Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing

The rise in demand for cloud resources (network, hardware and software) requires cost effective scientific workflow scheduling algorithm to reduce cost and balance load of all jobs evenly for a better system throughput. Getting multiple scientific workflows scheduled with a reduced makespan and cost...

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Main Authors: Konjaang, James Kok, Ayob, Fahrul Hakim, Muhammed, Abdullah
Format: Article
Language:English
Published: Science Publications 2018
Online Access:http://psasir.upm.edu.my/id/eprint/72134/1/Cost%20effective%20Expa-Max-Min%20scientific%20workflow%20allocation%20and%20load%20balancing%20strategy%20in%20cloud%20computing.pdf
http://psasir.upm.edu.my/id/eprint/72134/
https://thescipub.com/abstract/10.3844/jcssp.2018.623.638
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spelling my.upm.eprints.721342020-03-03T02:38:09Z http://psasir.upm.edu.my/id/eprint/72134/ Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing Konjaang, James Kok Ayob, Fahrul Hakim Muhammed, Abdullah The rise in demand for cloud resources (network, hardware and software) requires cost effective scientific workflow scheduling algorithm to reduce cost and balance load of all jobs evenly for a better system throughput. Getting multiple scientific workflows scheduled with a reduced makespan and cost in a dynamic cloud computing environment is an attractive research area which needs more attention. Scheduling multiple workflows with the standard Max-Min algorithm is a challenge because of the high priority given to task with maximum execution time first. To overcome this challenge, we proposed a new mechanism call Expanded Max-Min (Expa-Max-Min) algorithm to effectively give equal opportunity to both cloudlets with maximum and minimum execution time to be scheduled for a reduce cost and time. Expa-Max-Min algorithm first calculates the completion time of all the cloudlets in the cloudletList to find cloudlets with minimum and maximum execution time, then it sorts and queue the cloudlets in two queues based on their execution times. The algorithm first select a cloudlet from the cloudletList in the maximum execution time queue and assign it to a resource that produces minimum completion time, while executing cloudlets in the minimum execution time queue concurrently. The experimented results demonstrats that our proposed algorithm, Expa-Max-Min algorithm, is able to produce good quality solutions in terms of minimising average cost and makespan and able to balance loads than Max-Min and Min-Min algorithms. Science Publications 2018 Article NonPeerReviewed text en http://psasir.upm.edu.my/id/eprint/72134/1/Cost%20effective%20Expa-Max-Min%20scientific%20workflow%20allocation%20and%20load%20balancing%20strategy%20in%20cloud%20computing.pdf Konjaang, James Kok and Ayob, Fahrul Hakim and Muhammed, Abdullah (2018) Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing. Journal of Computer Science, 14 (5). 623 - 638. ISSN 1549-3636; ESSN: 1552-6607 https://thescipub.com/abstract/10.3844/jcssp.2018.623.638 10.3844/jcssp.2018.623.638
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The rise in demand for cloud resources (network, hardware and software) requires cost effective scientific workflow scheduling algorithm to reduce cost and balance load of all jobs evenly for a better system throughput. Getting multiple scientific workflows scheduled with a reduced makespan and cost in a dynamic cloud computing environment is an attractive research area which needs more attention. Scheduling multiple workflows with the standard Max-Min algorithm is a challenge because of the high priority given to task with maximum execution time first. To overcome this challenge, we proposed a new mechanism call Expanded Max-Min (Expa-Max-Min) algorithm to effectively give equal opportunity to both cloudlets with maximum and minimum execution time to be scheduled for a reduce cost and time. Expa-Max-Min algorithm first calculates the completion time of all the cloudlets in the cloudletList to find cloudlets with minimum and maximum execution time, then it sorts and queue the cloudlets in two queues based on their execution times. The algorithm first select a cloudlet from the cloudletList in the maximum execution time queue and assign it to a resource that produces minimum completion time, while executing cloudlets in the minimum execution time queue concurrently. The experimented results demonstrats that our proposed algorithm, Expa-Max-Min algorithm, is able to produce good quality solutions in terms of minimising average cost and makespan and able to balance loads than Max-Min and Min-Min algorithms.
format Article
author Konjaang, James Kok
Ayob, Fahrul Hakim
Muhammed, Abdullah
spellingShingle Konjaang, James Kok
Ayob, Fahrul Hakim
Muhammed, Abdullah
Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing
author_facet Konjaang, James Kok
Ayob, Fahrul Hakim
Muhammed, Abdullah
author_sort Konjaang, James Kok
title Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing
title_short Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing
title_full Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing
title_fullStr Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing
title_full_unstemmed Cost effective Expa-Max-Min scientific workflow allocation and load balancing strategy in cloud computing
title_sort cost effective expa-max-min scientific workflow allocation and load balancing strategy in cloud computing
publisher Science Publications
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/72134/1/Cost%20effective%20Expa-Max-Min%20scientific%20workflow%20allocation%20and%20load%20balancing%20strategy%20in%20cloud%20computing.pdf
http://psasir.upm.edu.my/id/eprint/72134/
https://thescipub.com/abstract/10.3844/jcssp.2018.623.638
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score 13.209306