The robustness of interdependent clustered networks

Abstract

It was recently found that cascading failures can cause the abrupt breakdown of a system of interdependent networks. Using the percolation method developed for single clustered networks by Newman [Phys. Rev. Lett. {\bf 103}, 058701 (2009)], we develop an analytical method for studying how clustering within the networks of a system of interdependent networks affects the system's robustness. We find that clustering significantly increases the vulnerability of the system, which is represented by the increased value of the percolation threshold $p_c$ in interdependent networks.

6 pages, 6 figures

References in corpus (17)

• Catastrophic cascade of failures in interdependent networks
• Why social networks are different from other types of networks
• Interdependent networks: Reducing the coupling strength leads to a change from a first to second order percolation transition
• Network Physiology reveals relations between network topology and physiological function
• Robustness of a Network of Networks
• Robustness of interdependent networks under targeted attack
• Random graphs with clustering
• Cascade of failures in coupled network systems with multiple support-dependent relations
• The critical effect of dependency groups on the function of networks
• Assortativity Decreases the Robustness of Interdependent Networks
• Optimal Allocation of Interconnecting Links in Cyber-Physical Systems: Interdependence, Cascading Failures and Robustness
• Random graphs containing arbitrary distributions of subgraphs
• Clustering in complex networks. I. General formalism
• How clustering affects the bond percolation threshold in complex networks
• Cascades on a class of clustered random networks
• Bond percolation on a class of clustered random networks
• Networks with arbitrary edge multiplicities

Cited by in corpus (23)

• Multilayer Networks
• The structure and dynamics of multilayer networks
• The Kuramoto model in complex networks
• Percolation on complex networks: Theory and application
• Multilayer Networks in a Nutshell
• Effect of the Interconnected Network Structure on the Epidemic Threshold
• Percolation of a general network of networks
• Cascading Failures in Complex Networks
• The Impact of the Topology on Cascading Failures in Electric Power Grids
• Robustness of partially interdependent network formed of clustered networks
• Node-weighted interacting network measures improve the representation of real-world complex systems
• Clustering determines the dynamics of complex contagions in multiplex networks
• Multilayer Network Science: from Cells to Societies
• Asymmetry in interdependence makes a multilayer system more robust against cascading failures
• Cascading failures in coupled networks with both inner-dependency and inter-dependency links
• Cascades on clique-based graphs
• Network Properties for Robust Multilayer Infrastructure Systems: A Percolation Theory Review
• Spectra of random networks in the weak clustering regime
• Growing Self-organized Design of Efficient and Robust Complex Networks
• Self-avoiding walks and connective constants in clustered scale-free networks
• Effects of clustering heterogeneity on the spectral density of sparse networks
• Resilience of antagonistic networks with regard to the effects of initial failures and degree-degree correlations
• Hierarchy of percolation patterns in a kinetic replication model