Coverage optimization in wireless sensor networks based on improved cuckoo search algorithm
Zhou Kaiqing
Yang Senyu
Kang Diwen
Ou Yun
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.
Keywords：wireless sensor networkMarkov chaincuckoo search algorithmdimension-by-dimension up-dateopposition-based search
Publication Date：2025-07-31
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：12( 48-58,141 )