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An Artificial Immune System for Heterogeneous Multiprocessor Scheduling with Task Duplication

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2 Author(s)
Young Choon Lee ; Advanced Networks Research Group, School of Information Technologies, The University of Sydney, NSW 2006, Australia. yclee@it.usyd.edu.au ; Albert Y. Zomaya

In this study, we investigate the task scheduling problem in heterogeneous computing environments and propose a novel scheduling algorithm, called the artificial immune system with duplication (AISD) algorithm that efficiently tackles the problem. The AISD algorithm incorporates the clonal selection principle in the immune system and task duplication into the scheduling process. Based on the performance results obtained from extensive experiments conducted with a comprehensive set of both randomly generated and well-known application task graphs and various system configurations, AISD consistently outperformed the two existing algorithms by a noticeable margin, especially when scheduling communication intensive task graphs.

Published in:

2007 IEEE International Parallel and Distributed Processing Symposium

Date of Conference:

26-30 March 2007