Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/424601
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dc.coverage.spatialLoad distribution approaches for energy efficiency in cloud data centers
dc.date.accessioned2022-12-12T07:10:57Z-
dc.date.available2022-12-12T07:10:57Z-
dc.identifier.urihttp://hdl.handle.net/10603/424601-
dc.description.abstractData centers are the backbone of cloud computing. These data newlinecenters significantly impact various sectors, such as business, education, newlinegovernment, information and communication systems, and social networking newlineactivities. Large-scale data centers perform the aforementioned activities. newlineSuch hyper-scale data centers use millions of kilowatts of electricity every newlineyear, causing huge energy consumption leading to increased energy cost and newlinecarbon footprint. To reduce the economic and environmental consequences, newlineenergy efficiency is one of the key factors for greening data centers, which newlinecomprises energy management, thermal management and environmental newlineawareness. newlineMotivated by the manifold approach for energy efficiency, this thesis newlinework considers energy aware, temperature aware and eco-aware load newlinedistribution approaches for efficient energy utilization. Generally, load newlinebalancing, scheduling and server consolidation are the mechanisms used for newlineimproving energy efficiency in the computing environment. Handling newlineworkload distribution is crucial to both mechanisms. This thesis work newlinepresents novel techniques, models and algorithms for efficient load newlinedistribution approaches to handle energy efficiency problems in cloud data newlinecenters. The aim is to optimize energy consumption in the context of green newlineaspects using efficient workload distribution and server consolidation newlineapproaches. newline
dc.format.extentxvi, 149p.
dc.languageEnglish
dc.relationp.138-148
dc.rightsuniversity
dc.titleLoad distribution approaches for energy efficiency in cloud data centers
dc.title.alternative
dc.creator.researcherThilagavathi, N
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordenergy efficiency
dc.subject.keywordcloud data
dc.description.note
dc.contributor.guideRhymend uthariaraj, V
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File518.17 kBAdobe PDFView/Open
02_prelim pages.pdf1.78 MBAdobe PDFView/Open
03_content.pdf217.95 kBAdobe PDFView/Open
04_abstract.pdf367.21 kBAdobe PDFView/Open
05_chapter 1.pdf2.89 MBAdobe PDFView/Open
06_chapter 2.pdf1.14 MBAdobe PDFView/Open
07_chapter 3.pdf894.41 kBAdobe PDFView/Open
08_chapter 4.pdf1.56 MBAdobe PDFView/Open
09_chapter 5.pdf963.86 kBAdobe PDFView/Open
10_chapter 6.pdf677.03 kBAdobe PDFView/Open
11_annexures.pdf4.83 MBAdobe PDFView/Open
80_recommendation.pdf2.11 MBAdobe PDFView/Open


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