Research on Optimization of WSN Network Communication Service Based on Decision Tree Algorithm

Aiming at the problems of single path and high energy consumption in current methods, this paper puts forward an optimization method of WSN (Wireless sensor network) network communication service based on DT (Decision tree) algorithm, in order to meet the optimization requirements of WSN network communication service, determine key parameters, take key variables as the input values of overrun fast learning machine, and use the learning machine to train and output the routing optimization results to complete network routing optimization. At the same time, PSO (Particle Swarm Optimization) algorithm is introduced, and penalty function method is used to help the algorithm get rid of the constraints of local minima and improve the optimization speed, and the improved PSO is introduced into DT tree-building method. The research results show that this method has high classification accuracy, can get the appropriate number of scientific variables, and improve the final routing optimization effect. With the increase of the number of nodes, the energy consumption of the proposed algorithm is about 33.3% of the literature algorithm. When the network scale reaches the maximum, its energy consumption is less than 150 mW, which ensures the synchronization accuracy and the energy utilization effect is good. Experiments show that the key parameters selected in this method can complete routing optimization, effectively improve data transmission rate and reduce energy consumption.