Staff View: Cloud customers service selection scheme based on improved conventional cat swarm optimization

Cloud customers service selection scheme based on improved conventional cat swarm optimization

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...

Full description

Saved in:

Bibliographic Details
Main Authors:	Gabi, Danlami, Ismail, Abdul Samad, Zainal, Anazida, Zakaria, Zalmiyah, Abraham, Ajith, Muhammed Dankolo, Nasiru
Format:	Article
Language:	English
Published:	Springer Science and Business Media Deutschland GmbH 2020
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://eprints.utm.my/id/eprint/91714/1/AbdulSamadIsmail2020_CloudCustomersServiceSelectionScheme.pdf http://eprints.utm.my/id/eprint/91714/ http://dx.doi.org/10.1007/s00521-020-04834-6
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my.utm.91714
record_format	eprints
spelling	my.utm.917142021-07-27T05:46:21Z http://eprints.utm.my/id/eprint/91714/ Cloud customers service selection scheme based on improved conventional cat swarm optimization Gabi, Danlami Ismail, Abdul Samad Zainal, Anazida Zakaria, Zalmiyah Abraham, Ajith Muhammed Dankolo, Nasiru QA75 Electronic computers. Computer science 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. Springer Science and Business Media Deutschland GmbH 2020-09 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/91714/1/AbdulSamadIsmail2020_CloudCustomersServiceSelectionScheme.pdf Gabi, Danlami and Ismail, Abdul Samad and Zainal, Anazida and Zakaria, Zalmiyah and Abraham, Ajith and Muhammed Dankolo, Nasiru (2020) Cloud customers service selection scheme based on improved conventional cat swarm optimization. Neural Computing and Applications, 32 (18). pp. 14817-148381. ISSN 0941-0643 http://dx.doi.org/10.1007/s00521-020-04834-6 DOI:10.1007/s00521-020-04834-6
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Gabi, Danlami Ismail, Abdul Samad Zainal, Anazida Zakaria, Zalmiyah Abraham, Ajith Muhammed Dankolo, Nasiru Cloud customers service selection scheme based on improved conventional cat swarm optimization
description	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.
format	Article
author	Gabi, Danlami Ismail, Abdul Samad Zainal, Anazida Zakaria, Zalmiyah Abraham, Ajith Muhammed Dankolo, Nasiru
author_facet	Gabi, Danlami Ismail, Abdul Samad Zainal, Anazida Zakaria, Zalmiyah Abraham, Ajith Muhammed Dankolo, Nasiru
author_sort	Gabi, Danlami
title	Cloud customers service selection scheme based on improved conventional cat swarm optimization
title_short	Cloud customers service selection scheme based on improved conventional cat swarm optimization
title_full	Cloud customers service selection scheme based on improved conventional cat swarm optimization
title_fullStr	Cloud customers service selection scheme based on improved conventional cat swarm optimization
title_full_unstemmed	Cloud customers service selection scheme based on improved conventional cat swarm optimization
title_sort	cloud customers service selection scheme based on improved conventional cat swarm optimization
publisher	Springer Science and Business Media Deutschland GmbH
publishDate	2020
url	http://eprints.utm.my/id/eprint/91714/1/AbdulSamadIsmail2020_CloudCustomersServiceSelectionScheme.pdf http://eprints.utm.my/id/eprint/91714/ http://dx.doi.org/10.1007/s00521-020-04834-6
_version_	1706956983874093056
score	13.211869

Cloud customers service selection scheme based on improved conventional cat swarm optimization

Similar Items