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

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dc.contributor.authorSiriluck Lorpunmanee
dc.contributor.authorMohd Noor Md Sap
dc.contributor.authorAbdul Hanan Abdullah
dc.contributor.authorSurat Srinoy
dc.contributor.correspondenceS. Lorpunmanee; Faculty of Science and Technology, Suan Dusit Rajabhat University, Dusit, Bangkok, 295 Rajasrima Rd., Malaysia; email: siriluck_lor@dusit.ac.th
dc.date.accessioned2025-03-10T07:38:08Z
dc.date.available2025-03-10T07:38:08Z
dc.date.issued2006
dc.description.abstractGrid 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.
dc.identifier.citationWSEAS Transactions on Computers
dc.identifier.issn11092750
dc.identifier.scopus2-s2.0-33645146212
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/5071
dc.languageEnglish
dc.rights.holderScopus
dc.subjectAverage waiting time
dc.subjectGenetic algorithm
dc.subjectGrid computing
dc.subjectJob scheduling
dc.subjectMake-span time
dc.subjectNP-hard problem
dc.subjectOptimal job scheduling
dc.titleMeta-scheduler in Grid environment with multiple objectives by using genetic algorithm
dc.typeArticle
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-33645146212&partnerID=40&md5=99932d1d286ee13a37c02d89ddb55311
oaire.citation.endPage491
oaire.citation.issue3
oaire.citation.startPage484
oaire.citation.volume5
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