Ensemble Scheduling: Resource Co-Allocation on the Computational Grid
GRID '01 Proceedings of the Second International Workshop on Grid Computing
Distributed Dynamic Scheduling of Composite Tasks on Grid Computing Systems
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Grids
PARA '02 Proceedings of the 6th International Conference on Applied Parallel Computing Advanced Scientific Computing
Genetic Scheduling on Minimal Processing Elements in the Grid
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Platforms
IEEE Transactions on Parallel and Distributed Systems
Adaptive Allocation of Independent Tasks to Maximize Throughput
IEEE Transactions on Parallel and Distributed Systems
| Hi-index | 0.00 |
In this paper, we present a scalable scheduling heuristic for several common classes of multi-component applications (meta-applications). We consider this scheduling problem in a wide-area heterogeneous computing environment, or metasystem. The heterogeneity and scale of the computing environment and the heterogeneity of the application make this a challenging problem.We have studied the performance of the heuristic in simulation and the results are encouraging. Completion times for three common classes of meta-applications were within 10-20% of optimal on average with a worst-case variance of 60%. The results suggest that effective scheduling of meta-applications is possible, if sufficient application and system resource cost information is provided.