Improved whale optimization algorithm and its application in heterogeneous wireless sensor networks

作     者：Yue, Yinggao You, Hairong Wang, Shuxin Cao, Li 

作者机构：Wenzhou Univ Oujiang Coll Wenzhou 325035 Zhejiang Peoples R China Hubei Univ Arts & Sci Comp Sch Xiangyang Peoples R China Northeastern Univ Sch Informat Sci & Engn Shenyang Peoples R China 

出 版 物：《INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS》 (分布式传感网络国际杂志)

年 卷 期：2021年第17卷第5期

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Natural Science Foundation of Hubei Province [2020CFB304] Talent Introduction Project of Oujiang College of Wenzhou University Science and Technology Program of Sichuan, China [2020YFH0124] Guangdong Natural Science Foundation of China Zigong Key Science and Technology Project of China [2020YGJC01] Huzhou Science and Technology Plan Project [2020GG33] 

主　　题：Heterogeneous wireless sensor networks whale optimization algorithm coverage optimization sine and cosine algorithm energy balance 

摘      要：Aiming at the problems of node redundancy and network cost increase in heterogeneous wireless sensor networks, this article proposes an improved whale optimization algorithm coverage optimization method. First, establish a mathematical model that balances node utilization, coverage, and energy consumption. Second, use the sine-cosine algorithm to improve the whale optimization algorithm and change the convergence factor of the original algorithm. The linear decrease is changed to the nonlinear decrease of the cosine form, which balances the global search and local search capabilities, and adds the inertial weight of the synchronous cosine form to improve the optimization accuracy and speed up the search speed. The improved whale optimization algorithm solves the heterogeneous wireless sensor network coverage optimization model and obtains the optimal coverage scheme. Simulation experiments show that the proposed method can effectively improve the network coverage effect, as well as the utilization rate of nodes, and reduce network cost consumption.