Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/339357
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dc.date.accessioned2021-09-07T03:55:29Z-
dc.date.available2021-09-07T03:55:29Z-
dc.identifier.urihttp://hdl.handle.net/10603/339357-
dc.description.abstractThe new data era has reached the heights of technical eminence. Including Cloud computing, Next-generation Networks (NGN), and the Internet of Things (IoT). The integration of cloud computing with IoT strives the new research doors for the universal network community. As the major players, iCloud, Dropbox, Face book and Amazon EMR have built up an outstanding escalation in recent years on the planet cloud showcase. Current, approaches use batch processing to monitor network traffic in their middlebox layers newline
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleEfficient Approaches for Improved Datacentre Network Throughput by Solving TCP Incast Problem Using Machine Learning Algorithms
dc.title.alternative
dc.creator.researcherThiruvenkatam B
dc.subject.keywordAutomation and Control Systems
dc.subject.keywordComputer Science
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideMukesh Krishnan M B
dc.publisher.placeKattankulathur
dc.publisher.universitySRM University
dc.publisher.institutionDepartment of Computer Science Engineering
dc.date.registered
dc.date.completed2021
dc.date.awarded
dc.format.dimensions
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science Engineering

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80_recommendation.pdfAttached File492.97 kBAdobe PDFView/Open
certificate page.pdf479.95 kBAdobe PDFView/Open
chapter 1.pdf1.03 MBAdobe PDFView/Open
chapter 2.pdf772.75 kBAdobe PDFView/Open
chapter 3.pdf1.51 MBAdobe PDFView/Open
chapter 4.pdf1.29 MBAdobe PDFView/Open
chapter 5.pdf352.43 kBAdobe PDFView/Open
list of publications.pdf352.02 kBAdobe PDFView/Open
preliminary page.pdf484.96 kBAdobe PDFView/Open
references.pdf490.38 kBAdobe PDFView/Open
title page.pdf150.91 kBAdobe PDFView/Open
vitae.pdf243.69 kBAdobe PDFView/Open


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