Cloud workflow scheduling algorithm based on multi-objective hybrid particle swarm optimisation. (24th September 2021)

• Record Type: Journal Article
• Authors: Dai, Gang; Xu, Baomin; Peng, Jianfeng; Zhang, Lei
• Is Part Of: International journal of grid and utility computing. Volume 12:Number 3(2021)
• Page Start: 287
• Page End: 301
• Publication Date: 2021-09-24
• Subjects: hill climbing algorithm -- task scheduling -- particle swarm optimisation -- cloud workflow; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

Particle swarm optimisation has been widely used in solving scheduling problems. This paper proposes a hybrid algorithm namely Hill Climbing with Multi-objective Particle Swarm Optimisation called HCMOPSO, which is based on heuristic local search and multi-objective particle swarm optimisation algorithm. HCMOPSO introduces hill climbing optimisation techniques into particle swarm optimisation algorithm to improve the local search ability. Experimental results show that the HCMOPSO is an effective cloud workflow scheduling algorithm, which has faster convergence velocity and better optimisation ability.