Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4947182 | Neurocomputing | 2017 | 14 Pages |
Abstract
In order to efficiently fortify the robustness of a scale-free network against cascading failure, a model of this phenomenon is proposed based on defining the load of a node with respect to both degree and betweenness centrality. Simultaneously, when the load is redistributed, an allocation proportion is ascertained according to both the loads and the energies of the nodes. After that, we obtain the relationship between the model parameters and the robustness of the network against the cascading failure with theoretical analysis, which also helps us determine the influence of the average network degree on cascading failure. Finally, the results of theoretical analysis are verified with simulation experiments.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hao-Ran Liu, Yan-Long Hu, Rong-Rong Yin, Yu-Jing Deng,