Yang-Suk Kee, Henri Casanova, and Andrew Chien (2004)
Realistic Modeling and Synthesis of Resources for Computational Grids
In: ACM Conference on High Performance Computing and Networking (SC2004), ACM Press.
Understanding large Grid platform configurations and generating representative synthetic configurations is critical for a broad range of Grid computing research. This paper presents an analysis of existing resource configurations and proposes a Grid platform generator that synthesizes realistic configurations of both computing and communication resources. Our key contributions include the development of statistical models for currently deployed resources and techniques that use this base to estimate the characteristics of future systems. Through the analysis of the cluster configurations of 114 clusters and over 10,000 processors, we identify appropriate distributions for many typical cluster resource configuration parameters. Using well-established statistical tests, we validate our models against a second resource collection of 191 clusters and over 10,000 processors, and show that our models effectively capture the resource characteristics found in the real world resource infrastructures. These models are realized in a resource generator which can be easily recalibrated by running it on a training sample set, and the model generates representative resource configurations for current and extrapolates to future resource configurations.