chinkapin) "   0 "`OK I c UNC (dante)   "2  <L jJ"`   GARPSPLT$0'  0D "`  kUnidata (lead1)&  "   <L "`  p d OU (aquaman)   "XB  0LDjJ' g h  c @A lead-adas-wrf1 p f  0A?"`K y  Hd38c?g  `Hurricane Emily data H  0޽h ? 33___PPT10i.Bw[+D=' = @B +rg<K18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-N  0 e ]  (  f2  0̙>"`  r  S  O%   2  <0 jJ"` E4 QData Assimilation$0'2  < jJ"`  CWRF$0'2  <| jJ"`,,  CWRF$0'RB @ s *DjJRB   s *DjJRB   s *DjJ! RB  @ s *DjJ x 2   <( jJ"`   E IDV$0'RB   s *DjJRB @ s *DjJ    Z o?"0@NNN?N D& &0'  <h "`  fIU (chinkapin) "   0 "`OK I c UNC (dante)   "2  <L jJ"`   GARPSPLT$0'  0D "`  kUnidata (lead1)&  "   <L "`  p d OU (aquaman)   "XB  0LDjJ' g h  c @A lead-adas-wrf1 p f  0A?"`K yH  0޽h ? 33___PPT10i.Bw[+D=' = @B +rKKڒ18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 0DppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 0DppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent Control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r 18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 0DppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/acAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 $(  $r $ S  O%   r $ S 0 1    Q $ 3 rh 88?"6@`NNN?N   qModel20!#!#    U $ 3 r 88?"6@`NNN?N o  u Resources2 0!#!#    P $ 3 rP 88?"6@`NNN?N 0  pData20!#!#    B $@ ZDo?"0@NNN?Np 0 q i $  f(9 88o?"0@NNN?N ;b Need resourcesR0!#!# !#!#    n  $  f,= 88o?"0@NNN?N *  Have more resourcesR0 !#!# !#!#    6  $ ZH 88o?"0@NNN?N P  tGet data2 0!#!#    ]  $ ZXQ 88o?"0@NNN?N  Have more dataR0 !#!#!#!#    B  $@ ZDo?"0@NNN?N` ` a B  $ ZDo?"0@NNN?N = B $ ZDo?"0@NNN?N B $ ZDo?"0@NNN?N L @B $ ZDo?"0@NNN?N D P \ $ ZT4 88o?"0@NNN?N   Have more dataR0 !#!#!#!#    H $ 0޽h ? ; F33___PPT10i.JP+D=' = @B +r =  O 18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 0DppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxy{|}~h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/acAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-rP O ψ 18( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed BlackPDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 0DppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0 Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)BPEL (aka WSBPEL and BPEL4WS) multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PP5PP}P PdPP5}  d* 0%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r ߈ 199( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)pBPEL (aka WSBPEL and BPEL4WS)  lower the cost for cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PaP5PP}P PdPPa5}  d<B 0,%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 p<(  p~ p s *Ȼ    ~ p s *p    H p 0޽h ? lb___PPT10i.cP;+D=' != @B +r #  199( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" 2___PPT9/ 0? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)pBPEL (aka WSBPEL and BPEL4WS)  lower the cost for cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PaP5PP}P PdPPa5}  d<B 0,%LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r  U7 1!9( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" 2___PPT9/ 0? %O  =rLEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)XBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBMs, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP6PP}P PdPPT6}  d<| 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 p<(  p~ p s *Ȼ    ~ p s *p    H p 0޽h ? lb___PPT10i.cP;+D=' != @B +r7 p e7 gs 19( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" 2___PPT9/ 0? %O  =pLEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d<| 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 p<(  p~ p s *Ȼ    ~ p s *p    H p 0޽h ? lb___PPT10i.cP;+D=' != @B +rs ʬ s  19( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" 2___PPT9/ 0? %O  =pLEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d<| 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r  1 9( / 0DDTimesmbolomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black" A .  @n?" dd@  @@`` H()  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hib$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@Q ̻ʚ;"v8ʚ;g47d7dp 0DppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hvh___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" 2___PPT9/ 0? %O  =^LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(# LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r  +" 1f;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-  0L0 0(  x  c $!O%  ! x  c $!P  ! H  0޽h ? lb___PPT10i.