Study on The Robustness of Cascade Failure and Recovery of Dependent Networks Under Load

Abstract

In view of the vulnerability of dependent networks and in order to avoid the huge impact of cascading failures on life, this paper adopts four dependent network recovery algorithms: random recovery (RR), preferential recovery based on local centrality (PRL), preferential recovery based on degree centrality (PRD), and preferential recovery based on connectivity link (PRCL). Using scale-free network (SF) and random network (ER) as sub-network models, a one-to-one dependent network is built with random coupling of SF-SF and ER-ER, and the cascade failure process includes dependent failure, overload failure and non-maximum connected network failure, and experiments were conducted to examine the recovery effects of these four recovery models on different recovery ratios and different dependent network models under the action of load [1]. In this paper, the curve of the robustness of dependent networks with load tolerance after cascading failure and recovery is drawn, and finally it is proved that the robustness of the dependent network after recovery is significantly improved compared with that before recovery, which proves that all four recovery methods are effective, and the relationship between robustness of dependent network after recovery and load tolerance, recovery ratio and edge parameters is obtained.