In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

In this paper, an energy-efficient strategy is proposed for tracking a moving target in a mobile sensor network. The energy expenditure of the sensors in the network is assumed to be due to communication, sensing and movement. First, the target area is divided into a grid of sufficiently small rectangular cells in order to search for near optimal locations for the sensors in different time instants. The grid is then converted to a graph with properly weighted edges. A shortestpath algorithm is subsequently used to route information from target to destination by a subset of sensors.

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In this paper, an energy-efficient technique is proposed for tracking a target in a field using a network of mobile sensors while maximizing the life span of the network. The most important energy consumption sources in a mobile sensor network (MSN) are sensing, communication and movement of the sensors. In the proposed technique, first the field is divided into a grid of arbitrarily small cells. This grid is then used to obtain a graph with properly weighted edges. The weight assignment is done in such a way that it results in a close estimate of the maximum lifetime for the network. Finally, using a shortest path algorithm, an efficient route is found to transfer information from the target to destination.

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