文献类型：期刊文献

英文题名：Secure Clustering Strategy Based on Improved Particle Swarm Optimization Algorithm in Internet of Things

作者：Bao, Zhanbiao[1]

第一作者：暴占彪

通讯作者：Bao, ZB[1]

机构：[1]Henan Univ Econ & Law, Ctr Educ Technol, Zhengzhou 450046, Henan, Peoples R China

第一机构：河南财经政法大学

通讯机构：[1]corresponding author), Henan Univ Econ & Law, Ctr Educ Technol, Zhengzhou 450046, Henan, Peoples R China.|[10484]河南财经政法大学;

年份：2022

卷号：2022

外文期刊名：COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE

收录：;EI(收录号：20223112455131);Scopus(收录号：2-s2.0-85134887944);WOS:【SCI-EXPANDED(收录号:WOS:000872079200009)】；

基金：This work was supported by the Natural Science Foundation of China (No. 61502434).

语种：英文

外文关键词：Cluster analysis - Energy utilization - Particle swarm optimization (PSO)

摘要：This paper proposes a secure clustering strategy based on improved particle swarm optimization (PSO) in the environment of the Internet of Things (IoT). First, in the process of cluster head election, by considering the residual energy and load balance of nodes, a new fitness function is established to evaluate and select better candidate cluster head nodes. Second, the optimized adaptive learning factor is used to adjust the location update speed of candidate cluster head nodes, expand the local search, and accelerate the convergence speed of global search. Finally, in the stage of forwarding node election and data transmission, in order to reduce the energy consumption of forwarding nodes, each cluster head node elects a forwarding node among the ordinary nodes in its cluster, so that the elected forwarding nodes have the optimal energy and location relationship. Experiments show that the proposed method effectively prolongs the network lifetime compared with the comparison methods. The average node degree of the proposed method is less than 2.5.