Solving the Node Localization Problem in WSNs by a Two-Objective Evolutionary Algorithm and Local Descent
Given a small percentage of nodes whose actual positions are known, the problem of estimating the locations of the remaining nodes of a wireless sensor network has attracted a large interest in the last years. The localization task is based on the noisy estimates of the distances between pairs of nodes in range of each other. The problem is particularly hard when the network connectivity is not sufficiently high, the most attractive case in real applications. In this paper, the authors propose to solve the localization problem by using a two-objective evolutionary algorithm which takes concurrently into account during the evolutionary process both the localization accuracy and certain topological constraints induced by the network connectivity.