Node deployment optimization of wireless sensor network based on hybrid chicken swarm optimization algorithm
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摘要：
无线传感网络(Wireless Sensor Network,WSN)技术,在节点随机部署的情况下,容易出现节点分布不均的问题.为了提高节点部署的覆盖率,提出了一种基于混合鸡群优化算法(Hybrid Chicken Swarm Optimization Algorithm,HCSO)的WSN节点部署优化方法.首先为了平衡算法的全局搜索和局部搜索的能力,提出了一种自适应种群分配策略;其次,结合正余弦算法思想,改进了公鸡种群更新公式,提高其收敛速度和精度;最后,优化小鸡种群学习方式,使其不仅学习母鸡,也向公鸡和最优个体学习,提高小鸡粒子的质量.将HCSO算法在基准函数上测试,实验结果表明,本算法比其他算法的法收敛精度提高了10%,收敛速度均比原算法提高了0.05~0.10 s.最后将HCSO算法应用于WSN节点部署优化中,结果表明所提出的方法所得到的覆盖率高于其他算法,提高了0.2~13.1个百分点,充分证明了基于HCSO算法的WSN节点部署优化方法的优越性.
Wireless Sensor Network(WSN)technology,with random node deployment,is prone to the problem of uneven node distribution.To improve the coverage of node deployment,this paper proposes a Hybrid Chicken Swarm Optimization Algorithm(HCSO)based WSN node deployment optimization method.Firstly,an adaptive population allocation strategy is proposed to balance the ability of global search and local search of the algorithm;secondly,by combining the idea of Sine and Cosine Algorithm,the rooster population update formula is improved to improve its convergence speed and accuracy;finally,the chick population learning method is optimized so that they not only learn from the hen but also learn from the rooster and the optimal individual to improve the quality of chick particles.The HCSO algorithm is tested on the benchmark function,and the experimental results show that the present algorithm improves the accuracy of the method convergence by 10% compared with other algorithms,and the convergence speed is all improved by 0.05-0.10 seconds compared with the original algorithm.Finally,the HCSO algorithm is applied to the optimization of WSN node deployment,and the results show that the coverage obtained by the method proposed in this paper is higher than other algorithms by 0.2-13.1 percentage points,which fully proves the superiority of the WSN node deployment optimization method based on the HCSO algorithm.
作者：
韦修喜 郑宝峰
Wei Xiuxi;Zheng Baofeng(College of Artificial Intelligence,Guangxi Minzu University,Nanning 530006,China;College of Electronic Information,Guangxi Minzu University,Nanning 530006,China)
机构地区：
广西民族大学人工智能学院 广西民族大学电子信息学院
出处：
《betway官方app 学报:自然科学版》 CAS 北大核心 2023年第5期57-66,I0006,共11页
Journal of Henan Normal University(Natural Science Edition)
基金:
国家自然科学基金(62266007,61662005) 广西自然科学基金(2021GXNSFAA220068,2018GXNSFAA294068)。
关键词:
无线传感网络 节点部署 鸡群优化算法 自适应分配 正余弦算法
wirelesssensornetwork nodedeployment chickenswarmoptimizationalgorithm adaptiveallocation sine cosinealgorithm
分类号:
TP18 [自动化与计算机技术—控制理论与控制工程]
