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Design of Energy Efficient WSN Using a Noble SMOWA Algorithm
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作者 Avishek Banerjee Deepak Garg +4 位作者 Victor Das Laxminarayan Sahoo Ira Nath Vijayakumar Varadarajan Ketan Kotecha 《Computers, Materials & Continua》 SCIE EI 2022年第8期3585-3600,共16页
In this paper,the establishment of efficientWireless Sensor Network(WSN)networks has been projected to minimize the consumption of energy using a new Self-adaptive Multi-Objective Weighted Approach(SMOWA)algorithm for... In this paper,the establishment of efficientWireless Sensor Network(WSN)networks has been projected to minimize the consumption of energy using a new Self-adaptive Multi-Objective Weighted Approach(SMOWA)algorithm for solving a multi-objective problem.The Different WSN nodes deployment policies have been proposed and applied in this paper to design an efficientWireless Sensor Network to minimize energy consumption.After that,the cluster head for each cluster has been selected with the help of the duty cycle.After configuring the WSN networks,the SMOWA algorithms have been developed to obtain the minimum energy consumption for the networks.Energy minimization,as well as the amount of day-saving,has been calculated for the differentWSNswhich has been configured through different deployment policies.The major finding of the research paper is to improve the durability of Wireless Sensor Network(i)applying different deployment strategies:(Random,S pattern and nautilus shell pattern),and(ii)using a new Meta-heuristic algorithm(SMOWA Algorithm).In this research,the lifetime of WSN has been increased to a significant level.To choose the best result set from all the obtained results set some constraints such as“equivalent distribution”,“number of repetitions”,“maximum amount energy storage by a node”has been set to an allowable range. 展开更多
关键词 Wireless Sensor Network(WSN) Self-adaptive Multi-Objective Weighted Approach(SMOWA) deployment strategies meta-heuristicmethods energy minimization duty cycle
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