A Service Routing Optimization Algorithm for Power Communication Optical Transport Network Based on Knowledge Graph and Reinforcement Learning

Aimed at the single method of power communication OTN transmission network service routing planning, and lack of comprehensive consideration of risk balance, load balancing, and grid service characteristics. this paper proposes a power communication OTN transmission network service routing optimization algorithm based on reinforcement learning and fusion of multiple constraints. In this paper, the knowledge graph technology is used to obtain data sources in each business system, and at the same time, structured data is used to provide knowledge and computable services for the business system. Research and analyze the current transmission status and service characteristics of the power communication network, as well as the requirements for the effectiveness and reliability of transmission requirements. Aiming at the reasons that affect the effectiveness and reliability of the OTN transmission network, a mathematical assessment model of risk balance based on the importance of the business is proposed. At the same time, in order to avoid the large difference in the capacity of each link of the power communication network leading to deviations in the risk balance evaluation, the information entropy of the communication network is introduced as a joint evaluation index. Finally, the feasibility of the algorithm is simulated.