Cholesky MDS: A Fast and Efficient Heterogeneous Localization Algorithm

摘要

Creating an efficient localization algorithm for Internet of Things (IoT) and heterogeneous networks has been of the greatest challenges in the recent years for the researchers and industries. There has been significant efforts to increase the estimation accuracy and computational speed of localization algorithms either by improving the already existing ones or proposing new solutions. In this paper we propose a new algorithm, namely Cholesky MDS (CMDS) which is based on Multidimensional Scaling (MDS) and Super MDS (SMDS). Likewise SMDS, the proposed algorithm allows angle and distance information to be used simultaneously for an accurate position estimation while offering a computational speed of up to 8 times faster. This makes CMDS one of the best candidates for real-time and power-constrained scenarios especially those involving large networks and fast moving targets.