Localization in Wireless Sensor Networks by Cross Entropy Method

Wireless sensor network localization technique remains an open research topic due to its challenges on reducing the location estimation error and cost of the localization algorithm itself. For a large mobile network localization cost becomes increasingly important due to the exponential increment of the algorithmic cost. Conversely sacrificing localization accuracy to a great extent is not acceptable at all. To address the localization problem of wireless sensor network this paper presents a novel algorithm based on cross-entropy (CE) method. The proposed centralized algorithm estimates location information of the nodes based on the measured distances of the neighboring nodes. The algorithm minimizes the estimated location error by using the CE method. Simulation results compare the proposed CE approach with DV-Hop and Simulated Annealing-based localizations and show that this approach provides a balance between the accuracy and cost. When compared with DV-Hop, the CE approach is costlier but much more accurate. When compared with Simulated Annealing-based method, this approach offers the same level of accuracy but is significantly less costly.