On Advantages of Grid Computing for Parallel Job Scheduling
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
Characterization of Bandwidth-Aware Meta-Schedulers for Co-Allocating Jobs Across Multiple Clusters
The Journal of Supercomputing
Software—Practice & Experience
Online resource matching for heterogeneous grid environments
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Backfilling with lookahead to optimize the packing of parallel jobs
Journal of Parallel and Distributed Computing
A performance model for analysis of heterogeneous multi-cluster systems
Parallel Computing
Backfilling Using System-Generated Predictions Rather than User Runtime Estimates
IEEE Transactions on Parallel and Distributed Systems
Scheduling Policies for Processor Coallocation in Multicluster Systems
IEEE Transactions on Parallel and Distributed Systems
Well-Balanced Allocation Strategy for Multi-Cluster Computing Environments
FTDCS '08 Proceedings of the 2008 12th IEEE International Workshop on Future Trends of Distributed Computing Systems
Resource Matching in Non-dedicated Multicluster Environments
High Performance Computing for Computational Science - VECPAR 2008
Time and cost trade-off management for scheduling parallel applications on Utility Grids
Future Generation Computer Systems
Optimal job packing, a backfill scheduling optimization for a cluster of workstations
The Journal of Supercomputing
Multisite co-allocation algorithms for computational grid
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Parallel job scheduling — a status report
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
Workload characteristics of a multi-cluster supercomputer
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
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Multi-cluster environments are composed of multiple clusters that act collaboratively, thus allowing computational problems that require more resources than those available in a single cluster to be treated. However, the degree of complexity of the scheduling process is greatly increased by the resources heterogeneity and the co-allocation process, which distributes the tasks of parallel jobs across cluster boundaries. In this paper, the authors propose a new MIP model which determines the best scheduling for all the jobs in the queue, identifying their resource allocation and its execution order to minimize the overall makespan. The results show that the proposed technique produces a highly compact scheduling of the jobs, producing better resources utilization and lower overall makespan. This makes the proposed technique especially useful for environments dealing with limited resources and large applications.