Cascading Failures in Interdependent Networks with Multiple Supply-Demand Links and Functionality Thresholds

Various social, financial, biological and technological systems can be modeled by interdependent networks. It has been assumed that in order to remain functional, nodes in one network must receive the support from nodes belonging to different networks. So far these models have been limited to the case in which the failure propagates across networks only if the nodes lose all their supply nodes. In this paper we develop a more realistic model for two interdependent networks in which each node has its own supply threshold, i.e., they need the support of a minimum number of supply nodes to remain functional. In addition, we analyze different conditions of internal node failure due to disconnection from nodes within its own network. We show that several local internal failure conditions lead to similar nontrivial results. When there are no internal failures the model is equivalent to a bipartite system, which can be useful to model a financial market. We explore the rich behaviors of these models that include discontinuous and continuous phase transitions. Using the generating functions formalism, we analytically solve all the models in the limit of infinitely large networks and find an excellent agreement with the stochastic simulations.

[1]  Wei Li,et al.  Cascading Failures in Interdependent Lattice Networks: The Critical Role of the Length of Dependency Links , 2012, Physical review letters.

[2]  D S Callaway,et al.  Network robustness and fragility: percolation on random graphs. , 2000, Physical review letters.

[3]  Chi Ho Yeung,et al.  Recovery of infrastructure networks after localised attacks , 2016, Scientific Reports.

[4]  H. Stanley,et al.  Networks formed from interdependent networks , 2011, Nature Physics.

[5]  Harry Eugene Stanley,et al.  Robustness of a Network of Networks , 2010, Physical review letters.

[6]  Sergey N. Dorogovtsev,et al.  Critical phenomena in complex networks , 2007, ArXiv.

[7]  L. D. Valdez,et al.  Triple point in correlated interdependent networks. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  Reuven Cohen,et al.  Spatio-temporal propagation of cascading overload failures in spatially embedded networks , 2016, Nature Communications.

[9]  James P. Gleeson,et al.  An analytical approach to cascades on random networks , 2007, SPIE International Symposium on Fluctuations and Noise.

[10]  Duncan J Watts,et al.  A simple model of global cascades on random networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Xiaoming Xu,et al.  Percolation of a general network of networks. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Junshan Zhang,et al.  Optimal Allocation of Interconnecting Links in Cyber-Physical Systems: Interdependence, Cascading Failures, and Robustness , 2012, IEEE Transactions on Parallel and Distributed Systems.

[13]  Cesar Ducruet,et al.  Inter-similarity between coupled networks , 2010, ArXiv.

[14]  L. D. Valdez,et al.  A triple point induced by targeted autonomization on interdependent scale-free networks , 2013, 1310.6345.

[15]  Harry Eugene Stanley,et al.  Robustness of interdependent networks under targeted attack , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Harry Eugene Stanley,et al.  Robustness of onion-like correlated networks against targeted attacks , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  S. Havlin,et al.  Interdependent networks: reducing the coupling strength leads to a change from a first to second order percolation transition. , 2010, Physical review letters.

[18]  Dror Y. Kenett,et al.  Networks of networks – An introduction , 2015 .

[19]  B. M. Fulk MATH , 1992 .

[20]  S. Havlin,et al.  Robustness of a network formed by n interdependent networks with a one-to-one correspondence of dependent nodes. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[21]  Harry Eugene Stanley,et al.  $k$-core percolation on complex networks: Comparing random, localized and targeted attacks , 2016, Physical review. E.

[22]  S. Buldyrev,et al.  Interdependent networks with identical degrees of mutually dependent nodes. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  H E Stanley,et al.  Recovery of Interdependent Networks , 2015, Scientific Reports.

[24]  Harry Eugene Stanley,et al.  Catastrophic cascade of failures in interdependent networks , 2009, Nature.

[25]  M. Newman,et al.  Random graphs with arbitrary degree distributions and their applications. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  S. N. Dorogovtsev,et al.  Evolution of networks , 2001, cond-mat/0106144.

[27]  Harry Eugene Stanley,et al.  Cascade of failures in coupled network systems with multiple support-dependent relations , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  S. N. Dorogovtsev,et al.  Bootstrap percolation on complex networks. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  Hans J. Herrmann,et al.  Towards designing robust coupled networks , 2011, Scientific Reports.

[30]  James P. Peerenboom,et al.  Identifying, understanding, and analyzing critical infrastructure interdependencies , 2001 .

[31]  Ernesto Estrada,et al.  The Structure of Complex Networks: Theory and Applications , 2011 .

[32]  Vittorio Rosato,et al.  Modelling interdependent infrastructures using interacting dynamical models , 2008, Int. J. Crit. Infrastructures.

[33]  Lin Wang,et al.  Evolutionary games on multilayer networks: a colloquium , 2015, The European Physical Journal B.

[34]  S. Havlin,et al.  The extreme vulnerability of interdependent spatially embedded networks , 2012, Nature Physics.

[35]  S. N. Dorogovtsev,et al.  Multiple percolation transitions in a configuration model of a network of networks. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[36]  S. N. Dorogovtsev,et al.  Avalanche collapse of interdependent networks. , 2012, Physical review letters.

[37]  S N Dorogovtsev,et al.  Heterogeneous k-core versus bootstrap percolation on complex networks. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  H E Stanley,et al.  Cascading failures in interdependent networks with finite functional components. , 2016, Physical review. E.

[39]  H. Stanley,et al.  Robustness of network of networks under targeted attack. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  Aonghus Lawlor,et al.  Critical phenomena in heterogeneous k-core percolation. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[41]  Peter Grassberger,et al.  Percolation theory on interdependent networks based on epidemic spreading , 2011, 1109.4447.

[42]  Bruce A. Reed,et al.  A Critical Point for Random Graphs with a Given Degree Sequence , 1995, Random Struct. Algorithms.