基于连通度的分布式加权多维尺度节点定位算法

研究了迭代优化方法在无线传感器网络节点定位中的应用,针对多维尺度分析定位技术和传统的梯度迭代优化方法,根据数值实验确定了迭代步长和网络连通度之间的函数关系,提出了一种基于连通度的分布式多维尺度分析节点定位算法(a connectivity-based distributed weighted multidimensional scaling algorithm,简称dwMDS(C)).该算法首先根据网络的平均连通度确定迭代步长,然后对每个未知节点的局部代价函数进行优化求解.实验表明该迭代算法收敛快速且稳定,比基于SMACOF算法的dwMDS(G)算法在定位精度上有明显的提高.

A Connectivity-based Distributed Weighted-multidimensional Scaling Algorithm for Nodes Location in Wireless Sensor Network

This paper focuses on the methods of localization with iterative optimization in wireless sensor networks. After studying the Multi-dimensional scaling algorithms and traditional gradient optimization methods, we determine the function relation between iteration step size and network connectivity based on numerical experiments and introduce a connectivity-based distributed weighted Multi-dimensional scaling algorithm. First, this method calculates the iteration step size with the average value of connectivity ,then it optimizes the local cost functions. Experiments show that this method performances a faster and more stable convergence than dwMDS(G) algorithm which is based on SMACOF algorithm.