Title: A particle swarm optimisation algorithm for cloud-oriented workflow scheduling based on reliability

Authors: Chengfeng Jian; Meng Tao; Yekun Wang

Addresses: College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China ' College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China ' College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China

Abstract: Currently researches on workflow scheduling in cloud platform pay more attention to the execution time and cost. However, reliability of resource suppliers affects the quality of cloud-oriented workflow scheduling. Reliability of schedule is determined together by the reliability of a cloud resource provider tasks and network data transmission between suppliers. A particle swarm optimisation (PSO) algorithm is presented to schedule tasks to cloud resource suppliers that takes into account reliability as the main factor influencing to schedule workflow. After comparing PSO and genetic algorithm (GA), experiments show that PSO can achieve a higher reliability.

Keywords: cloud-oriented workflow; supplier reliability; PSO; particle swarm optimisation; particle swarm workflow scheduling; cloud computing; genetic algorithms.

DOI: 10.1504/IJCAT.2014.066731

International Journal of Computer Applications in Technology, 2014 Vol.50 No.3/4, pp.220 - 225

Published online: 07 Feb 2015 *

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