Controlling the uncertain response of real multiplex networks to random damage

Abstract

We reveal large fluctuations in the response of real multiplex networks to random damage of nodes. These results indicate that the average response to random damage, traditionally considered in mean-field approaches to percolation, is a poor metric of system robustness. We show instead that a large deviation approach to percolation provides a more accurate characterization of system robustness. We identify an effective percolation threshold at which we observe a clear abrupt transition separating two distinct regimes in which the most likely response to damage is either a functional or a dismantled multiplex network. We leverage our findings to propose a new metric, named safeguard centrality, able to single out the nodes that control the response of the entire multiplex network to random damage. We show that safeguarding the function of top-scoring nodes is sufficient to prevent system collapse.

arXiv comment(12 pages, 9 figures and Supplementary Information)

References in corpus (35)

• Catastrophic cascade of failures in interdependent networks
• The structure and dynamics of multilayer networks
• Critical phenomena in complex networks
• Influence maximization in complex networks through optimal percolation
• Interdependent networks: Reducing the coupling strength leads to a change from a first to second order percolation transition
• k-core organization of complex networks
• Explosive Synchronization Transitions in Scale-free Networks
• Avalanche Collapse of Interdependent Network
• Statistical Mechanics of Multiplex Ensembles: Entropy and Overlap
• Abrupt transition in the structural formation of interconnected networks
• Inter-similarity between coupled networks
• Percolation on sparse networks
• Network dismantling
• Avoiding catastrophic failure in correlated networks of networks
• Network robustness of multiplex networks with interlayer degree correlations
• Percolation Theory on Interdependent Networks Based on Epidemic Spreading
• Percolation in Multiplex Networks with Overlap
• Percolation in real interdependent networks
• Multiple percolation transitions in a configuration model of network of networks
• Collective phenomena emerging from the interactions between dynamical processes in multiplex networks
• Explosive Percolation: Novel critical and supercritical phenomena
• Towards real-world complexity: an introduction to multiplex networks
• Redundant interdependencies boost the robustness of multilayer networks
• Message passing theory for percolation models on multiplex networks with link overlap
• Optimal percolation on multiplex networks
• Link overlap, viability, and mutual percolation in multiplex networks
• Correlated Edge Overlaps in Multiplex Networks
• Hybrid Phase Transition into an Absorbing State: Percolation and Avalanches
• Stability of a Giant Connected Component in a Complex Network
• Mutually connected component of network of networks with replica nodes
• Rare events and discontinuous percolation transitions
• Fluctuations in percolation of sparse complex networks
• Percolation in real multiplex networks
• Targeted Damage to Interdependent Networks
• On $k$-Core Percolation in Four Dimensions

Cited by in corpus (14)

• Percolation on complex networks: Theory and application
• Cascading Failures in Complex Networks
• Large deviation theory of percolation on multiplex networks
• Identifying vital nodes by Achlioptas process
• Large deviations of random walks on random graphs
• Smeared phase transitions in percolation on real complex networks
• Optimal percolation in correlated multilayer networks with overlap
• Spreading of localized attacks on spatial multiplex networks with a community structure
• Deep-learning-aided dismantling of interdependent networks
• Delocalization-localization dynamical phase transition of random walks on graphs
• Dynamical fluctuations of random walks in higher-order networks
• Fragility and anomalous susceptibility of weakly interacting networks
• Maximal dispersion of adaptive random walks
• Heterogeneity in Outcomes of Repeated Instances of Percolation Experiments