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Design of Energy Efficient WSN Using a Noble SMOWA Algorithm

Computers, Materials & Continua 2022年第8期72卷 3585-3600页

作者： Avishek Banerjee Deepak Garg Victor Das Laxminarayan Sahoo Ira Nath Vijayakumar Varadarajan Ketan Kotecha Department of Computer Science and Engineering Bennett UniversityGreater Noida201310India Department of Information Technology Asansol Engineering CollegeAsansol713305India Department of Computer and Information Science Raiganj UniversityRaiganj733134India Department of Computer Science and Engineering JIS College of EngineeringKalyani741235India School of Computer Science and Engineering University of New South WalesSydneyAustralia Symbiosis Centre for Applied Artificial Intelligence Symbiosis International(Deemed University)PuneIndia

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 *** Different WSN nodes deployment policies have been proposed and applied in this paper to design an efficientWireless Sensor Network to minimize energy *** that,the cluster head for each cluster has been selected with the help of the duty *** configuring the WSN networks,the SMOWA algorithms have been developed to obtain the minimum energy consumption for the *** minimization,as well as the amount of day-saving,has been calculated for the differentWSNswhich has been configured through different deployment *** 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 *** 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.

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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