Chandan Bikash Das

Work place: Department of Mathematics, Tamralipta Mahavidyalaya, Tamluk, Purba Midnapore

E-mail: cdasmathematics@gmail.com

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Biography

Dr. Chandan Bikash Das has a good research experience as he is involved in research for past 15 years. He is an Associate Professor in Department of Mathematics, Tamralipta Mahavidyalaya,Tamluk, Purba Midnapur, West Bengal, India. He has published many research articles in the International & National Conferences and Journals. His research interests are: Fuzzy System, Game Theory, Genetic Algorithm and other related topics.

Author Articles
Fuzzy-based Bi-objective Energy Efficient Routing Protocol for Large Scale Mobile Ad-hoc Network

By Subhrananda Goswami Sukumar Mondal Subhankar Joardar Sovan Samanta Chandan Bikash Das

DOI: https://doi.org/10.5815/ijisa.2024.06.06, Pub. Date: 8 Dec. 2024

MANET is an infrastructure-less network, which is comprised of a greater number of nodes that are moving in a random manner. Establishing efficient and reliable routes is the crucial design issue in MANET. In addition, providing energy-efficient routes for performing communication operations in MANET is also a challenging goal. Increasing network lifetime and decreasing overall traffic load are the significant considerations while designing the MANET. An energy optimization routing mechanism with a fuzzy basis that is state-based and influenced by COVID-19 is used to prevent and control epidemics. Based on their lifespan and varying mobility speeds, it is dependent on energy optimization yield under various scenarios. Fuzzy-based bi-objective criteria in energy-efficient routing protocol for the mobile ad-hoc network to select the different constraints like link stability, bandwidth, and battery life. The main goal of this paper is to obtain the optimal solution to choose the best route, limit battery life, and change the movement of mobile nodes for large-scale mobile ad-hoc networks. It is demonstrated that the possible solution relates to the domain of selecting the variables by outlining the connection between the energy function’s variables. Researchers optimize a path's link lifespan, resulting in the choice of the shortest path being particularly efficient in COVID-19 pandemic prevention and treatment. 

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