Chen Chao-Yang, Zhao Yang, Gao Jianxi, Stanley Harry Eugene
School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, 411201, People's Republic of China.
Center for Polymer Studies and Department of Physics, Boston University, Boston, MA, 02215, USA.
Sci Rep. 2020 Aug 10;10(1):13428. doi: 10.1038/s41598-020-69775-5.
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.
考虑到实际网络的弹性，网络中的组件对负载具有冗余容量，如电网、交通网络等。此外，节点之间的相互作用强度通常是不同的。本文提出了一种考虑过载边的加权复杂网络级联故障的新型非线性模型，以描述边的冗余容量并捕捉节点的相互作用强度。我们通过研究合成加权网络和实际加权网络上具有过载边的级联故障非线性加权模型来填补这一空白。首次根据过载系数、容量参数、权重系数和分布系数构建了级联故障模型。然后通过理论分析，得到了阻止故障级联的条件，分析表明了所构建模型的优越性。最后，在几个典型网络模型和美国电网中模拟了级联抗毁性。结果表明，该模型是可行且合理的，权重参数、容量系数、分布系数和过载系数的变化可以显著提高复杂网络对级联故障的破坏性。我们的方法为许多实际网络中级联故障的控制和预防提供了有效的参考。
