@article{percolation2015hu,
author = "Yanqing Hu and Dong Zhou and Rui Zhang and Zhangang Han and C{\'e}line Rozenblat and Shlomo Havlin",
abstract = "Real data show that interdependent networks usually involve intersimilarity. Intersimilarity means that a pair of interdependent nodes have neighbors in both networks that are also interdependent [ Parshani et al. Europhys. Lett. 92 68002 (2010)]. For example, the coupled worldwide port network and the global airport network are intersimilar since many pairs of linked nodes (neighboring cities), by direct flights and direct shipping lines, exist in both networks. Nodes in both networks in the same city are regarded as interdependent. If two neighboring nodes in one network depend on neighboring nodes in the other network, we call these links common links. The fraction of common links in the system is a measure of intersimilarity. Previous simulation results of Parshani et al. suggest that intersimilarity has considerable effects on reducing the cascading failures; however, a theoretical understanding of this effect on the cascading process is currently missing. Here we map the cascading process with intersimilarity to a percolation of networks composed of components of common links and noncommon links. This transforms the percolation of intersimilar system to a regular percolation on a series of subnetworks, which can be solved analytically. We apply our analysis to the case where the network of common links is an Erdős-R{\'e}nyi (ER) network with the average degree K, and the two networks of noncommon links are also ER networks. We show for a fully coupled pair of ER networks, that for any K⩾0, although the cascade is reduced with increasing K, the phase transition is still discontinuous. Our analysis can be generalized to any kind of interdependent random network systems.",
doi = "10.1103/PhysRevE.88.052805",
issn = "15393755",
journal = "Physical Review E - Statistical, Nonlinear, and Soft Matter Physics",
number = "5",
pages = "1--7",
title = "{P}ercolation of interdependent networks with intersimilarity",
volume = "88",
year = "2013",
}