Recent advances on failure and recovery in networks of networks

• Published in: Chaos, solitons and fractals Vol. 90; pp. 28 - 36
• Main Authors: Shekhtman, Louis M., Danziger, Michael M., Havlin, Shlomo
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-09-2016
• Subjects: Complex matter and networks; Interdependent networks; Percolation Theory; 30.04; 30.03; Complex matter and networks; Interdependent networks; Percolation Theory
• ISSN: 0960-0779; 1873-2887
• DOI: 10.1016/j.chaos.2016.02.002

Until recently, network science has focused on the properties of single isolated networks that do not interact or depend on other networks. However it has now been recognized that many real-networks, such as power grids, transportation systems, and communication infrastructures interact and depend on other networks. Here, we will present a review of the framework developed in recent years for studying the vulnerability and recovery of networks composed of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes, like for example certain people, play a role in two networks, i.e. in a multiplex. Dependency relations may act recursively and can lead to cascades of failures concluding in sudden fragmentation of the system. We review the analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. The general theory and behavior of interdependent networks has many novel features that are not present in classical network theory. Interdependent networks embedded in space are significantly more vulnerable compared to non-embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences. Finally, when recovery of components is possible, global spontaneous recovery of the networks and hysteresis phenomena occur. The theory developed for this process points to an optimal repairing strategy for a network of networks. Understanding realistic effects present in networks of networks is required in order to move towards determining system vulnerability.