摘要
无线传感器网络(Wireless sensor network,WSN)中的核心技术之一就是节点定位。不同的定位方法对定位结果有不同的影响。针对最小二乘法在求解未知节点位置过程中定位精度的不足,提出一种WSN节点定位算法--基于改进的布谷鸟搜索算法(Cuckoo search,CS)的定位算法。首先根据优化目标建立数学模型,然后设计了布谷鸟搜索算法中的适应值函数,并修改步长和拒绝概率参数,快速确定未知节点坐标位置。数字仿真实验表明:与基于距离向量跳数的定位方法(Distance vector hop,DV-HOP),基于自适应的布谷鸟搜索和距离向量跳数的定位算法(Self-adaption cuckoo search and distance vector hop,SACSDV-HOP)进行比较,本文算法可以有效提高节点定位精度,降低定位误差,具有较高的实用性。
Node localization is one of the core technologies in wireless sensor network(WSN).Different localization methods have different effects on localization results.In response to the deficiency in accuracy of localization during the process of searching for the unknown node localization with the least-square algorithm,a localization algorithm is proposed based on improved cuckoo search(CS)algorithm.The first step is to establish the mathematical model according to the optimization objective,and then we design the fitness function of cuckoo search algorithm.Finally,we modify the parameters of the step length and rejection probability and thus determine the coordinate position of the unknown nodes quickly.The simulation results show that the proposed algorithm is better than the distance vector hop(DV-HOP)and the self-adaption cuckoo search and distance vector hop(SACSDV-HOP)algorithms.The algorithm can effectively reduce the error of localization in WSN and improve the accuracy in locating nodes.Accordingly,it has high practicability in WSN node localization.
作者
李娜
贾伟
LI Na;JIA Wei(School of Mathematics and Computer Science,Shaanxi University of Technology,Hanzhong,723000,China)
出处
《数据采集与处理》
CSCD
北大核心
2020年第2期315-321,共7页
Journal of Data Acquisition and Processing
基金
陕西省教育厅(17JK0146)资助项目
陕西理工大学科研基金(SLG1915)资助项目。
关键词
节点定位
无线传感器网络
最小二乘法
布谷鸟搜索算法
智能优化
node localization
wireless sensor network(WSN)
least-square algorithm
cuckoo search(CS)algorithm
intelligent optimization
