Two-Layer Network Configuration Optimization Approach Considering Primary And Backup Paths

The study of logical-physical networks has signifi-cant meaning, as these networks play a vital role in our daily life. The analysis of their configurations is of paramount importance for ensuring their stability and resilience. In this paper, we propose a mixed-integer planning model that considers primary and backup paths to improve the robustness of the two-layer logical-physical networks. Based on the Monte Carlo simulation method and genetic algorithm, the configuration scheme with the highest expectation of the robustness metric is presented. Experiments are conducted on a case study of network configu-ration with and without backup paths considering random edge failures. The findings illustrate that the incorporation of backup paths can markedly enhance the expectation of robustness metric, thereby reinforcing its stability and resilience of the logical-nhvsical network.