Robustness of a partially interdependent network formed of clustered networks

Shuai Shao, Xuqing Huang, H. Eugene Stanley, Shlomo Havlin

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

Abstract

Clustering, or transitivity, a behavior observed in real-world networks, affects network structure and function. This property has been studied extensively, but most of this research has been limited to clustering in single networks. The effect of clustering on the robustness of coupled networks, on the other hand, has received much less attention. Only the case of a pair of fully coupled networks with clustering has recently received study. Here we generalize the study of clustering of a fully coupled pair of networks and apply it to a partially interdependent network of networks with clustering within the network components. We show, both analytically and numerically, how clustering within networks affects the percolation properties of interdependent networks, including the percolation threshold, the size of the giant component, and the critical coupling point at which the first-order phase transition changes to a second-order phase transition as the coupling between the networks is reduced. We study two types of clustering, one proposed by Newman [Phys. Rev. Lett. 103, 058701 (2009)PRLTAO0031-900710.1103/PhysRevLett.103.058701] in which the average degree is kept constant while the clustering is changed, and the other by Hackett et al. [Phys. Rev. E 83, 056107 (2011)PLEEE81539-375510.1103/PhysRevE. 83.056107] in which the degree distribution is kept constant. The first type of clustering is studied both analytically and numerically, and the second is studied numerically.

Original languageEnglish
Article number032812
JournalPhysical Review E
Volume89
Issue number3
DOIs
StatePublished - 25 Mar 2014

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