ɷn+D=' != @B +r_" ] ;" v` 1f;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZap      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~f DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r`  ` 1f;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-rT  0 1f;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r   d 1f;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r  t O 1f;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@o ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r:O  O 1f;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-r܊  J 1|;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather '"*(/='"*(/  =    ' Comments?    /    PLyonl1< 08  .,=>5/2347:-  0 X<(  X~ X s *! O%   ~ X s *" B   H X 0޽h ? 33___PPT10i.[g+D=' != @B +r~  Z  1|;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather '"*(/='"*(/  =    ' Comments?    /    PLyonl1< 08  .,=>5/2347:-r  _@ 1;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =)LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsMStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location and action Integrated decision process performance and reliability guarantees application, weather ')"*(/=')"*(/  =    '" Comments?    /    PLyonl1< 08  .,=>5/2347:-  0 X<(  X~ X s *! O%   ~ X s *" B   H X 0޽h ? 33___PPT10i.[g+D=' != @B +r@ #| o@ ~ 1};( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsBStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  =    \ Comments?    /    PLyonl1< 08  .,=>5/2347:-  0 X<(  X~ X s *! O%   ~ X s *" B   H X 0޽h ? 33___PPT10i.[g+D='  = @B +r~  ~  1[;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsBStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  =     Comments?    /    PLyonl1< 08  .,=>5/2347:-rZ 6 1F;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?    /    PLyonl1< 08  .,=>5/2347:-  0 X<(  X~ X s *! O%   ~ X s *"     H X 0޽h ? 33___PPT10i.[g+D=' != @B +r ?4 61F;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple impleme ntations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture Virtual Grid provides LEADDynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?    /    PLyonl1< 08  .,=>5/2347:-r76fr1~;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?    /    PLyonl1< 08  .,=>5/2347:-8  0 OG ##<(  <~ < s * O%   ~ < s *     ` < T o))?(0~v0___PPT106___PPT9 VDVCW"c   a < T o))?p f ~v0___PPT106___PPT9 WvgFAB"c   ~2 < H8c?"`  e < T o))? "2F ~v0___PPT106___PPT9 [ vgES APIs"  c   o < T o))?V j ~v0___PPT106___PPT9 evgMON"c   L Cb   <#  PZ  < s *ffZ  < s *fLZ  < s *3Cb Z  < s *b Z < s *b Z < s *b LZ < s *CZ < s *Z < s *33LZ < s *Z < s *Lb Z < s *b f2 < < "` P~v0___PPT106___PPT9 fInformation Services"c   ^B < 6Do _ ^B < 6Dopr < T o))?X L ~v0___PPT106___PPT9 hvgLAUNCH"  c   |" <  ` Go?"  ~v0___PPT106___PPT9 XVG&g   |" <  `l Go?" @@:~v0___PPT106___PPT9 XVG&g   |" <  `d G33o?"` ~v0___PPT106___PPT9 XVG&g   ^B <@ 6Do P ^B <@ 6DoRq < T o))?j @  ~v0___PPT106___PPT9 gvgAgent"c     < <X 8c?"`V HGrid Resources #L !< N o))?"` P~v0___PPT106___PPT9 :&g  3c2 "< < "`g~v0___PPT106___PPT9 cResource Managers"c   ^B #<@ 6DopH < 0޽h ? 33___PPT10i.d3+D='  = @B +rr  vr`1~;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD ArchitectureLEAD Monitoring Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?    /    PLyonl1< 08  .,=>5/2347:-rx"1~;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?  LEAD Monitoring Architecture  /    PLyonl1< 08  .,=>5/2347:-rV 2A1d;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w       !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?  LEAD Monitoring Architecture  /    PLyonl1< 08  .,=>5/2347:-rBA|}1d;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?  LEAD Monitoring Architecture  /    PLyonl1< 08  .,=>5/2347:-r}}1d;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?  LEAD Monitoring Architecture  /    PLyonl1< 08  .,=>5/2347:-rP,1d;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?  LEAD Monitoring Architecture  /    PLyonl1< 08  .,=>5/2347:-r\01d;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?  LEAD Monitoring Architecture  /    PLyonl1< 08  .,=>5/2347:-r0l0k1d;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?  