Cloud customers service selection scheme based on improved conventional cat swarm optimization
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ORIGINAL ARTICLE
Cloud customers service selection scheme based on improved conventional cat swarm optimization Danlami Gabi1,2 • Abdul Samad Ismail3 • Anazida Zainal3 • Zalmiyah Zakaria3 • Ajith Abraham4 Nasiru Muhammed Dankolo3
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Received: 15 February 2019 / Accepted: 5 March 2020 The Author(s) 2020
Abstract With growing demand on resources situated at the cloud datacenters, the need for customers’ resource selection techniques becomes paramount in dealing with the concerns of resource inefficiency. Techniques such as metaheuristics are promising than the heuristics, most especially when handling large scheduling request. However, addressing certain limitations attributed to the metaheuristic such as slow convergence speed and imbalance between its local and global search could enable it become even more promising for customers service selection. In this work, we propose a cloud customers service selection scheme called Dynamic Multi-Objective Orthogonal Taguchi-Cat (DMOOTC). In the proposed scheme, avoidance of local entrapment is achieved by not only increasing its convergence speed, but balancing between its local and global search through the incorporation of Taguchi orthogonal approach. To enable the scheme to meet customers’ expectations, Pareto dominant strategy is incorporated providing better options for customers in selecting their service preferences. The implementation of our proposed scheme with that of the benchmarked schemes is carried out on CloudSim simulator tool. With two scheduling scenarios under consideration, simulation results show for the first scenario, our proposed DMOOTC scheme provides better service choices with minimum total execution time and cost (with up to 42.87%, 35.47%, 25.49% and 38.62%, 35.32%, 25.56% reduction) and achieves 21.64%, 18.97% and 13.19% improvement for the second scenario in terms of execution time compared to that of the benchmarked schemes. Similarly, statistical results based on 95% confidence interval for the whole scheduling scheme also show that our proposed scheme can be much more reliable than the benchmarked scheme. This is an indication that the proposed DMOOTC can meet customers’ expectations while providing guaranteed performance of the whole cloud computing environment. Keywords Cloud computing Scheduling Cat swarm optimization Pareto dominance
& Danlami Gabi [email protected]
1
Abdul Samad Ismail [email protected]
Department of Computer Science, Faculty of Science, Kebbi State University of Science and Technology, Aliero, Kebbi State, Nigeria
2
Anazida Zainal [email protected]
Department of Computing Science, Umea University, Umea˚, Sweden
3
Zalmiyah Zakaria [email protected]
Department of Computer Science, School of Computing, Universiti Teknologi Malaysia, Johor, Malaysia
4
Machine Intelligence Research Labs, Scientific Network for Innovation and Research Excellence, Auburn, WA 98071, USA
Ajith Abraham [email protected] Nasiru Muhammed Dankolo [email protected]
123
Neur
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