Routing Optimization Algorithm for Electric Power Communication Network Based on Graph Neural Network
With the development of society and the increasing demand for electricity,to guarantee the transmission reliability of important data in electric power communication networks has become one of the main focuses.In particular,when facing the changes in network topology due to natural disasters,human social activities,etc.,as well as the variations in communication requirements of electric power services,it is very challenging to quickly establish reliable routes for all services.It is difficult to obtain the opti-mal path combination in real time through traditional methods.In this paper,by analyzing the character-istics of network structure and task requirements,we formulate a routing optimization problem for both du-al-routing and single-routing applications,aiming to improving the transmission reliability of electric pow-er data.By combining the graph neural network with depth-first search method,we propose a novel rou-ting scheme which is scalable for different network scenarios and service requirements.Simulation results show that compared with the traditional routing algorithm,our proposed algorithm can achieve higher rou-ting reliability under delay and capacity constraints,and can be extended to the power communication network with different structures.
power communication networkroutinggraph neural network
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