Abstract—In wireless ad-hoc networks, the nodes are randomly distributed in a field; and in most cases, only the distances in between the nodes are available practically. The main goal in such a problem is to obtain the coordinates from the data regarding the distance pairs. One of the tools for solving this problem is the Multidimensional Scaling Method (MDS). Additionally, due to the imperfect conditions in the field, the measurement data contains noise and uncertainties. In this study, a sequentially-executed method is proposed with the aid of the combination of Scaling by Majorizing a Complicated Function (SMACOF) method and the Particle Swarm Optimization (PSO). The results show that the proposed framework reduces the error under different environmental conditions.

 

Index Terms—Multidimensional scaling, MDS, scaling by majorizing a complicated function, SMACOF, particle swarm optimization

Cite: O. Tolga Altinoz, Ahmet Akbulut, Tolga Numanoglu, Güven Yenihayat, Cagri Goken, and A. Egemen Yilmaz, "Node Localization with MDS-Based Hybrid Algorithms at Mobile Ad-Hoc Networks," Journal of Communications, vol. 12, no. 3, pp. 194-199, 2017. Doi: 10.12720/jcm.12.3.194-199