Hybrid cat swarm optimization and simulated annealing for dynamic task scheduling on cloud computing environment

In this study, a Cloud Scalable Multi-Objective Cat Swarm Optimization-based Simulated Annealing algorithm is proposed. In the proposed method, the orthogonal Taguchi approach is applied to enhance the SA which is incorporated into the local search of the proposed CSMCSOSA algorithm for scalability performance. | Journal of ICT, 17, No. 3 (July) 2018, pp: 435–467 How to cite this paper: Gabi, D., Ismail, A S., Zainal, A., Zakaria, Z., & Al-Khasawneh, A. (2018). Hybrid cat swarm optimization and simulated annealing for dynamic task scheduling on cloud computing environment. Journal of Information and Communication Technology, 17(3), 435-467. HYBRID CAT SWARM OPTIMIZATION AND SIMULATED ANNEALING FOR DYNAMIC TASK SCHEDULING ON CLOUD COMPUTING ENVIRONMENT Danlami Gabi, 2Abdul Samad Ismail, 2Anazida Zainal, 2 Zalmiyah Zakaria & 3Ahmad Al-Khasawneh 1 Department of Kebbi State University of Science and Technology, Aliero, Nigeria 2 Faculty of Computing, Universiti Teknologi Malaysia, Malaysia 3 Faculty of Prince Al-Hussein bin Abdullah II of Information Technology, Hashemite University, Zarqa, Jordan 1 gabsonley@; abdsamad@; anazida@; zalmiyah@; akhasawneh@ ABSTRACT The unpredictable number of task arriving at cloud datacentre and the rescaling of virtual processing elements can affect the provisioning of better Quality of Service expectations during task scheduling in cloud computing. Existing researchers have contributed several task scheduling algorithms to provide better QoS expectations but are characterized with entrapment at the local search and high dimensional breakdown due to slow convergence speed and imbalance between global and local search, resulting from lack of scalability. Dynamic task scheduling algorithms that can adjust to long-time changes and continue facilitating the provisioning of better QoS are necessary for cloud computing environment. In this study, a Cloud Scalable Multi-Objective Cat Swarm Optimization-based Simulated Annealing algorithm is proposed. In the proposed method, the Received: 8 August 2017 Accepted: 10 April 2018 435 Published: 12 June 2018 Journal of ICT, 17, No. 3 (July) 2018, pp: 435–467 . orthogonal Taguchi approach is applied to enhance the SA which is incorporated into the local search