摘要
针对三维无线传感器网络(3D WSNs)的节点部署问题,提出了一种基于双层混沌粒子群优化(TCPSO)算法的解决方案。利用TCPSO算法对节点进行优化部署,以提高网络的空间覆盖率。TCPSO算法通过非线性分类系数将种群分为精英种群和普通种群,分别采取不同的速度、位置更新公式进行迭代优化。TCPSO提出了基于Logistic混沌映射的递减惯性权重,用来控制算法在局部的开发,并且为了避免算法早熟,引入了Levy飞行策略增强算法的全局搜索能力。通过在1个三维网格空间中进行仿真实验,验证TCPSO以及粒子群优化(PSO)算法解决3D WSNs的节点部署问题的能力。分别在不同数量的节点数、不同的通信半径以及不同的种群规模上进行了3组实验,实验采用控制变量法,观察在不同条件下TCPSO的性能。TCPSO在全部的实验中提出的节点部署方案均明显优于PSO的部署方案。
Three-dimensional wireless sensor networks(3D WSNs)are communication networks consisting of numerous wireless sensor nodes.Aiming at the node deployment problem of 3D WSNs,a solution based on the two-layer chaotic particle swarm optimization(TCPSO)algorithm is proposed.TCPSO is utilized to optimize the deployment of nodes and improve the spatial coverage of the network.The TCPSO algorithm divides the population into elite and ordinary subpopulations based on nonlinear classification coefficients,adopting different velocity and position update formulas for iterative optimization.TCPSO introduces a decreasing inertia weight based on Logistic chaotic mapping to control the local exploitation of the algorithm.To avoid premature convergence,levy flight strategy is introduced to enhance the global search ability of the algorithm.Simulation experiments are conducted in three-dimensional grid space to verify the ability of TCPSO and particle swarm optimization(PSO)algorithms to solve the node deployment problem of 3D WSNs.Three sets of experiments are conducted with different numbers of nodes,communication radii,and population sizes,respectively.The control variable method is adopted to observe the performance of TCPSO under different conditions.The node deployment solutions proposed by TCPSO in all experiments are significantly superior to those of PSO.The experimental results indicate that the proposed scheme can effectively improve the spatial coverage of 3D WSNs,reduce the cost of network construction,and provide strong support for practical applications.
作者
赵梦玲
赵昊男
ZHAO Mengling;ZHAO Haonan(College of Science,Xi’an University of Science and Technology,Xi’an 710054,China)
出处
《河南科技大学学报（自然科学版）》
CAS
北大核心
2024年第4期40-48,M0004,M0005,共11页
Journal of Henan University of Science And Technology:Natural Science
基金
国家自然科学基金项目(51974231,12302038)。
关键词
无线传感器网络
节点部署
空间覆盖率
粒子群优化算法
wireless sensor networks
node deployment
spatial coverage
particle swarm optimization algorithm
作者简介
赵梦玲(1974-),女,陕西西安人,副教授,硕士生导师,主要研究方向为机器学习和进化计算.
