Optimization and Control of Wireless Rechargeable Sensor Network Based on Intelligent Algorithm

Aiming to optimize the charging scheme and deployment cost of wireless rechargeable sensor network when the node coordinates are given. We first establish a TSP charging route model of a single mobile charger, use an improved ant colony algorithm to deal with the problem of the nearest charging route, and then establish an aperiodic greedy charging model based on the imbalance of sensor energy consumption of the shortest charging path obtained. Two reasonable charging strategies and a variable step size adaptive algorithm are used to search for the minimum battery capacity required for the sensor to work normally, so as to optimize the entire wireless rechargeable sensor network. The simulation using the data provided by MMCT indicates that the model and algorithm are able to commendably control the normal operation of the sensor network and reduce the operating cost of the entire network.