Binary Information Press
In this paper, the authors focus on the methods of localization with iterative optimization in wireless sensor networks. After studying the multi-dimensional scaling algorithms and traditional gradient optimization methods, they determine the function relation between iteration step size and network connectivity based on numerical experiments and introduces a connectivity-based distributed weighted Multi-Dimensional SCaling algorithm, dwMDSC. The algorithm firstly calculates the iterative step size with the average value of connectivity it optimizes the local cost functions. Experiments show that this method performances a faster and more stable convergence than dwMDS algorithm which is based on SMACOF algorithm.