Authors: Yongxuan Sang; Zhongwen Li; Tien-Hsiung Weng; Bo Wang
Addresses: Software Engineering College, Zhengzhou University of Light Industry, No. 136 Kexue Road, Zhengzhou, China ' College of Computer, Chengdu University, Chengdu, China ' Department of Computer Science and Information Engineering, Providence University, 200, Sec. 7, Taiwan Boulevard, Shalu Dist., Taichung City 43301, Taiwan ' Software Engineering College, Zhengzhou University of Light Industry, No. 136 Kexue Road, Zhengzhou, China
Abstract: Task scheduling is one of the key techniques for effective and reliable resource usage in cloud computing. In this paper, we designed a hybrid heuristic scheduling that employed particle swarm optimisation (PSO) and least accumulated slack time to respectively address the problem of assigning tasks to servers and the problem of the task scheduling for multi-core servers, to maximise the service level agreement (SLA) satisfaction for resource efficiency improvement and task execution in heterogeneous clouds with deadline constraints. Experimental results show that our method can complete up to 112.5% more tasks, compared with several classical and state-of-art task scheduling methods.
Keywords: cloud computing; hybrid heuristic; service level agreement; SLA; task scheduling; particle swarm optimisation; PSO.
International Journal of Computational Science and Engineering, 2021 Vol.24 No.5, pp.463 - 472
Received: 27 Nov 2020
Accepted: 08 Dec 2020
Published online: 12 Oct 2021 *