Improving grid resource allocation via integrated selection and binding
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Self-adaptive applications on the grid
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
Scheduling Policies for Processor Coallocation in Multicluster Systems
IEEE Transactions on Parallel and Distributed Systems
Inter-operating grids through delegated matchmaking
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Inter-operating grids through Delegated MatchMaking
Scientific Programming - Large-Scale Programming Tools and Environments
Dynamic photonic lightpaths in the StarPlane network
Future Generation Computer Systems
Fair resource sharing in hierarchical virtual organizations for global grids
GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
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
On grid performance evaluation using synthetic workloads
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
Deadline-guarantee-enhanced co-allocation for parameter sweep application in grid
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
JSSPP'10 Proceedings of the 15th international conference on Job scheduling strategies for parallel processing
A multi-level scheduler for batch jobs on grids
The Journal of Supercomputing
Configurable performance analysis and evaluation framework for cloud systems
International Journal of Information and Communication Technology
Resource co-allocation framework based on hybrid gaming model in grid environments
International Journal of Grid and Utility Computing
International Journal of Computational Science and Engineering
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In multicluster systems, and more generally, in grids, jobs may require co-allocation, i.e., the simultaneous allocation of resources such as processors and input files in multiple clusters. While such jobs may have reduced runtimes because they have access to more resources, waiting for processors in multiple clusters and for the input files to become available in the right locations, may introduce inefficiencies. Moreover, as single jobs now have to rely on multiple resource managers, co-allocation introduces reliability problems. In this paper, we present two additions to the original design of our KOALA co-allocating scheduler (different priority levels of jobs and incrementally claiming processors), and we report on our experiences with KOALA in our multicluster testbed while it was unstable.