Cellular Genetic Algorithms for Optimizing the Area Covering of Wireless Sensor Networks

To maximize the network coverage and prolong the lifetime of the network, an optimization for the Wireless sensor network (WSN) coverage is proposed, which is combined the principle of Cellular automata (CA) with Genetic algorithm (GA) in this paper. Through the evolutionary mechanism of cellular and the redistribution of pheromones, the searching of solution space is effectively improved and the phenomenon of “premature” is avoided. The artificial result reveals that, to a target area having complex boundary, WSN can achieve an optimal cover from a random initial cover by self-organized shift and power control. Moreover, the simulation results also show the Cellular genetic algorithm (CGA) is better than GA and Efficient cover set selection (ECSS) approaches in coverage optimization.