Network resilience

Abstract

Many systems on our planet are known to shift abruptly and irreversibly from one state to another when they are forced across a "tipping point," such as mass extinctions in ecological networks, cascading failures in infrastructure systems, and social convention changes in human and animal networks. Such a regime shift demonstrates a system's resilience that characterizes the ability of a system to adjust its activity to retain its basic functionality in the face of internal disturbances or external environmental changes. In the past 50 years, attention was almost exclusively given to low dimensional systems and calibration of their resilience functions and indicators of early warning signals without considerations for the interactions between the components. Only in recent years, taking advantages of the network theory and lavish real data sets, network scientists have directed their interest to the real-world complex networked multidimensional systems and their resilience function and early warning indicators. This report is devoted to a comprehensive review of resilience function and regime shift of complex systems in different domains, such as ecology, biology, social systems and infrastructure. We cover the related research about empirical observations, experimental studies, mathematical modeling, and theoretical analysis. We also discuss some ambiguous definitions, such as robustness, resilience, and stability.

Review chapter

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Cited by in corpus (14)

• Robustness and resilience of complex networks
• A resilience glossary shaped by context: Reviewing resilience-related terms for critical infrastructures
• Early warning signals for critical transitions in complex systems
• Resilience of international oil trade networks under extreme event shock-recovery simulations
• Unveiling the Importance of Nonshortest Paths in Quantum Networks
• Predicting Long-term Dynamics of Complex Networks via Identifying Skeleton in Hyperbolic Space
• Reconstructing Sparse Multiplex Networks with Application to Covert Networks
• Efficient parameter inference in networked dynamical systems via steady states: A surrogate objective function approach integrating mean-field and nonlinear least squares
• Identifying Central Nodes in Multiplex Networks by Embracing Layer-Specific Heterogeneity via DomiRank
• Dimensional Reduction of Solvency Contagion Dynamics on Financial Networks
• Predicting the response of structurally altered and asymmetrical networks
• Reconstruction of the temporal correlation network of all-cause mortality fluctuation across Italian regions: the importance of temperature and among-nodes flux
• Locally Optimal Percolation for Network Resilience Dismantling via Fiedler Vector Gradient Iterative Attack
• Spatio-Temporal Graphical Counterfactuals: An Overview