Controlled Mobility Sensor Networks for Target Tracking Using Ant Colony Optimization

In mobile sensor networks, it is important to manage the mobility of the nodes in order to improve the performances of the network. This paper addresses the problem of single target tracking in controlled mobility sensor networks. The proposed method consists of estimating the current position of a single target. Estimated positions are then used to predict the following location of the target. Once an area of interest is defined, the proposed approach consists of moving the mobile nodes in order to cover it in an optimal way. It thus defines a strategy for choosing the set of new sensors locations. Each node is then assigned one position within the set in the way to minimize the total traveled distance by the nodes. While the estimation and the prediction phases are performed using the interval theory, relocating nodes employs the ant colony optimization algorithm. Simulations results corroborate the efficiency of the proposed method compared to the target tracking methods considered for networks with static nodes.