河南理工大学学报（自然科学版）2025，Vol.44Issue(4)：48-58,141,12.DOI:10.16186/j.cnki.1673-9787.2024070037
基于改进布谷鸟搜索算法的无线传感器网络覆盖优化
Coverage optimization in wireless sensor networks based on improved cuckoo search algorithm
摘要
Abstract
Objectives To enhance the coverage rate of Wireless Sensor Networks(WSN).Methods An Im-proved Cuckoo Search with Multi-Strategies(ICS-MS)algorithm is proposed for the coverage optimization problem in WSN.The ICS-MS algorithm analyzes the optimization process of the standard Cuckoo Search al-gorithm by establishing a Markov model.Through iterative process analysis,it identifies improvement direc-tions,reduces self-transition probability,decreases the theoretical average iteration count,and implements a series of optimized strategy selections.Initially,a phased dimension-by-dimension update strategy is intro-duced to mitigate the dimension coupling effect in high-dimensional spaces and to reduce the self-transition probability of the solution space.Subsequently,elite individuals are retained based on their fitness after performing Lévy flight operations,and the search domain is expanded through opposition-basedsearch op-erations.Finally,a multi-strategy based stochastic preference walk algorithm is employed,incorporating in-formation from the global optimal solution to guide the population evolution towards the optimal solution.Ex-periments modeled WSN coverage optimization under three assumptions:node homogeneity,identical sens-ing/communication ranges,and real-time node sensing capability,while establishing cuckoo individual con-struction methods.Targeting maximal WSN coverage rate,the discrete point monitoring method was em-ployed to compare the proposed ICS-MS against standard CS and six variants(MACS,DA-DOCS,WCSDE,ICS-ABC-OBL,CSDE,ICS)under 20-node and 30-node scenarios.Results The experimental re-sults show that the ICS-MS algorithm,in 20 nodes scenario,achieves an average increase in coverage rate of 17.12%～17.35%compared to the comparative algorithms;in 30 nodes scenario,the average increase is 10.09%-18.05%.Conclusions The ICS-MS algorithm demonstrates more uniform node distribution,higher coverage rates,and faster convergence rates in the field of WSN coverage optimization.关键词
无线传感器网络/马尔可夫链/布谷鸟搜索算法/逐维更新/反向搜索Key words
wireless sensor network/Markov chain/cuckoo search algorithm/dimension-by-dimension up-date/opposition-based search分类
电子信息工程引用本文复制引用
周恺卿,杨森宇,康棣文,欧云..基于改进布谷鸟搜索算法的无线传感器网络覆盖优化[J].河南理工大学学报（自然科学版）,2025,44(4):48-58,141,12.基金项目
国家自然科学基金资助项目(62066016) （62066016）
湖南省自然科学基金资助项目(2024JJ7395) （2024JJ7395）
湖南省教育厅科学研究优秀青年项目(22B0549) （22B0549）
