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Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm

In cloud computing, resources are dynamically provisioned and delivered to users in a transparent manner automatically on-demand. Task execution failure is no longer accidental but a common characteristic of cloud computing environment. In recent times, a number of intelligent scheduling techniques...

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Main Authors: Abdulhamid, Shafi’i Muhammad, Abd Latiff, Muhammad Shafie, Madni, Syed Hamid Hussain, Abdullahi, Mohammed
Format: Article
Published: Springer-Verlag London Ltd 2016
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/72818/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978911323&doi=10.1007%2fs00521-016-2448-8&partnerID=40&md5=2c82f7ec11d9a34a2e349af8f78e747c
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spelling my.utm.728182017-11-20T08:14:57Z http://eprints.utm.my/id/eprint/72818/ Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm Abdulhamid, Shafi’i Muhammad Abd Latiff, Muhammad Shafie Madni, Syed Hamid Hussain Abdullahi, Mohammed QA75 Electronic computers. Computer science In cloud computing, resources are dynamically provisioned and delivered to users in a transparent manner automatically on-demand. Task execution failure is no longer accidental but a common characteristic of cloud computing environment. In recent times, a number of intelligent scheduling techniques have been used to address task scheduling issues in cloud without much attention to fault tolerance. In this research article, we proposed a dynamic clustering league championship algorithm (DCLCA) scheduling technique for fault tolerance awareness to address cloud task execution which would reflect on the current available resources and reduce the untimely failure of autonomous tasks. Experimental results show that our proposed technique produces remarkable fault reduction in task failure as measured in terms of failure rate. It also shows that the DCLCA outperformed the MTCT, MAXMIN, ant colony optimization and genetic algorithm-based NSGA-II by producing lower makespan with improvement of 57.8, 53.6, 24.3 and 13.4 % in the first scenario and 60.0, 38.9, 31.5 and 31.2 % in the second scenario, respectively. Considering the experimental results, DCLCA provides better quality fault tolerance aware scheduling that will help to improve the overall performance of the cloud environment. Springer-Verlag London Ltd 2016 Article PeerReviewed Abdulhamid, Shafi’i Muhammad and Abd Latiff, Muhammad Shafie and Madni, Syed Hamid Hussain and Abdullahi, Mohammed (2016) Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm. Neural Computing and Applications . pp. 1-15. ISSN 0941-0643 (In Press) https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978911323&doi=10.1007%2fs00521-016-2448-8&partnerID=40&md5=2c82f7ec11d9a34a2e349af8f78e747c
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 QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Abdulhamid, Shafi’i Muhammad
Abd Latiff, Muhammad Shafie
Madni, Syed Hamid Hussain
Abdullahi, Mohammed
Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm
description In cloud computing, resources are dynamically provisioned and delivered to users in a transparent manner automatically on-demand. Task execution failure is no longer accidental but a common characteristic of cloud computing environment. In recent times, a number of intelligent scheduling techniques have been used to address task scheduling issues in cloud without much attention to fault tolerance. In this research article, we proposed a dynamic clustering league championship algorithm (DCLCA) scheduling technique for fault tolerance awareness to address cloud task execution which would reflect on the current available resources and reduce the untimely failure of autonomous tasks. Experimental results show that our proposed technique produces remarkable fault reduction in task failure as measured in terms of failure rate. It also shows that the DCLCA outperformed the MTCT, MAXMIN, ant colony optimization and genetic algorithm-based NSGA-II by producing lower makespan with improvement of 57.8, 53.6, 24.3 and 13.4 % in the first scenario and 60.0, 38.9, 31.5 and 31.2 % in the second scenario, respectively. Considering the experimental results, DCLCA provides better quality fault tolerance aware scheduling that will help to improve the overall performance of the cloud environment.
format Article
author Abdulhamid, Shafi’i Muhammad
Abd Latiff, Muhammad Shafie
Madni, Syed Hamid Hussain
Abdullahi, Mohammed
author_facet Abdulhamid, Shafi’i Muhammad
Abd Latiff, Muhammad Shafie
Madni, Syed Hamid Hussain
Abdullahi, Mohammed
author_sort Abdulhamid, Shafi’i Muhammad
title Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm
title_short Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm
title_full Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm
title_fullStr Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm
title_full_unstemmed Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm
title_sort fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm
publisher Springer-Verlag London Ltd
publishDate 2016
url http://eprints.utm.my/id/eprint/72818/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978911323&doi=10.1007%2fs00521-016-2448-8&partnerID=40&md5=2c82f7ec11d9a34a2e349af8f78e747c
_version_ 1643656519736098816
score 13.211869

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