Matchmaking: Distributed Resource Management for High Throughput Computing
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
Combinatorial Auction-Based Protocols for Resource Allocation in Grids
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 13 - Volume 14
The Computational and Storage Potential of Volunteer Computing
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Resource Selection in Grids Using Contract Net
PDP '08 Proceedings of the 16th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2008)
Incentive-Based Scheduling for Market-Like Computational Grids
IEEE Transactions on Parallel and Distributed Systems
Resource Discovery Techniques in Distributed Desktop Grid Environments
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Using Data Accessibility for Resource Selection in Large-Scale Distributed Systems
IEEE Transactions on Parallel and Distributed Systems
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Large-scale distributed system provides an attractive scalable infrastructure for network applications. In such environment there exist large sets of heterogeneous and geographically distributed resources. These resources can be aggregated as a virtual computing platform for executing large-scale scientific applications. Among numerous optional resources, selecting appropriate resources for applications is challenging and affected by many factors. The loosely coupled nature of large-scale distributed environment makes data access unpredictable and instability. Slow allocation process may offset the benefit obtained by running a job on a fast node. Besides, the operation condition of a resource provider changes rapidly. The status of job execution and computing capability of a resource provider need to be considered dynamically. In this paper we present an approach of dynamic task-sharing based on the record of previous data download and current execution status of resource providers to select the appropriate one or more providers to execute a job together. The proposed approach can also avoids single point failure and server overload problem.