A New Method for Network Coverage Optimization and its Application on Fire Monitoring

Fire monitoring is an important task. We can better monitor the fires by enhancing the coverage rate of the fire wireless sensor networks. However, the maximization of the network coverage to achieve the best monitoring effect is widely recognized as a challenging problem. Thus, it is necessary to develop new technologies for the deployment of the sensor networks. This paper proposes an improved seagull optimization algorithm with particle swarm optimization algorithm (ISOAPSO) to solve the network coverage optimization problem. The ISOAPSO algorithm introduces a nonlinear control strategy and a Lévy flight mechanism to overcome the local optimal problem. It also adopts a hybrid optimal control strategy to further improve the results. This algorithm can improve the coverage in fire wireless sensor network deployment and enhance the fire monitoring capability. Theoretically analysis shows the advantages of our method over seven algorithms on eighteen benchmark functions. ISOAPSO obtains the best coverage rate in the experiments of network coverage optimization for fire monitoring. Therefore, this study validates the effectiveness of ISOAPSO both theoretically and experimentally in the field of fire monitoring.