Deployment method of wireless sensor networks based on MaOEA/P-GM algorithm

作     者：Wang, Jun Luo, Dongxu Chen, Weiru Peng, Funan Li, Zhiwu 

作者机构：College of Computer Science and Technology Shenyang University of Chemical Technology Shenyang110142 China Key Laboratory of Industrial Intelligence Technology on Chemical Process Shenyang University of Chemical Technology Shenyang110142 China College of System Engineering Institute Macao University of Science and Technology 00853 China 

出 版 物：《Soft Computing》 (Soft Comput.)

年 卷 期：2024年

页      面：1-10页

核心收录：

学科分类：0810[工学-信息与通信工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work was supported by the Science and Technology Activity Support Project for Candidates of \u201CTalents Project\u201D in Liaoning Province (Liaorenshe No. 45) The Natural Foundation of Liaoning Province (2022-MS-291) Project of Liaoning Provincial Department of Education (LJ2020024 and 2022) 

主　　题：Life cycle 

摘      要：At present, wireless sensor networks are developing rapidly, but they will also face many challenges. For example, in the deployment problem, many problems such as cost, coverage, connectivity, energy, network life cycle and so on need to be considered, while the traditional multi-objective algorithm does not perform well in dealing with many-objective problems. How to quickly find high-quality solutions is the focus of research today. This paper proposes a deployment method for wireless sensor networks based on MaOEA/P-GM algorithm. This method improves the mutation strategy of the algorithm according to the characteristics of wireless sensor network deployment based on the many-objective algorithm MaOEA/P. Experiments show that using this algorithm in a many-objective environment can quickly get a high-quality solution set with fewer nodes, high coverage, good connectivity, and balanced energy consumption. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.