Research On Risk Assessment Algorithm Of Power Communication Network Based On SDN

With the development of cloud computing,big data and 5G technology,the power communication network(PCN)will continue to evolve towards the power Internet of Things.The network will carry more services and the information transmission methods will become increasingly complex;at the same time,a large number of emerging power businesses have gradually expanded their demand for communications services.Traditional power communications networks are limited in terms of unified network management and unified scheduling of network resources,and their flexibility and scalability are insufficient to meet the needs of the network development.The power communication network under the software defined network(SDN)architecture came into being.The power communication network under the SDN architecture can easily implement network resource scheduling and management,and can quickly allocate resources for network services.The risk assessment of electric power communication network is a research topic with multiple entry points and multiple thinking angles.This paper will use the method based on the link importance entropy to evaluate the network risk,that is,the more balanced the link importance distribution,the lower the network risk.The accuracy of link importance assessment is related to the effectiveness of network risk assessment.Therefore,this article will carry out relevant research work on link importance assessment.The assessment of the importance of existing network elements is mainly based on a single route,which is inconsistent with the fact that many services in the electric power communication network need to be equipped with backup routing.Therefore,this article will consider the power communication of the working and backup routing under the SDN architecture to evaluate the importance of network links.This article proposes a working and backup routing model under the SDN architecture.In this model,the services that need to be protected have completely separate working and backup path.When the link fails and the route is interrupted,when bandwidth and delay allow,the SDN controller will redistribute the working and backup routing for the service according to the importance of the service type.Based on the working and backup routing model,this paper proposes the link importance evaluation algorithm WBR-LIEA,which evaluates link-related risks from three logical levels(service layer,transport layer,and physical topology layer).Through adaptive coefficients,the three levels of link-related risks are merged into a comprehensive link-related risk value to measure the importance of links in the network.In order to verify the effectiveness of WBR-LIEA,this paper established four network performance indicators,namely business importance loss rate LSI,business traffic loss rate LTF,network efficiency NE and network comprehensive risk CNR,and compare them by algorithm for simulation analysis on different power communication networks.The simulation results show that WBR-LIEA can evaluate the link importance more effectively and accurately than the comparison algorithm,and can provide a valuable reference for the risk control and reliability guarantee of the power communication network with active and standby routes under the SDN architecture.Finally,the network risk is evaluated based on the link importance entropy,and the genetic algorithm is used to optimize the network service routing so that the network risk can be effectively reduced.In order to verify the effect of routing optimization,this paper also deliberately attacked the network link under the shortest path and genetic algorithm routing methods.The four network performance indicators above are still used for verification,and it is found that the network link is subject to continuous deliberate attack.The relative performance of the network after genetic algorithm optimization changes relatively slowly,indicating that the optimized network link importance distribution is more balanced,and the network risk is effectively reduced.