In this paper we propose an adaptive scheduling approach designed to improve the performance of parallel applications in Computational Grid environments. A primary contribution of our work is that our design is decoupled, thus providing a separation of the scheduler itself from the application-specific components needed for the scheduling process. As part of the scheduler, we have also developed an application-generic resource selection procedure that effectively and efficiently identifies desirable resources.

As test cases for our approach, we selected two applications from the class of iterative, mesh-based applications. We used a prototype of our approach with these applications to perform validation experiments in production Grid environments. Our results show that our scheduler, albeit decoupled, provides significantly better application performance than conventional scheduling strategies. We also show that our scheduler gracefully handles degraded levels of availability of application and Grid resource information. Finally, we demonstrate that the overhead associated with our methodology is reasonable. This work evolved in the context of the Grid Application Development Software Project (GrADS). Our approach has been integrated with other GrADS software tools and, in that context, has been applied to three real-world applications by other members of the project.