A self-adaptive load balancing strategy for p2p grids

Authors:
Po-Jung Huang;You-Fu Yu;Quan-Jie Chen;Tian-Liang Huang;Kuan-Chou Lai;Kuan-Ching Li
Affiliations:
Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer and Information Science, National Taichung University, Taichung, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan, R.O.C.
Venue:
ICA3PP'10 Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part II
Year:
2010

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Abstract

The grid computing system becomes a promising platform for high performance computing. Recently, grid systems integrate with the P2P technology to enhance the efficiency of distributed computing. Load balancing is one of the most important issues in P2P grid systems, and the efficiency of the resource utilization is also one of the key issues. This study proposes a Self-Adaptive Load Balancing (SALB) strategy to improve the efficiency of load balancing. SALB selects appropriate neighbors according to the Small World Theory; then, the proposed strategy transfers jobs to these neighbors in order to distribute load. Experimental results show that the proposed algorithm performs well and that the SALB strategy could improve the resource utilization and shorten the job completion time.