标题:A novel discrete particle swarm optimization algorithm for meta-task assignment in heterogeneous computing systems
作者:Qinma Kang;Hong He
作者机构:[Kang, Q] Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai 201804, China, School of Informa 更多
通讯作者:Kang, Q
通讯作者地址:[Kang, QM]Shandong Univ Weihai, Sch Informat Engn, Weihai 264209, Peoples R China.
来源:Microprocessors and microsystems
出版年:2011
卷:35
期:1
页码:10-17
DOI:10.1016/j.micpro.2010.11.001
关键词:discrete particle swarm optimization;variable neighborhood descent;task assignment;heterogeneous computing;exploration and exploitation
摘要:Optimal assignment of a meta-task in heterogeneous computing systems is NP-complete in the general case. Therefore, heuristic approaches must be employed to find good solutions within a reasonable time. We propose a novel discrete particle swarm optimization (DPSO) algorithm for this problem. Firstly, to make particle swarm optimization algorithm more suitable for solving task assignment problems, particles are represented as integer vectors and a new position update method is developed based on discrete domain. Secondly, an effective variable neighborhood descent algorithm is applied to emphasize exploitation. In addition, migration mechanism is introduced with the hope to escape from possible local optimum and to balance the exploration and exploitation. Computational simulations and comparisons based on a set of benchmark instances indicate that the proposed DPSO algorithm is a viable approach for the task assignment problem.
收录类别:EI;SCOPUS;SCIE
WOS核心被引频次:25
Scopus被引频次:32
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-78649967706&doi=10.1016%2fj.micpro.2010.11.001&partnerID=40&md5=df0fa201c09ec459f489089234c508f7
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