Group percolation in interdependent networks

Abstract

In many real network systems, nodes usually cooperate with each other and form groups, in order to enhance their robustness to risks. This motivates us to study a new type of percolation, group percolation, in interdependent networks under attacks. In this model, nodes belonging to the same group survive or fail together. We develop a theoretical framework for this novel group percolation and find that the formation of groups can improve the resilience of interdependent networks significantly. However, the percolation transition is always of first order, regardless of the distribution of group sizes. As an application, we map the interdependent networks with inter-similarity structures, which attract many attentions very recently, onto the group percolation and confirm the non-existence of continuous phase transitions.

References in corpus (5)

• Mitigation of Malicious Attacks on Networks
• Avoiding catastrophic failure in correlated networks of networks
• Eradicating Catastrophic Collapse in Interdependent Networks via Reinforced Nodes
• Message passing theory for percolation models on multiplex networks with link overlap
• Geometric correlations mitigate the extreme vulnerability of multiplex networks against targeted attacks

Cited by in corpus (6)

• Percolation on complex networks: Theory and application
• Cascading Failures in Complex Networks
• Asymmetry in interdependence makes a multilayer system more robust against cascading failures
• Network Properties for Robust Multilayer Infrastructure Systems: A Percolation Theory Review
• Sustainable optimal transport in multilayer networks
• Enhancing photoelectric current by nonclassical light