Multi objective bee colony optimization framework for grid job scheduling

Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid compu...

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Main Authors: Alyaseri, Sana, Ku-Mahamud, Ku Ruhana
Format: Conference or Workshop Item
Language:English
Published: 2013
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Online Access:http://repo.uum.edu.my/11970/1/PID89.pdf
http://repo.uum.edu.my/11970/
http://www.icoci.cms.net.my/proceedings/2013/TOC.html
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spelling my.uum.repo.119702015-04-08T02:14:40Z http://repo.uum.edu.my/11970/ Multi objective bee colony optimization framework for grid job scheduling Alyaseri, Sana Ku-Mahamud, Ku Ruhana QA76 Computer software Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources. 2013-08-28 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/11970/1/PID89.pdf Alyaseri, Sana and Ku-Mahamud, Ku Ruhana (2013) Multi objective bee colony optimization framework for grid job scheduling. In: 4th International Conference on Computing and Informatics (ICOCI 2013), 28 -30 August 2013, Kuching, Sarawak, Malaysia. http://www.icoci.cms.net.my/proceedings/2013/TOC.html
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Alyaseri, Sana
Ku-Mahamud, Ku Ruhana
Multi objective bee colony optimization framework for grid job scheduling
description Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.
format Conference or Workshop Item
author Alyaseri, Sana
Ku-Mahamud, Ku Ruhana
author_facet Alyaseri, Sana
Ku-Mahamud, Ku Ruhana
author_sort Alyaseri, Sana
title Multi objective bee colony optimization framework for grid job scheduling
title_short Multi objective bee colony optimization framework for grid job scheduling
title_full Multi objective bee colony optimization framework for grid job scheduling
title_fullStr Multi objective bee colony optimization framework for grid job scheduling
title_full_unstemmed Multi objective bee colony optimization framework for grid job scheduling
title_sort multi objective bee colony optimization framework for grid job scheduling
publishDate 2013
url http://repo.uum.edu.my/11970/1/PID89.pdf
http://repo.uum.edu.my/11970/
http://www.icoci.cms.net.my/proceedings/2013/TOC.html
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score 13.1944895