Clustering, or transitivity has been observed in real networks and its effects on their structure and function has been discussed extensively. The focus of these studies has been on clustering of single networks while the effect of clustering on the robustness of coupled networks received very little attention. Only the case of a pair of fully coupled networks with clustering has been studied recently. Here we generalize the study of clustering of a fully coupled pair of networks to the study of partially interdependent network of networks with clustering within the network components. We show both analytically and numerically, how clustering within the networks, affects the percolation properties of interdependent networks, including percolation threshold, size of giant component and critical coupling point where first order phase transition changes to second order phase transition as the coupling between the networks reduces. We study two types of clustering: one type proposed by Newman [25] where the average degree is kept constant while changing the clustering and the other proposed by Hackett et al. [38] where the degree distribution is kept constant. The first type of clustering is treated both analytically and numerically while the second one is treated only numerically.
Shao et al. REF applied a study on the clustering of two fully coupled networks and applied it to partially interdependent networks with clustering.
Robustness of partially interdependent network formed of clustered networks
Physics Medicine Mathematics