计算机与数字工程2025，Vol.53Issue(3)：623-627,683,6.DOI:10.3969/j.issn.1672-9722.2025.03.002
基于改进K-means和熵权法的WSN分簇路由算法
WSN Clustering Routing Algorithm Based on Improved K-means and Entropy Weight Method
摘要
Abstract
Aiming at the problems of limited energy and unbalanced load of the wireless sensor network,a WSN clustering routing algorithm based on improved K-means and entropy weight method(IKEW)is proposed.During the clustering phase,this al-gorithm improves the K-means algorithm using density-based methods and maximum-minimum distance,and adopts a reassign-ment scheme to balance the number of nodes in each cluster.During the cluster head selection phase,the entropy weight method is used to calculate the weight of each node index,making the selection of cluster heads more reasonable.During the data transmission phase,a communication consumption function is constructed based on the cluster head's remaining energy and the data's transmis-sion distance to select relay nodes.Simulation results show that the proposed algorithm can effectively balance network energy con-sumption and prolong the network lifetime.关键词
无线传感器网络/K-means/节点重分配/熵权法/负载均衡Key words
wireless sensor network/K-means/node redistribution/entropy weight method/load balancing分类
计算机与自动化引用本文复制引用
方旺盛,王旭..基于改进K-means和熵权法的WSN分簇路由算法[J].计算机与数字工程,2025,53(3):623-627,683,6.基金项目
国家自然科学基金项目(编号:62062037)资助. （编号:62062037）
