MDS-BASED METHODS FOR AD HOC NETWORK LOCALIZATION

Recently, multidimensional scaling (MDS) techniques have been successfully applied in the MDS-MAP method to the node localization problem of ad hoc networks, such as wireless sensor networks. MDS-MAP uses MDS to compute a local, relative map at each node from the distance or proximity information of its neighboring nodes. Based on the local maps and the locations of a set of anchor nodes with known locations, the absolute positions of unknown nodes in the network can be computed. In this paper, we investigate the effects of several variants of MDS on the accuracy of localization in wireless sensor networks. We compare metric scaling and non-metric scaling methods, each with several different optimization criteria. Simulation results show that different optimization models of metric scaling achieve comparable localization accuracy for dense networks and non-metric scaling achieves more accurate results than metric scaling for sparse networks at the expense of higher computational cost.