Research on Risk Assessment Algorithm for Power Monitoring Global Network Based on Link Importance and Genetic Algorithm

Abstract

To improve the risk assessment capability of the Power Monitoring Global Network (PMGN), based on the Software Defined Network (SDN) architecture, a Link Importance Evaluation Algorithm (LIEA-ARBR) based on the Active Route and the Backup Route was constructed. The link association risk degree before and after the link failure at different levels was calculated, and the adaptive coefficient was used to fuse the link association risk of the three-layer link, and the link importance degree of the active and backup routes was formed. The simulation results showed that the LIEA-ARBR can more accurately and reliably evaluate the importance of network links whether it was a small or large network, and services were randomly distributed or deterministically distributed, providing a prerequisite for risk assessment and control of PMGN. Taking the network risk as the optimization goal, a routing optimization strategy based on genetic algorithm is formed. The network risk assessment result based on Genetic Algorithm was 37.43% lower than that of the Shortest Path Algorithm; when subjected to simulated network attacks, the CNR of important links was reduced by nearly 20%, and the overall network risk was reduced by nearly 19%.