一种改进果蝇算法的WSN节点定位方法  

A node location method based on improved fruit fly optimization algorithm of WSN

作　　者：王海云 唐亮[1] 林智慧[1] Wang Haiyun;Tang Liang;Lin Zhihui(School of Electronics and Information Engineering,Xi'an Siyuan University,Shaanxi Xi'an,710038,China)

机构地区：[1]西安思源学院电子信息工程学院,陕西西安710038

出　　处：《机械设计与制造工程》2023年第4期116-120,共5页Machine Design and Manufacturing Engineering

基　　金：陕西省教育厅科研计划项目(21JK0856)。

摘　　要：针对三边测量法在测距过程中产生的误差,利用果蝇优化算法收敛速度快、精度高、实现简单的特点设计了一种改进果蝇算法的WSN节点定位方法。通过算法反复迭代、比较、择优,获得未知节点与锚节点之间距离误差的最小值,从而实现对未知节点的准确定位。算法从不同种群数、不同初始位置、不同飞行区间3个方面进行了参数的比较与选择,确定获得准确定位时算法各参数取值的重要性。将该定位算法与基于粒子群的DV-Hop定位算法进行定位比较,结果表明该定位算法具有更好的准确性。Aiming at the positioning errors in the trilateration method,a wireless sensor network(WSN)node location method is designed based on the advantages of fast convergence,high precision and simple realization of fruit fly optimization algorithm.The minimum distance error between the unknown node and the anchor node can be obtained through iterative,comparison and selection of the algorithm,so as to achieve accurate positioning.The algorithm parameters are compared and selected from three aspects:different population number,different initial position and different flight interval,determines the importance of each parameter value in obtaining accurate positioning.Otherwise,the localization algorithm is compared with DV-Hop based on particle swarm optimization,the simulation results show that the localization algorithm has better accuracy.

关 键 词：无线传感器网络 果蝇优化算法 节点定位 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]