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Clustering hypervisors to minimize failures in mobile cloud computing

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dc.contributor.authorFekade, Berihun-
dc.contributor.authorMaksymyuk, Taras-
dc.contributor.authorJo, Minho-
dc.date.accessioned2021-09-03T15:35:45Z-
dc.date.available2021-09-03T15:35:45Z-
dc.date.created2021-06-16-
dc.date.issued2016-12-25-
dc.identifier.issn1530-8669-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/86498-
dc.description.abstractResource virtualization has become one of the key super-power mobile computing architecture technologies. As mobile devices and multimedia traffic have increased dramatically, the load on mobile cloud computing systems has become heavier. Under such conditions, mobile cloud system reliability becomes a challenging task. In this paper, we propose a new model using a naive Bayes classifier for hypervisor failure prediction and prevention in mobile cloud computing. We exploit real-time monitoring data in combination with historical maintenance data, which achieves higher accuracy in failure prediction and early failure-risk detection. After detecting hypervisors at risk, we perform live migration of virtual servers within a cluster, which decreases the load and prevents failures in the cloud. We performed a simulation for verification. According to the experimental results, our proposed model shows good accuracy in failure prediction and the possibility of decreasing downtime in a hypervisor service. Copyright (c) 2017 John Wiley & Sons, Ltd.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherWILEY-HINDAWI-
dc.titleClustering hypervisors to minimize failures in mobile cloud computing-
dc.typeArticle-
dc.contributor.affiliatedAuthorJo, Minho-
dc.identifier.doi10.1002/wcm.2770-
dc.identifier.scopusid2-s2.0-85013054737-
dc.identifier.wosid000395656600020-
dc.identifier.bibliographicCitationWIRELESS COMMUNICATIONS & MOBILE COMPUTING, v.16, no.18, pp.3455 - 3465-
dc.relation.isPartOfWIRELESS COMMUNICATIONS & MOBILE COMPUTING-
dc.citation.titleWIRELESS COMMUNICATIONS & MOBILE COMPUTING-
dc.citation.volume16-
dc.citation.number18-
dc.citation.startPage3455-
dc.citation.endPage3465-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.subject.keywordAuthormobile cloud computing-
dc.subject.keywordAuthorhypervisor clustering-
dc.subject.keywordAuthorhypervisor failure prediction-
dc.subject.keywordAuthorvirtual server-
dc.subject.keywordAuthorphysical server-
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