Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/381742
Title: Performance Analysis Of Energy Efficient Infrastructure Less Networks
Researcher: Kumar Arun
Guide(s): Singh R K, Vijay Sandip
Keywords: Engineering
Engineering and Technology
Engineering Electrical and Electronic
University: Uttarakhand Technical University
Completed Date: 2021
Abstract: The scope of the thesis would include evaluating a mobile ad hoc grids energy usage by examining overhead routing, road set up and road maintenance problems. The suggested scheme monitors a nodes transmitting capacity by the distance between the nodes. The project will also provide energy details on the path request packet and pick the energy efficient route for route data packets. Then an algorithm is programmed and a protocol is built to simulate an energy efficient network without infrastructures. Finally, evaluate the collected data. The current analysis evaluates the energy consumption behavior of A mobile ad hoc network by evaluating overhead routing, path setup time and road maintenance problems. The suggested scheme monitors a nodes transmitting capacity by the distance between the nodes. The project also aims to evaluate the efficiency of energy efficient infrastructure less networks and then create an algorithm and a protocol to then model an energy efficient infrastructure less network and analysis the results obtained. Methodology for the proposed technique is a hybrid model consisting of two phases; Phase 1, for optimized selection of Cluster Head using Grey wolf Optimization Algorithm along with Tabu Search mechanism. Phase 2, in which, cluster size for routing is optimized using Grasshopper Optimization Algorithm. The proposed approach works in order to get the optimized value of energy on the basis of various quality of service parameters such as delay, throughput and Packet loss. In our research, we have proposed a hybrid model which in its initial phase optimizes the cluster head selection using a nature inspired algorithm called GWO along with a metaheuristic search approach called Tabu Search and in the second phase, we are also optimizing the cluster size according to the sink using Grasshopper Optimization algorithm. The optimization process in addition to achieve energy efficiency also focuses to retain the quality of service of the network. newline
Pagination: 147 pages
URI: http://hdl.handle.net/10603/381742
Appears in Departments:Department of Electronics and Communication Engineering

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01-title page.pdfAttached File66.25 kBAdobe PDFView/Open
02-certificate page.pdf469.16 kBAdobe PDFView/Open
03-contents.pdf23.96 kBAdobe PDFView/Open
04-list of tables.pdf72.32 kBAdobe PDFView/Open
05-list of figures.pdf21.1 kBAdobe PDFView/Open
06-acknowlegdement.pdf81.4 kBAdobe PDFView/Open
07-abstract.pdf70.04 kBAdobe PDFView/Open
08 �chapter 1.pdf298.96 kBAdobe PDFView/Open
09 �chapter 2.pdf246.25 kBAdobe PDFView/Open
10 �chapter 3.pdf551.36 kBAdobe PDFView/Open
11 �chapter 4.pdf246.03 kBAdobe PDFView/Open
12 �chapter 5.pdf515.73 kBAdobe PDFView/Open
13 �chapter 6.pdf57.97 kBAdobe PDFView/Open
14-refrences.pdf188.93 kBAdobe PDFView/Open
15-publication.pdf102.5 kBAdobe PDFView/Open
80_recommendation.pdf294.19 kBAdobe PDFView/Open
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