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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| 主要な著者: | , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English |
| 出版事項: |
2013
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| 主題: | |
| オンライン･アクセス: | 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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| 要約: | 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. |
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