1. Shodhganga@INFLIBNET
  2. Banaras Hindu University
  3. Department of Computer Science
Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/350199
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dc.coverage.spatial
dc.date.accessioned2021-12-03T07:16:48Z-
dc.date.available2021-12-03T07:16:48Z-
dc.identifier.urihttp://hdl.handle.net/10603/350199-
dc.description.abstractThe thesis is focused on Machine Learning Techniques to Enhance the Performance of Cloud Based Applications to solve the problems occurring in Cloud-based web services recommendation and Efficient Resource Utilization and Allocation. newlineThe First Chapter deals with the introduction of web services and their QoS parameters. Based on the web services and its QoS parameters how its assessments and recommendation is being carried out has been discussed in the later part of the chapter. Later in the chapter, we have described the use of statistical machine learning and cloud simulator in carrying out the experiments newline
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleMachine Learning Techniques To Enhance The Performance Of Cloud Based Applications
dc.title.alternative
dc.creator.researcherKumar, Sunil
dc.subject.keywordComputer programming
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Artificial Intelligence
dc.subject.keywordEngineering and Technology
dc.subject.keywordMachine-tools--Numerical control--Programming
dc.subject.keywordSoftware compatibility
dc.subject.keywordSystems programming (Computer science)
dc.description.note
dc.contributor.guideKarthikeyan, S And Singh, M. K
dc.publisher.placeVaranasi
dc.publisher.universityBanaras Hindu University
dc.publisher.institutionDepartment of Computer Science
dc.date.registered2011
dc.date.completed2019
dc.date.awarded
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science

Files in This Item:
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01_title.pdfAttached File148.63 kBAdobe PDFView/Open
02_certificate.pdf214.28 kBAdobe PDFView/Open
03_content.pdf68.22 kBAdobe PDFView/Open
04_abstract.pdf131.56 kBAdobe PDFView/Open
05_acknowledgement.pdf91.04 kBAdobe PDFView/Open
06_abbreviations.pdf93.23 kBAdobe PDFView/Open
07_list of tables.pdf114.18 kBAdobe PDFView/Open
08_list of figures.pdf109.6 kBAdobe PDFView/Open
09_preface.pdf139.39 kBAdobe PDFView/Open
10_glossary.pdf101.46 kBAdobe PDFView/Open
11_chapter1.pdf400.49 kBAdobe PDFView/Open
12_chapter2.pdf144.3 kBAdobe PDFView/Open
13_chapter3.pdf612.61 kBAdobe PDFView/Open
14_chapter4.pdf529.88 kBAdobe PDFView/Open
15_chapter5.pdf461.72 kBAdobe PDFView/Open
16_chapter6.pdf171.83 kBAdobe PDFView/Open
17_bibliography.pdf300.38 kBAdobe PDFView/Open
18_appendices.pdf1.09 MBAdobe PDFView/Open
80_recommendation.pdf320.57 kBAdobe PDFView/Open
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