Simulation of Signal Source Energy Attenuation Model Based on Genetic Algorithm

As a platform for real-time acquisition, monitoring and processing of monitoring information, wireless sensor network (WSN) has one of its most basic functions, which is to obtain the node position. In the traditional target location algorithm, it is assumed that all node coordinates have been located and are accurate. However, in the actual WSN, the target location and tracking node position need to be realized by the corresponding node location algorithm. In order to realize the target location and tracking of WSN, this paper proposes a signal source energy attenuation model based on genetic algorithm (GA). Aiming at the shortcomings of existing algorithms based on signal source energy model, this paper proposes a signal source energy attenuation model based on GA, which effectively reduces the sampling range of nodes and improves the sampling efficiency to achieve more accurate positioning. Simulation results show that the algorithm can effectively shorten the positioning time, and the positioning accuracy is improved by about 15% compared with the traditional algorithm. In the location-based routing protocol, accurate location information helps to improve the routing between sensors, thus reducing the power consumption during data transmission.