Merging Strategy on Cluster-based MDS Algorithm for Nodes Localization in Wireless Sensor Networks

Abstract

In this paper, we introduce a new map merging method based on least squares method (LSM) in cluster-based multidimensional scaling (MDS) localization systems. Most map merging algorithms used in cluster-based MDS localization systems cannot avoid the accumulation of errors in the map merging process in common. Unfortunately, these errors accumulated in the map merging process lead to a decrease in the performance of position estimation of the whole nodes in a network. Through the proposed merging algorithm based on LSM, the errors accumulated in the map merging process can be avoided. The proposed algorithm can be applied not only to the MDS-based localization system but also to other coordinate-based localization systems. The proposed map merging algorithm shows better performance of position estimation accuracy than the simple merging method used in many cluster-based MDS localization systems in all simulations which are not considering map weight factors. As an example of the highest improvement, a simulation result shows 29% improvement in position estimation accuracy after using each corresponding merging method.