Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/34201
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dc.coverage.spatialStudies on energy efficient techniques for cloud data centersen_US
dc.date.accessioned2015-02-10T07:31:44Z-
dc.date.available2015-02-10T07:31:44Z-
dc.date.issued2015-02-10-
dc.identifier.urihttp://hdl.handle.net/10603/34201-
dc.description.abstractnewlineThe objective of the research is to draw from existing approaches and techniques new insights that can assist the problem of power and performance trade off that exists in cloud data centers These insights would enable us to design our novel self adapting mechanism to solve the trade off We design a framework for the cloud environment and handle workload of virtualized servers and analyse the energy perspective A study was carried out on the available literature on data centers and the energy perspective for them That is the self managing mechanism should cater for the wide variation in reliability attributes and associated constraints for a large number of applications that are composed of services offered by a cloud environment Problem of dynamic virtualized instances selection have limitations when they need to scale to the case of the cloud Results of the literature review identified the axes that self adaptive VM consolidation need to be considered thus achieving better energy efficiency newlineThis thesis views the IaaS in the cloud based services and we propose a novel self adaptive energy efficient mechanisms to solve the trade off A Multi Informative VM Analysis MIVA was proposed to analyze the virtualized cloud component complexity newlineen_US
dc.format.extentxix, 169p.en_US
dc.languageEnglishen_US
dc.relationp162-168.en_US
dc.rightsuniversityen_US
dc.titleStudies on energy efficient techniques for cloud data centersen_US
dc.title.alternativeen_US
dc.creator.researcherAnandharajan T R Ven_US
dc.subject.keywordEnergy Curve Modelen_US
dc.subject.keywordEnergy per Instruction Rateen_US
dc.subject.keywordMinimum Processing Poweren_US
dc.subject.keywordMulti Informative VM Analysisen_US
dc.description.notereference p162-168.en_US
dc.contributor.guideBhagyaveni M Aen_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Information and Communication Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01/10/2014en_US
dc.date.awarded30/10/2014en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File32.2 kBAdobe PDFView/Open
02_certificate.pdf402.28 kBAdobe PDFView/Open
03_abstract.pdf12.48 kBAdobe PDFView/Open
04_acknowledgement.pdf6.77 kBAdobe PDFView/Open
05_content.pdf65.45 kBAdobe PDFView/Open
06_chapter1.pdf199.58 kBAdobe PDFView/Open
07_chapter2.pdf266.44 kBAdobe PDFView/Open
08_chapter3.pdf869.07 kBAdobe PDFView/Open
09_chapter4.pdf332.18 kBAdobe PDFView/Open
10_chapter5.pdf164.45 kBAdobe PDFView/Open
11_chapter6.pdf200.95 kBAdobe PDFView/Open
12_chapter7.pdf20.75 kBAdobe PDFView/Open
13_reference.pdf38.56 kBAdobe PDFView/Open
14_publication.pdf9.08 kBAdobe PDFView/Open


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