The Multidimensional Scaling and Barycentric Coordinates Based Distributed Localization in Wireless Sensor Networks

Position information is vital for wireless sensor networks in many applications. In this paper, based on the barycentric coordinate system, we incorporate a term constrains sensors to remain the intrinsic structure revealed by range measurements between neighboring nodes into the STRESS function, which is the cost function optimized by the distributed weighted-multidimensional scaling algorithm (dwMDS). By minimizing the modified cost function, we derive a distributed localization algorithm called the Multidimensional Scaling and Barycentric Coordinates based Distributed Localization Algorithm (MDS_BC_DLA). Experimental results on four different types of WSNs show MDS_BC_DLA outperforms dwMDS.