基于改进ACO的无线传感器网络节点定位算法

Node Location Algorithm for Wireless Sensor Networks Based on Improved ACO

为了优化节点定位算法,研究将节点定位问题转化为一个非常适合蚁群优化算法(ant colony optimization,ACO)的函数优化问题,提出了一种基于改进ACO的新型节点定位算法。该算法根据蚁群在上一次迭代中的路径选择,动态调整路径选择的概率和更新策略,从而避免算法陷入局部最优。在实验中,将提出的ACO定位算法与经典的无范围算法DV-Hop以及遗传算法进行了比较,结果表明,ACO算法在定位精度方面优于DV-Hop和遗传算法,同时,ACO定位算法表现出更强的稳定性和更快的收敛速度。

In order to optimize the node localization algorithm,a new node localization algorithm based on improved ACO is proposed to transform the node localization problem into a function optimization problem that is very suitable for ant colony optimization(ACO) algorithms.This algorithm dynamically adjusts the probability and update strategy of path selection based on the path selection of the ant colony in the previous iteration,thereby avoiding the algorithm from falling into local optima.In the experiment,the proposed ACO localization algorithm was compared with classic rangeless algorithms DV-Hop and genetic algorithm.The results showed that the ACO algorithm outperformed DV-Hop and genetic algorithm in localization accuracy.At the same time,the ACO localization algorithm showed greater stability and faster convergence rate.