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ABSTRACT
Desktop grids have evolved to combine Peer-to-Peer and Grid computing techniques to improve the robustness, reliability and scalability of job execution infrastructures. However, efficiently matching incoming jobs to available system resources and achieving good load balance in a fully decentralized and heterogeneous computing environment is a challenging problem. In this paper, we extend our prior work with a new decentralized algorithm for maintaining approximate global load information, and a job pushing mechanism that uses the global information to push jobs towards underutilized portions of the system. The resulting system more effectively balances load and improves overall system throughput. Through a comparative analysis of experimental results across different system configurations and job profiles, performed via simulation, we show that our system can reliably execute Grid applications on a distributed set of resources both with low cost and with good load balance.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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[doi> 10.1145/863955.863976]
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CITED BY 2
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Jik-Soo Kim , Beomseok Nam , Peter Keleher , Michael Marsh , Bobby Bhattacharjee , Alan Sussman, Trade-offs in matching jobs and balancing load for distributed desktop grids, Future Generation Computer Systems, v.24 n.5, p.415-424, May, 2008
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Jik-Soo Kim , Beomseok Nam , M. Marsh , P. Keleher , B. Bhattacharjee , A. Sussman, Integrating categorical resource types into a P2P desktop grid system, Proceedings of the 2008 9th IEEE/ACM International Conference on Grid Computing, p.284-291, September 29-October 01, 2008
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