文献类型：期刊文献

英文题名：WSN Coverage Optimization Based onTwo-Stage PSO

作者：Qi, Wei[1]; Yu, Huiqun[1,2]; Fan, Guisheng[1]; Chen, Liang[1]; Wen, Xinxiu[1]

机构：[1] Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, China; [2] Shanghai Key Laboratory of Computer Software Evaluating and Testing, Shanghai, China

年份：2021

卷号：349

起止页码：19

外文期刊名：Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

收录：EI(收录号：20210909984665)

语种：英文

外文关键词：Internet of things - Energy utilization - Sensor nodes - Embedded systems - Particle swarm optimization (PSO)

摘要：Wireless Sensor Networks (WSN) coverage perception is an important basis for communication between the cyber world and the physical world in Cyber-Physical Systems (CPS). To address the coverage redundancy, hole caused by initial random deployment and the energy constraint in redeployment, this paper proposes a multi-objective two-stage particle swarm optimization algorithm (MTPSO) based on coverage rate and moving distance deviation to improve coverage efficiency. This algorithm establishes a multi-objective optimization model for above problems, and determines the candidate deployment scheme by reducing its local convergence probability through improved inertia weight, and then introduces virtual force mechanism to adjust the relative position between nodes. This paper mainly analyzes the influence of different initial deployment category and mobile nodes proportion on multi-objective optimization performance, and gives the corresponding algorithm implement. Simulation experiments show that compared with MVFA, SPSO and OPSO algorithms, MTPSO algorithm has a better redeployment coverage performance, which fully demonstrates its effectiveness. ? 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.