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Optimization Approach for Resource Allocation on Cloud Computing for IoT

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dc.contributor.authorChoi, Yeongho-
dc.contributor.authorLim, Yujin-
dc.date.available2021-02-22T11:27:58Z-
dc.date.issued2016-03-
dc.identifier.issn1550-1329-
dc.identifier.issn1550-1477-
dc.identifier.urihttps://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/9893-
dc.description.abstractCombinatorial auction is a popular approach for resource allocation in cloud computing. One of the challenges in resource allocation is that QoS (Quality of Service) constraints are satisfied and provider's profit is maximized. In order to increase the profit, the penalty cost for SLA (Service Level Agreement) violations needs to be reduced. We consider execution time constraint as SLA constraint in combinatorial auction system. In the system, we determine winners at each bidding round according to the job's urgency based on execution time deadline, in order to efficiently allocate resources and reduce the penalty cost. To analyze the performance of our mechanism, we compare the provider's profit and success rate of job completion with conventional mechanism using real workload data.-
dc.language영어-
dc.language.isoENG-
dc.publisherHindawi Publishing Corporation-
dc.titleOptimization Approach for Resource Allocation on Cloud Computing for IoT-
dc.typeArticle-
dc.publisher.location이집트-
dc.identifier.doi10.1155/2016/3479247-
dc.identifier.scopusid2-s2.0-84962113294-
dc.identifier.wosid000372234600001-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS-
dc.citation.titleINTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.identifier.urlhttps://journals.sagepub.com/doi/10.1155/2016/3479247#-
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