基于MCOA的无线传感器网络部署优化方法研究  

Research on optimization method for wireless sensor network deployment based on MCOA

作　　者：闫好霖 李嘉诺 李秋姿 江雷雷 邢友松 YAN Haolin;LI Jianuo;LI Qiuzi;JIANG Leilei;XING Yousong(Nanyang Power Supply Company,State Grid Henan Electric Power Company,Nanyang 473005,China)

机构地区：[1]国网河南省电力公司南阳供电公司,河南南阳473005

出　　处：《微电子学与计算机》2025年第3期135-144,共10页Microelectronics & Computer

摘　　要：为解决无线传感器网络部署优化覆盖率低、传感器节点分布不均匀等问题,提出了一种基于改进黑猩猩优化算法的无线传感器网络部署优化方法。首先,为了保证黑猩猩种群具有多样性,使用Tent混沌映射进行种群初始化;其次,提出了一种非线性变化的收敛因子,以增强算法的全局和局部搜索能力;然后,为了防止算法陷入局部最优,同时引导种群向最优个体靠近,提出了一种狩猎贡献度加权策略对4类黑猩猩在狩猎过程中的贡献程度进行加权处理;最后,通过基准函数测试实验和无线传感器网络部署优化仿真实验验证了所提改进算法的寻优性能和应用性能。结果表明:改进黑猩猩优化算法具有比对比算法更好的寻优性能,其优化得到的无线传感器网络平均覆盖率明显优于其他对比算法,平均覆盖率最高可达99.81%,且传感器节点分布更加均匀。To address the challenges of suboptimal coverage and unequal sensor node distribution in Wireless Sensor Network(WSN)deployment optimization,this paper puts forward a method that leverages an modified version of the chimpanzee optimization algorithm for the optimization of WSN deployment.Firstly,to ensure the diversity of the chimpanzee population,the Tent chaotic mapping is used for population initialization.Secondly,we propose a non-linear convergence factor to boost both the global and local search abilities of the algorithm.Subsequently,a hunting contribution weighting strategy is proposed to balance the contributions of the four types of chimpanzees during the hunting process,with the aim of avoiding the algorithm from falling into local optima and steering the population towards the optimal individual.Finally,the optimization efficacy and applicability of the proposed enhanced algorithm are validated through a series of benchmark function testing experiments and simulation experiments for wireless sensor network deployment optimization.The results show that the modified chimpanzee optimization algorithm has better optimization performance than the comparison algorithms.The average coverage achieved by the modified chimpanzee optimization algorithm is markedly superior compared to other algorithms used for comparison,with the highest average coverage reaching 99.81%,and the distribution of sensor nodes is more uniform.

关 键 词：无线传感器网络 部署优化 改进黑猩猩优化算法 覆盖率 

分 类 号：TN915.9[电子电信—通信与信息系统]