Localization in wireless sensor networks by cross entropy method

Wireless sensor network (WSN) localization technique remains an open research issue due to its challenges on reducing location estimation error and cost of localization algorithm itself. For a large mobile network localization cost becomes increasingly important due to the exponential increment of 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 CE method. Simulation results compare the proposed CE approach with DV-Hop and simulated annealing (SA)-based localizations and show that this approach provides a balance between the accuracy and cost.