Coverage Optimization based on Improved NSGA-II in Wireless Sensor Network

Wireless sensor networks (WSN) constitute the platform of a wide application related to military, remote monitoring, inhospitable physical environment, and national security. Reducing energy consumption to extend network lifetime is one of the most important requirements in designing wireless sensor networks. Keeping only a minimal number of sensors active and putting others into low-power sleep mode is one promising approach to conserve system energy, in which the active sensors can maintain the communication connectivity and cover the target region completely. However, the problem of sorting such minimal active sensor set is NP-complete. In this paper, elitist non-dominated sorting genetic algorithm (NSGA-II), a new multi-objective genetic algorithm, is applied to coverage problem in wireless sensor networks. The novel scheme maximizes the coverage using a relative small quantity of sensor nodes in a given target area. Simulation results show that the algorithm is fast and effective, which gives strong support to the selection of optimal node set.