A Coverage Optimization Strategy for Mobile Wireless Sensor Networks Based on Genetic Algorithm

In this paper, we consider the issue of moving objects in a mobile wireless sensor network. Suppose we deploy a limited number of moveable wireless sensor nodes within a preselected area in order to provide coverage of moving objects traveling on a predetermined trajectory path. Due to the insufficient number and limited sensing range of the mobile wireless sensors, the entire object moving trajectory cannot be covered by all deployed sensors. For tackle the problem, sensors must move from one position on the trajectory to another in order to provide complete coverage. Because each sensor is powered only by battery for moving and sensing ability, large amount of movement will cause sensor node energy quickly exhausted. Therefore the goal of moving object coverage problem is to find an optimal movement of mobile sensors such that (1) the total moving distance is minimized and (2) the farthest movement distance is also minimized. We provide a genetic algorithm which takes reasonable crossover and mutation operation to ensure compliance with the topological of actual WSNs and the demand of movement among nodes for solving the moving object coverage problem. Simulations show that the proposed method can find a better schedule than the greedy approach. As a result, the energy consumption of the sensor nodes can be reduced effectively.