A New Distributed Weighted Multidimensional Scaling Algorithm for Localization in Wireless Sensor Networks

There are various applications in wireless sensor networks which require knowing the relative or actualposition of the sensor nodes, but adding GPS receivers or other sophisticated sensors to every node canbe expensive. Multidimensional scaling (MDS) is a recent localization technique that it usesconnectivity information. In this paper, we propose a new iterative distributed localization algorithmbased on Multidimensional Scaling in which each sensor updates its position estimate by minimizing thecorresponding local cost function, after taking measurements and initial position estimate from itsneighboring nodes. The experiments show the proposed algorithm reduces communication cost,complexity, and convergence time.