ZHOU K Q, YANG S Y, KANG D W, et al. Coverage optimization in wireless sensor networks  based on improved cuckoo search algorithm [J]. Journal of Henan Polytechnic University (Natural Science) , 2025, 44(4): 48-58.

doi: 10.16186/j.cnki.1673-9787.2024070037

Received: 2024/07/09

Revised: 2024/09/11

Published: 2025/06/19

Coverage optimization in wireless sensor networks  based on improved cuckoo search algorithm

Zhou Kaiqing, Yang Senyu, Kang Diwen, Ou Yun

School of Communication and Electronic Engineering， Jishou University， Jishou 416000， Hunan， China

Abstract: Objectives To enhance the coverage rate of Wireless Sensor Networks （WSN）.   Methods An Improved 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 algorithm by establishing a Markov model. Through iterative process analysis， it identifies improvement directions， 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 introduced 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-based search operations. Finally， a multi-strategy based stochastic preference walk algorithm is employed， incorporating information from the global optimal solution to guide the population evolution towards the optimal solution. Experiments modeled WSN coverage optimization under three assumptions： node homogeneity， identical sensing/communication ranges， and real-time node sensing capability， while establishing cuckoo individual construction methods. Targeting maximal WSN coverage rate， the discrete point monitoring method was employed 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 results 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. 

Key words: wireless sensor network; Markov chain; cuckoo search algorithm; dimension-by-dimension update; opposition-based search