A kind of wireless sensor network coverage optimization algorithm based on genetic PSO

Aiming to the problems of slow convergence speed and being easily early-maturing etc. in existing network based on standard particle swarm algorithm, this paper proposes a wireless sensor network coverage optimization algorithm based on the genetic particle swarm optimization (PSO). The wireless sensor maximum coverage is regarded as the objective function, the genetic algorithm with adaptive crossover and mutation factors is used to search the solution space, and the powerful global search ability of PSO is used to increase search scope to make particle covering more efficient, which both strengthen algorithm optimization ability, improve the nodes coverage, and solve early-mature problem. Comparing with the standard traditional genetic algorithm and new quantum genetic algorithm, simulation results present that the rate of coverage in this algorithm increases by 2.28 % and 0.65 % respectively; and convergence speed is also improved, therefore this method can effectively realize the wireless sensor network coverage optimization. © 2013 by IFSA.