Prediction-based dynamic routing intelligent algorithm in power optical communication network

New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network ( POCN ) more dynamic and changeable. This is directly reflected in the dynamics of the link risk and service importance of the POCN. In this paper, aiming at the problem of the dynamic importance of service in POCN, and the resulting power optical communication network reliability decline problem, a new energy POCN dynamic routing intelligence algorithm based on service importance prediction is proposed. Based on the short-term power generation of new energy power station, the importance of each service and the risk degree of each link are predicted. Link weights are dynamically adjusted, and k-shortest path ( KSP) algorithm is used to calculate route results. When network resources are insufficient, low-importance services can give way to prevent a large number of high-importance services from being blocked. Simulation results show that compared with the traditional KSP algorithm, the prediction-based dynamic routing intelligent ( P-DRI) algorithm can reduce the service blocking probability by 55.59% , and reduce the average importance of blocking services by 44.77% at the cost of about 6.17% of thecalculation delay.