
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.
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Models, Statistical, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph)
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Models, Statistical, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph)
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