Nonlinear model of cascade failure in weighted complex networks considering overloaded edges

Abstract

Considering the elasticity of the real networks, the components in the network have a redundant capacity against the load, such as power grids, traffic networks and so on. Moreover, the interaction strength between nodes is often different. This paper proposes a novel nonlinear model of cascade failure in weighted complex networks considering overloaded edges to describe the redundant capacity for edges and capture the interaction strength of nodes. We fill this gap by studying a nonlinear weighted model of cascade failure with overloaded edges over synthetic and real weighted networks. The cascading failure model is constructed for the first time according to the overload coefficient, capacity parameter, weight coefficient, and distribution coefficient. Then through theoretical analysis, the conditions for stopping failure cascades are obtained, and the analysis shows the superiority of the constructed model. Finally, the cascading invulnerability is simulated in several typical network models and the US power grid. The results show that the model is a feasible and reasonable change of weight parameters, capacity coefficient, distribution coefficient, and overload coefficient can significantly improve the destructiveness of complex networks against cascade failure. Our methodology provides an efficacious reference for the control and prevention of cascading failures in many real networks.

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“…As shown in Figure 1, after a while, many network communication links are failed. This action is known as cascading failure, which leads to network segmentation [13,17,18,19]. In [17,20], the authors have modeled cascading failure where the main reason for network shutdown is the overloaded traffic.…”

“…This process may continue in the network, and the failure cycle can be expanded throughout the network [12,13,14,15,16]. This failure is considered as one of the essential items affecting the robustness of IoT networks, which is called cascading failure [17,18,19].…”

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“…For robotic swarms, an approach to adapt their aggregation behavior to the variations in the swarm density and the external environment is present in [23]. For power grids, a nonlinear model for preventing cascading failures in complex networks is suggested in [1]. A fast computation method for the electrical characteristics such as currents, voltages, impedance of a complex electrical ladder network is developed in [17].…”

“…Otherwise, it is damaged. 1 Second, a network is either finite or infinite relying on its number of generations. Table 1 shows that the main contribution of this paper is twofold.…”