A High Robustness and Low Cost Model for Cascading Failures

Abstract

We study numerically the cascading failure problem by using artificially created scale-free networks and the real network structure of the power grid. The capacity for a vertex is assigned as a monotonically increasing function of the load (or the betweenness centrality). Through the use of a simple functional form with two free parameters, revealed is that it is indeed possible to make networks more robust while spending less cost. We suggest that our method to prevent cascade by protecting less vertices is particularly important for the design of more robust real-world networks to cascading failures.

5 pages, 5 figures, accepted by EPL

References in corpus (4)

• Cascade control and defense in complex networks
• Modeling Cascading Failures in the North American Power Grid
• Entropy Optimization of Scale-Free Networks Robustness to Random Failures
• Optimization of network structure to random failures

Cited by in corpus (7)

• A limited resource model of fault-tolerant capability against cascading failure of complex network
• Fluctuation-driven capacity distribution in complex networks
• Network Overload due to Massive Attacks
• Neighborhood Information-based Probabilistic Algorithm for Network Disintegration
• Protecting infrastructure networks from cost-based attacks
• Prediction and mitigation of nonlocal cascading failures using graph neural networks
• Integrating fluctuations into distribution of resources in transportation networks