Distribution Localization Estimation Algorithm in Wireless Sensor Networking

This paper proposes an incremental localization algorithm in wireless sensor network based on the estimation of distribution algorithms. In this algorithm, the distances between an unknown node and the anchor nodes are measured, and then samples are chosen in the area in which the unknown node is located possibly. Thus, the high accuracy samples selection is based on the calculated fitness, and the probability distribution of the location coordinates is updated. It optimizes the location results through the learning and evolution of the samples and the probability distribution. Simulation results show that the proposed algorithm achieves the comparable performance with other up-to-date complex localization algorithms at low noise level.