A multidimensional scaling analysis algorithm of nodes localization based on steepest descent in wireless sensor networks

Authors:
Zhao Qing-Hua;Li Liang;Li Hua;Zhang Kunpeng;Wang Huakui
Affiliations:
College of Information Engineering, Taiyuan University of Technology, Taiyuan, China;Urban and Tourism College, Taiyuan Normal University, Taiyuan, China;College of Information Engineering, Taiyuan University of Technology, Taiyuan, China;College of Information Engineering, Taiyuan University of Technology, Taiyuan, China;College of Information Engineering, Taiyuan University of Technology, Taiyuan, China
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Year:
2011

Citing 2
Cited 0

Localization from Connectivity in Sensor Networks

IEEE Transactions on Parallel and Distributed Systems
Distributed weighted-multidimensional scaling for node localization in sensor networks

ACM Transactions on Sensor Networks (TOSN)

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Abstract

This article studies the classical MDS and dwMDS location algorithm. On this basis, steepest descent algorithm is introduced to replace SMACOF algorithm as optimization objective function. The results show that the steepest descent method as the optimization objective function is simple and easy to implement. Compared with the dwMDS method based on SMACOF algorithm, the distributed MDS positioning algorithm with the steepest descent method has increased significantly in accuracy, and it has a relatively good performance in the anti-Error effects, the convergence and convergence speed, even in the uneven performance of the network also performed well.