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Dynamic resource management in energy constrained heterogeneous computing systems using voltage scaling

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dc.contributor.authorKim, Jong-Kook-
dc.contributor.authorSiegel, Howard Jay-
dc.contributor.authorMaciejewski, Anthony A.-
dc.contributor.authorEigenmann, Rudolf-
dc.date.accessioned2021-09-09T03:10:25Z-
dc.date.available2021-09-09T03:10:25Z-
dc.date.created2021-06-10-
dc.date.issued2008-11-
dc.identifier.issn1045-9219-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/122509-
dc.description.abstractAn ad hoc grid is a wireless heterogeneous computing environment without a fixed infrastructure. This study considers wireless devices that have different capabilities, have limited battery capacity, support dynamic voltage scaling, and are expected to be used for eight hours at a time and then recharged. To maximize the performance of the system, it is essential to assign resources to tasks (match) and order the execution of tasks on each resource (schedule) in a manner that exploits the heterogeneity of the resources and tasks while considering the energy constraints of the devices. In the single-hop ad hoc grid heterogeneous environment considered in this study, tasks arrive unpredictably, are independent (i.e., no precedent constraints for tasks) and have priorities and deadlines. The problem is to map (match and schedule) tasks onto devices such that the number of highest priority tasks completed by their deadlines during eight hours is maximized while efficiently utilizing the overall system energy. A model for dynamically mapping tasks onto wireless devices is introduced. Seven dynamic mapping heuristics for this environment are designed and compared to each other and to a mathematical bound.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherIEEE COMPUTER SOC-
dc.subjectINDEPENDENT TASKS-
dc.subjectALLOCATION-
dc.subjectHEURISTICS-
dc.subjectSUBTASKS-
dc.titleDynamic resource management in energy constrained heterogeneous computing systems using voltage scaling-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Jong-Kook-
dc.identifier.doi10.1109/TPDS.2008.113-
dc.identifier.scopusid2-s2.0-54249165363-
dc.identifier.wosid000259457200002-
dc.identifier.bibliographicCitationIEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, v.19, no.11, pp.1445 - 1457-
dc.relation.isPartOfIEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS-
dc.citation.titleIEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS-
dc.citation.volume19-
dc.citation.number11-
dc.citation.startPage1445-
dc.citation.endPage1457-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordPlusINDEPENDENT TASKS-
dc.subject.keywordPlusALLOCATION-
dc.subject.keywordPlusHEURISTICS-
dc.subject.keywordPlusSUBTASKS-
dc.subject.keywordAuthorad hoc-
dc.subject.keywordAuthordistributed heterogeneous computing-
dc.subject.keywordAuthordynamic resource allocation/management-
dc.subject.keywordAuthordynamic voltage scaling-
dc.subject.keywordAuthorenergy-aware computing-
dc.subject.keywordAuthortask priorities and deadlines-
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