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2PTS: A Two-Phase Task Scheduling Algorithm for MapReduce

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dc.contributor.authorLim, Byungnam-
dc.contributor.authorShim, Yeeun-
dc.contributor.authorChung, Yon Dohn-
dc.date.accessioned2021-09-03T20:47:24Z-
dc.date.available2021-09-03T20:47:24Z-
dc.date.created2021-06-16-
dc.date.issued2016-09-
dc.identifier.issn1745-1361-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/87716-
dc.description.abstractFor an efficient processing of large data in a distributed system, Hadoop MapReduce performs task scheduling such that tasks are distributed with consideration of the data locality. The data locality, however, is limitedly exploited, since it is pursued one node at a time basis without considering the global optimality. In this paper, we propose a novel task scheduling algorithm that globally considers the data locality. Through experiments, we show our algorithm improves the performance of MapReduce in various situations.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherIEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG-
dc.title2PTS: A Two-Phase Task Scheduling Algorithm for MapReduce-
dc.typeArticle-
dc.contributor.affiliatedAuthorChung, Yon Dohn-
dc.identifier.doi10.1587/transinf.2016EDL8075-
dc.identifier.scopusid2-s2.0-84984916905-
dc.identifier.wosid000384920500019-
dc.identifier.bibliographicCitationIEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E99D, no.9, pp.2377 - 2380-
dc.relation.isPartOfIEICE TRANSACTIONS ON INFORMATION AND SYSTEMS-
dc.citation.titleIEICE TRANSACTIONS ON INFORMATION AND SYSTEMS-
dc.citation.volumeE99D-
dc.citation.number9-
dc.citation.startPage2377-
dc.citation.endPage2380-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.subject.keywordAuthorMapReduce-
dc.subject.keywordAuthortask scheduling algorithm-
dc.subject.keywordAuthordata locality-
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