LEAD Monitoring Architecture  /    PLyonl1< 08  .,=>5/2347:-r0l l1d;( Z/ 0DTimesngsomanhh w 0 DCLB Helvetica Condensed Black DComic Sans MSCondensed BlackB0DZapf DingbatsCondensed Black@DArialingbatsCondensed Black"PDMS PGothictsCondensed Black"`DGenevahictsCondensed BlackpDTahomahictsCondensed Black"DTimes New Romanndensed BlackDStarSymbolomanndensed BlackDtrSymbolomanndensed Black"DWingdingsomanndensed Black A .  @n?" dd@  @@`` X**  !; QQRS{C Q Qk ;+ ;+[a&%<%$RN:$&I$$J1  @ 3 2&   : )M8V8x   - ?@ AB#CDEFbGH2IJKLMN3OPIQR$S;T0W>XYZM[\&]^_b+cdef&hikb$GDw}l+k6{/nb$6hпCFUGF> R$ g'#ɶU2$|JÏ5*?,rb$kB<zK~ay$R$͵=m6ezeIv(K9.b$ϘtS+r`8 $$R$=u>kjpq# lAA8c? f@@ ̻ʚ;"v8ʚ;g47d7dp 08ppK <4!d!d4w 0hv<4dddd4w 0hv<4dddd4w 0hv"h___PPT2001D<4X___PPT10DMS PGothichh0 0"DArialthichh0 0" Dtalthichh0 0" ___PPT9h/ 0L4? %O  =LEAD Workflow Orchestration,Lavanya Ramakrishnan Renaissance Computing Institute University of North Carolina  Chapel Hill Duke University North Carolina State University& [$ |OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management t)D)D  -Linked Environments for Atmospheric DiscoveryRationale each year, mesoscale weather  floods, tornadoes, hail, strong winds, lightning, hurricanes and winter storms  causes hundreds of deaths, routinely disrupts transportation and commerce, and results in annual economic losses in excess of $13B. From  offline to  online forecasting data assimilation and adaptive evaluationL '* '*Static ForecastingrLarge-scale tightly coupled components not adaptable to weather or resource behavior modifications are not trivial&'L'LDynamic Adaptive LEAD SystemMeteorology goal to provide timely and accurate forecasts using dynamic adaptation Computer Science goal map application requirements to resource capabilities redundant runs, scheduling policies adapt to weather as well as resource behaviortB7$.B7$.LEAD Control and Data FlowService Oriented LEAD Workflows*Business Process Execution Language (BPEL)VBPEL (aka WSBPEL and BPEL4WS) enable cross-enterprise automated business processes multiple vendor participation Oracle, Microsoft, IBM, SUN, SAP, BEA, EDS, Adobe, & multiple implementations Oracle BPEL, IBM BPWS4J and Microsoft BizTalk Process Managers, Active BPEL (www.activebpel.org) Open Source Process Manager Features loop and control logic, synchronous/asynchronous communication composition and concurrent execution PTP5PP}P PdPPT5}  d* 0 %LEAD Site Visit Experimental Ensemble !Characteristics of LEAD WorkflowsFCoupled analysis and assimilation tools, data repositories change configuration rapidly and automatically in response to weather Streaming data, steer remote observing technologies Multilevel monitoring and intelligent control workflow, resource, application, service performance and reliability guarantees of the resourcesL<{/a<{/aAdapting Workflow StructureReactive Adaptation e.g. service failure, resource behavior Proactive prediction and decisions adjust i, j, k (weather science meets the infrastructure science) to meet individual workflow guarantees global optimization of number of workflows being servicedL(#(#OutlineBackground and LEAD Service Architecture web services, BPEL LEAD Workflows status, site visit example run characteristics, workflow structures LEAD Virtual Grid Integration resource management )   D )D   LEAD ArchitectureLEAD Architecture 8Virtual Grid provides LEAD & Dynamic, scalable resource abstraction framework scheduler, resource broker Integrated monitoring and notification of resource behavior NWS, NWS-HAPIL1<1< FProposed LEAD  VGrADS Architecture$$b &   Some Thoughts & LEAD Dynamic Workflows vgDL Specification for LEAD 'LEAD Virtual Grid Research ImplicationsAStreaming data in resource scheduling fixed point makes scheduling complicated Persistent and transient services service directory, monitoring, scheduling Data management across the virtual grid run time knowledge of data location Integrated decision process performance and reliability guarantees application, weather ')"*($=')"*($  = Comments?  LEAD Monitoring Architecture  /    PLyonl1< 08  .,=>5/2347:-rЧ<1      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|~      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|~ersityersityPowerPoint Document( pDocumentSummaryInformation8Proposed LEAD – VGrADS ArchitectureSome Thoughts …LEAD Dynamic WorkflowsvgDL Specification for LEAD (LEAD Virtual Grid Research Implications Comments? LEAD Monitoring Architecture Slide 23Lyon  Fonts Used Design Template Slide Title'_L)Rice UniversityRice Univs Custom Shows4 $,