Routing Optimization of Sensor Nodes in the Internet of Things Based on Genetic Algorithm

As an important part of the perception layer of the Internet of things, wireless sensor networks will provide sensing data for the application of the Internet of things, so it is necessary to optimize the routing path of wireless sensor nodes for the application of the Internet of things. Aiming at the problem of optimal selection of wireless sensor nodes for the Internet of things, this paper describes the mathematical model and abstracts it as a multi-objective optimization problem. Secondly, through the analysis of the deployment optimization process, this paper abstracts the optimization selection method of wireless sensor nodes facing the Internet of things and the guarantee method to avoid coverage holes. Then a node selection method based on a genetic algorithm is proposed to solve the problems of high redundancy and high energy consumption in the internet of things. In the application process of genetic algorithm, aiming at the possible problems of standard genetic algorithm, the similarity judgment is introduced into the crossover operation, and the operation of introducing new individuals is added into the genetic process. Finally, simulation experiments are carried out to verify the feasibility, efficiency, and parameter setting of the algorithm. The simulation results show that the proposed method can guarantee the coverage of the area to be monitored, reduce the network energy consumption and keep the energy consumption balanced.

Automated summary

This paper focuses on the optimization of routing paths for wireless sensor nodes in the Internet of Things, proposing a node selection method based on genetic algorithm and verifying its feasibility and efficiency through simulation experiments. The research results can effectively guarantee the coverage of monitored areas, reduce network energy consumption, and maintain energy balance.