Research on Particle Swarm Optimization strategy for forest fire detection system based on Wireless Sensor Networks
In order to improve the network performance, to increase network coverage rate, to achieve the maximization of network coverage and extend the network of life in the forest fire detection system, the present research has proposed a Wireless Sensor Networks (WSNs) coverage Particle Swarm Optimization (PSO) strategy on the basis of probability measuring model. Through the PSO, the strategy achieves coverage control for the optimization objectives of network coverage rate and analyzes the effect of coverage performance about sensing radius. The coverage rate has increased and convergence rate has speeded up with perceived radius increased gradually. The simulation shows that effective coverage has reached 85.63 percent. Compared with the Conventional Genetic Algorithms (CGA) about the optimization effectiveness, the coverage rate has increased by 0.64 percent and the convergence rate has increased 13.7 percent. Therefore, the PSO strategy has a better coverage optimization results than CGA.