Robustness analysis of the networks in cascading failures with controllable parameters

Abstract

Network robustness is a core problem in network researches, it has achieved many good results by now. However, the network robustness against cascading failures under various controllable parameters has not been systematically studied.Therefore, based on load-capacity(LC) cascading failures model, a new definition of node load is proposed. An attenuation coefficient γ and exponential coefficient α are added to LC model, it can be proportional to node degree, but not completely proportional and achieves the greater degree and stronger load capacity, which is different from the existed model in related researches. The LC model which combines with random attacks and intention attacks strategies, called hybrid attacks strategy, is established on networks with cascading failures. By simulation, the results show that, in the cases of random attacks and hybrid attacks, the network robustness against cascading failures increases with the increase of scaling attacks and tolerance parameter, and the later parameter displays greater influence when it increases the robustness of networks shifted obviously to right, but declines significantly with the increase of load parameter; in the situation of intention attacks, network experienced extreme vulnerability under two types of controllable parameters and networks show the worst robustness.