Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/497431
Title: Novel Techniques for QoS Based Resource Allocation in Cloud Computing
Researcher: PRASAD DEVARASETTY
Guide(s): M. JAMES STEPHEN
Keywords: Computer Science
Computer Science Information Systems
Engineering and Technology
University: Andhra University
Completed Date: 2022
Abstract: quotABSTRACT newlineCloud Computing provides services based on the pay-as-you-use policy. It is obvious that newlineincreased utilization of services leads to the utilization of more number of data centres. newlineTherefore, data centres demand high energy consumption for computing the tasks. On the other side newlinethe applications have to be deployed on to the servers without compromising the Quality of Service newline(QoS) requirements. Hence Resource management activities like using of virtualization technology , newline selection of the appropriate resources , scheduling the resources are crucial factors for an newlineefficient cloud computing environment. This thesis proposes solutions for three issues, the first newlineis the Virtual Machine Placement using the Multi-objective Ant Colony Optimization algorithm for newlineminimizing the resource wastage, energy consumption and communication cost within the data centre. newlineA novel solution for this multi-objective problem had been derived. newlinequot newline newline
Pagination: 202 pg
URI: http://hdl.handle.net/10603/497431
Appears in Departments:Department of Computer Science & Systems Engineering

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01_title.pdfAttached File128.16 kBAdobe PDFView/Open
02_prelim pages.pdf260.7 kBAdobe PDFView/Open
03_content.pdf75.11 kBAdobe PDFView/Open
04_abstract.pdf73.04 kBAdobe PDFView/Open
05_chapter 1.pdf202.57 kBAdobe PDFView/Open
06_chapter 2.pdf201.87 kBAdobe PDFView/Open
07_chapter 3.pdf168.98 kBAdobe PDFView/Open
08_chapter 4.pdf239.31 kBAdobe PDFView/Open
09_chapter 5.pdf192.16 kBAdobe PDFView/Open
10_chapter 6.pdf425.46 kBAdobe PDFView/Open
11_annexures.pdf2.37 MBAdobe PDFView/Open
80_recommendation.pdf494.3 kBAdobe PDFView/Open
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