Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/599101
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dc.coverage.spatial
dc.date.accessioned2024-11-04T06:43:19Z-
dc.date.available2024-11-04T06:43:19Z-
dc.identifier.urihttp://hdl.handle.net/10603/599101-
dc.description.abstractAvailable newline
dc.format.extentxix, 125p.
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleAI Driven Strategies for Edge Server Deployment in 5G Networks
dc.title.alternative
dc.creator.researcherTiwari, V.
dc.subject.keywordComputer Science
dc.subject.keywordEdge Server Placement (ESP); Evolutionary Computation; Mobile edge computing (MEC); 5G; Energy Consumption; Load balancing; Fault-Tolerance; Base Station Allocation; Heterogeneous capacities; Homogeneous capacities; Cellular Traffic Forecasting; Performance Evaluation.
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideRoy, D. S. and Singh, A. P.
dc.publisher.placeShillong
dc.publisher.universityNational Institute of Technology (NIT) Meghalaya
dc.publisher.institutionComputer Science And Engineering
dc.date.registered2018
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Computer Science And Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File292.62 kBAdobe PDFView/Open
02_prelim pages.pdf584.89 kBAdobe PDFView/Open
03_contents.pdf106.58 kBAdobe PDFView/Open
04_abstract.pdf127.42 kBAdobe PDFView/Open
05_chapter 1.pdf697.41 kBAdobe PDFView/Open
06_chapter 2.pdf194.04 kBAdobe PDFView/Open
07_chapter 3.pdf6.02 MBAdobe PDFView/Open
08_chapter 4.pdf3.7 MBAdobe PDFView/Open
09_chapter 5.pdf8.94 MBAdobe PDFView/Open
10_chapter 6.pdf4.17 MBAdobe PDFView/Open
11_chapter 7.pdf169.59 kBAdobe PDFView/Open
12_annexures.pdf190.19 kBAdobe PDFView/Open
80_recommendation.pdf609.6 kBAdobe PDFView/Open


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