Emerging Workload Power Analysis Using Multi Level Threshold Partitioning in Cloud Environment

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dc.contributor.guideKavitha, K
dc.coverage.spatialComputer Science
dc.creator.researcherChinna, J
dc.date.accessioned2023-12-26T06:03:34Z
dc.date.available2023-12-26T06:03:34Z
dc.date.awarded2023
dc.date.completed2023
dc.date.registered2018
dc.description.noteBibliography p.155-168
dc.format.accompanyingmaterialDVD
dc.format.dimensionsA4
dc.format.extent154p.
dc.identifier.urihttp://hdl.handle.net/10603/533049
dc.languageEnglish
dc.publisher.institutionDepartment of Computer Science
dc.publisher.placeKodaikanal
dc.publisher.universityMother Teresa Womens University
dc.relation114 Nos.
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordEngineering and Technology
dc.titleEmerging Workload Power Analysis Using Multi Level Threshold Partitioning in Cloud Environment
dc.title.alternative-
dc.type.degreePh.D.

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