Scheduling mixed-parallel applications with advance reservations
HPDC '08 Proceedings of the 17th international symposium on High performance distributed computing
Resource co-allocation for large-scale distributed environments
Proceedings of the 18th ACM international symposium on High performance distributed computing
Measuring Fragmentation of Two-Dimensional Resources Applied to Advance Reservation Grid Scheduling
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Rescheduling co-allocation requests based on flexible advance reservations and processor remapping
GRID '08 Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing
Scheduling mixed-parallel applications with advance reservations
Cluster Computing
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Applications to be executed in Grid computing environments become more and more complex and usually consist of multiple interdependent tasks. The coordinated execution of such tightly or loosely coupled tasks often requires simultaneous access to different Grid resources. This leads to the problem of resource co-allocation. Efficient and robust scheduling algorithms have to be developed that can cope with the Grid's largescale distribution, a high number of competing and demanding applications, the inherent resource heterogeneity and the often limited view on resource availability. In this paper, we present two heuristic scheduling algorithms that are based on a well-known list scheduling algorithm and both support coallocation and advance resource reservation. Our first algorithm preserves the run-time efficiency of Greedy list schedulers while the second approach incorporates more sophisticated search techniques in order to achieve better results with respect to the performance metrics. Both algorithms have been implemented within a Grid simulation framework. An extensive simulation study was conducted to evaluate and compare the performance of both algorithms. It showed the general suitability of our enhanced list scheduling heuristics within heterogeneous Grid environments.