Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm

Grid computing is the principle in utilizing and sharing large-scale resources of heterogeneous computing systems to solve the complex scientific problem. Such flexible resource request could offer the opportunity to optimize several parameters, such as coordinated resource sharing among dynamic col...

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Main Authors: Lorpunmanee, Siriluck, Sap, M.N.M, Abdullah, Abdul Hanan, Srinoy, Surat
Format: Article
Published: 2006
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Online Access:http://eprints.utm.my/7461/
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author Lorpunmanee, Siriluck
Sap, M.N.M
Abdullah, Abdul Hanan
Srinoy, Surat
author_facet Lorpunmanee, Siriluck
Sap, M.N.M
Abdullah, Abdul Hanan
Srinoy, Surat
author_sort Lorpunmanee, Siriluck
building UTM Library
collection Institutional Repository
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
continent Asia
country Malaysia
description Grid computing is the principle in utilizing and sharing large-scale resources of heterogeneous computing systems to solve the complex scientific problem. Such flexible resource request could offer the opportunity to optimize several parameters, such as coordinated resource sharing among dynamic collections of individuals, institutions, and resources. However, the major opportunity is in optimal job scheduling, which Grid nodes need to allocate the resources for each job. This paper proposes and evaluates a new method for job scheduling in heterogeneous computing Systems. Its objectives are to minimize the average waiting time and make-span time. The minimization is proposed by using a multiple objective genetic algorithm (GA), because the job scheduling problem is NP-hard problem. Our model presents the strategies of allocating jobs to different nodes. In this preliminary tests we show how the solution founded may minimize the average waiting time and the make-span time in Grid environment. The benefits of the usage of multiple objective genetic algorithm is improving the performance of the scheduling is discussed. The simulation has been obtained using historical information to study the job scheduling in Grid environment. The experimental results have shown that the scheduling system using the multiple objective genetic algorithms can allocate jobs efficiently and effectively.
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spelling my.utm.eprints-74612009-01-05T07:28:00Z http://eprints.utm.my/7461/ Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm Lorpunmanee, Siriluck Sap, M.N.M Abdullah, Abdul Hanan Srinoy, Surat QA75 Electronic computers. Computer science Grid computing is the principle in utilizing and sharing large-scale resources of heterogeneous computing systems to solve the complex scientific problem. Such flexible resource request could offer the opportunity to optimize several parameters, such as coordinated resource sharing among dynamic collections of individuals, institutions, and resources. However, the major opportunity is in optimal job scheduling, which Grid nodes need to allocate the resources for each job. This paper proposes and evaluates a new method for job scheduling in heterogeneous computing Systems. Its objectives are to minimize the average waiting time and make-span time. The minimization is proposed by using a multiple objective genetic algorithm (GA), because the job scheduling problem is NP-hard problem. Our model presents the strategies of allocating jobs to different nodes. In this preliminary tests we show how the solution founded may minimize the average waiting time and the make-span time in Grid environment. The benefits of the usage of multiple objective genetic algorithm is improving the performance of the scheduling is discussed. The simulation has been obtained using historical information to study the job scheduling in Grid environment. The experimental results have shown that the scheduling system using the multiple objective genetic algorithms can allocate jobs efficiently and effectively. 2006-03 Article PeerReviewed Lorpunmanee, Siriluck and Sap, M.N.M and Abdullah, Abdul Hanan and Srinoy, Surat (2006) Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm. WSEAS Transaction on Computer, 5 (3). pp. 484-491.
spellingShingle QA75 Electronic computers. Computer science
Lorpunmanee, Siriluck
Sap, M.N.M
Abdullah, Abdul Hanan
Srinoy, Surat
Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm
title Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm
title_full Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm
title_fullStr Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm
title_full_unstemmed Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm
title_short Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm
title_sort meta-scheduler in grid environment with multiple objectives by using genetic algorithm
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/7461/
url_provider http://eprints.utm.my/