Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/331493
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dc.coverage.spatialCertain investigations on energy efficient scheduling for cloud data center using heuristic based migration
dc.date.accessioned2021-07-12T10:14:57Z-
dc.date.available2021-07-12T10:14:57Z-
dc.identifier.urihttp://hdl.handle.net/10603/331493-
dc.description.abstractCloud Computing nowadays has become an exceptionally fast spread in research, industry and the various fields of computing. In the means of virtualization a part of services that they offered some new possibilities for building application and they providing certain services to the end user. This technology it also provides infrastructure, application, software in a platform that sharing of resources. In the present world, the energy efficient is a universal challenges and virtualization will make available approach for re-dividing the software and hardware further than physical servers in their various applications. Because even while they having different resources it will helps able to run a similar server. At present in cloud data centres it had a tendency to be a mounting threat to the environment in need of huge energy consumption. Here the major problem was energy efficient using in huge data centres. The actual essential of this cloud computing environment will have a cloud data centres that s consists of huge configured hardware facilities. In the cloud service providers that s computing ability of the data canters will be the main indicator. In this thesis, The heuristic algorithms are the main dependent on the problem and they finding the solution by apply this problem sorts in a complete way. Their solution is based on learning and exploration in which a comprehensive and scientific search for finding an optimal response and speeding to response process is applied. To finding an optimal response and quick to response process by applying this based on learning and exploration by in which scientific search and comprehensive their solutions. newline
dc.format.extentxvii, 141p.
dc.languageEnglish
dc.relationp.128-140
dc.rightsuniversity
dc.titleCertain investigations on energy efficient scheduling for cloud data center using heuristic based migration
dc.title.alternative
dc.creator.researcherGanesh kumar G
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordheuristic
dc.subject.keywordcloud data
dc.description.note
dc.contributor.guideVivekanandan P
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2020
dc.date.awarded2020
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 File26.93 kBAdobe PDFView/Open
02_certificates.pdf372.83 kBAdobe PDFView/Open
03_vivaproceedings.pdf730.45 kBAdobe PDFView/Open
04_bonafidecertificate.pdf447.23 kBAdobe PDFView/Open
05_abstracts.pdf131.9 kBAdobe PDFView/Open
06_acknowledgements.pdf433.42 kBAdobe PDFView/Open
07_contents.pdf337.77 kBAdobe PDFView/Open
08_listoftables.pdf22.21 kBAdobe PDFView/Open
09_listoffigures.pdf29.79 kBAdobe PDFView/Open
10_listofabbreviations.pdf33.03 kBAdobe PDFView/Open
11_chapter1.pdf284.34 kBAdobe PDFView/Open
12_chapter2.pdf359.46 kBAdobe PDFView/Open
13_chapter3.pdf258.74 kBAdobe PDFView/Open
14_chapter4.pdf422.19 kBAdobe PDFView/Open
15_chapter5.pdf382.57 kBAdobe PDFView/Open
16_chapter6.pdf104.08 kBAdobe PDFView/Open
17_conclusion.pdf135.32 kBAdobe PDFView/Open
18_references.pdf320.6 kBAdobe PDFView/Open
19_listofpublications.pdf129.39 kBAdobe PDFView/Open
80_recommendation.pdf67.18 kBAdobe PDFView/Open


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