Solving Minimum Cost Three-Dimensional Localization Problem in Ocean Sensor Networks

Localization is one of the most fundamental problems in wireless sensor networks (including ocean sensor networks). Current localization algorithms mainly focus on how to localize as many sensors as possible given a set of mobile or static anchor nodes and distance measurements. In this paper, we consider an optimization problem, the minimum cost three-dimensional (3D) localization problem, in an ocean sensor network, which aims to localize all underwater sensors using the minimum number of anchor nodes or the minimum travel distance of the surface vessel which deploys and measures the anchors. Given the hardness of 3D localization, we propose a set of greedy methods to pick the anchor set and its visiting sequence. Aiming at minimizing the localization errors, we also adopt a confidence-based approach for all proposed methods to deal with noisy ranging measurements (which is very common in ocean sensor networks) and possible flip ambiguity. Our simulation results demonstrate the efficiency of all proposed methods.