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Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing

In cloud computing datacenter, task execution delay is a common phenomenal cause by task imbalance across virtual machines (VMs). In recent times, a number of artificial intelligence scheduling techniques are applied to reduced task execution delay. These techniques have contributed toward the need...

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Main Authors: Gabi, Danlami, Ismail, Abdul Samad, Zainal, Anazida, Zakaria, Zalmiyah, Abraham, Ajith
Format: Article
Published: Springer London 2018
Subjects:
QA76 Computer software
Online Access:http://eprints.utm.my/id/eprint/72790/
http://dx.doi.org/10.1007/s00521-016-2816-4
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spelling my.utm.727902020-08-05T03:15:53Z http://eprints.utm.my/id/eprint/72790/ Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing Gabi, Danlami Ismail, Abdul Samad Zainal, Anazida Zakaria, Zalmiyah Abraham, Ajith QA76 Computer software In cloud computing datacenter, task execution delay is a common phenomenal cause by task imbalance across virtual machines (VMs). In recent times, a number of artificial intelligence scheduling techniques are applied to reduced task execution delay. These techniques have contributed toward the need for an ideal solution. The objective of this study is to optimize task scheduling based on proposed orthogonal Taguchi-based cat swarm optimization (OTB-CSO) in order to reduce total task execution delay. In our proposed algorithm, Taguchi orthogonal approach was incorporated into tracing mode of CSO to scheduled tasks on VMs with minimum execution time. CloudSim tool was used to implement the proposed algorithm where the impact of the algorithm was checked with 5, 10 and 20 VMs besides input tasks and evaluated based on makespan and degree of imbalance metrics. Experimental results showed that for 20 VMs used, our proposed OTB-CSO was able to minimize makespan of the total tasks scheduled across VMs with 42.86, 34.57 and 2.58% improvement over minimum and maximum job first (Min–Max), particle swarm optimization with linear descending inertia weight (PSO-LDIW) and hybrid PSO with simulated annealing (HPSO-SA) and likewise returned degree of imbalance with 70.03, 62.83 and 35.68% improvement over existing algorithms. Results obtained showed that OTB-CSO is effective to optimize task scheduling and improve overall cloud computing performance through minimizing task execution delay while ensuring better system utilization. Springer London 2018-09 Article PeerReviewed Gabi, Danlami and Ismail, Abdul Samad and Zainal, Anazida and Zakaria, Zalmiyah and Abraham, Ajith (2018) Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing. Neural Computing and Applications, 30 (6). pp. 1845-1863. ISSN 0941-0643 http://dx.doi.org/10.1007/s00521-016-2816-4 DOI:10.1007/s00521-016-2816-4
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/
topic QA76 Computer software
spellingShingle QA76 Computer software
Gabi, Danlami
Ismail, Abdul Samad
Zainal, Anazida
Zakaria, Zalmiyah
Abraham, Ajith
Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing
description In cloud computing datacenter, task execution delay is a common phenomenal cause by task imbalance across virtual machines (VMs). In recent times, a number of artificial intelligence scheduling techniques are applied to reduced task execution delay. These techniques have contributed toward the need for an ideal solution. The objective of this study is to optimize task scheduling based on proposed orthogonal Taguchi-based cat swarm optimization (OTB-CSO) in order to reduce total task execution delay. In our proposed algorithm, Taguchi orthogonal approach was incorporated into tracing mode of CSO to scheduled tasks on VMs with minimum execution time. CloudSim tool was used to implement the proposed algorithm where the impact of the algorithm was checked with 5, 10 and 20 VMs besides input tasks and evaluated based on makespan and degree of imbalance metrics. Experimental results showed that for 20 VMs used, our proposed OTB-CSO was able to minimize makespan of the total tasks scheduled across VMs with 42.86, 34.57 and 2.58% improvement over minimum and maximum job first (Min–Max), particle swarm optimization with linear descending inertia weight (PSO-LDIW) and hybrid PSO with simulated annealing (HPSO-SA) and likewise returned degree of imbalance with 70.03, 62.83 and 35.68% improvement over existing algorithms. Results obtained showed that OTB-CSO is effective to optimize task scheduling and improve overall cloud computing performance through minimizing task execution delay while ensuring better system utilization.
format Article
author Gabi, Danlami
Ismail, Abdul Samad
Zainal, Anazida
Zakaria, Zalmiyah
Abraham, Ajith
author_facet Gabi, Danlami
Ismail, Abdul Samad
Zainal, Anazida
Zakaria, Zalmiyah
Abraham, Ajith
author_sort Gabi, Danlami
title Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing
title_short Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing
title_full Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing
title_fullStr Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing
title_full_unstemmed Orthogonal Taguchi-based cat algorithm for solving task scheduling problem in cloud computing
title_sort orthogonal taguchi-based cat algorithm for solving task scheduling problem in cloud computing
publisher Springer London
publishDate 2018
url http://eprints.utm.my/id/eprint/72790/
http://dx.doi.org/10.1007/s00521-016-2816-4
_version_ 1675327330001616896
score 13.211869

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