Operational resilience: concepts, design and analysis

Abstract

Building resilience into today’s complex infrastructures is critical to the daily functioning of society and its ability to withstand and recover from natural disasters, epidemics, and cyber-threats. This study proposes quantitative measures that capture and implement the definition of engineering resilience advanced by the National Academy of Sciences. The approach is applicable across physical, information, and social domains. It evaluates the critical functionality, defined as a performance function of time set by the stakeholders. Critical functionality is a source of valuable information, such as the integrated system resilience over a time interval, and its robustness. The paper demonstrates the formulation on two classes of models: 1) multi-level directed acyclic graphs, and 2) interdependent coupled networks. For both models synthetic case studies are used to explore trends. For the first class, the approach is also applied to the Linux operating system. Results indicate that desired resilience and robustness levels are achievable by trading off different design parameters, such as redundancy, node recovery time, and backup supply available. The nonlinear relationship between network parameters and resilience levels confirms the utility of the proposed approach, which is of benefit to analysts and designers of complex systems and networks.

Stability of a giant connected component in a complex network

“…There is a growing body of work in largescale optimization and game theory that leverages the specialized structure of these networks to discover specific vulnerabilities and to identify limited defensive investments that can maximally increase robustness and resilience (e.g., Ref. [4,25]). Bridging the gap between the specific recommendations of these highly detailed models and the insights from more general models described here is an important goal for ongoing research.…”

“…Rather, the location of the functional component within the network itself is important. It is especially true in the case of resilience where critical system function and its recovery is of prime importance [4,5]. For example, in the case of a major natural disaster, such as flood or an earthquake, one needs to know infrastructure units and transportation routes that are likely to remain functional.…”

Avoiding Decline: Fostering Resilience and Sustainability in Midsize Cities

“…Several frameworks have been proposed for conducting resilience assessments [16,40], yet the applicability of these techniques for midsize cities is underdeveloped [41,42]. Here we build on existing approaches [16,[40][41][42], using established social-ecological properties [13] to estimate the relative resilience of two midsize cities in the Midwestern region of the United States.…”

“…This approach allows for visualization of multiple, integrated variables (each axis represents multiple variables) but does not provide a single overall measure of resilience. That type of metric can be derived using tools of Multi-Criteria Decision Analysis (see [14,15]) or Network Science techniques [16].…”

A Comprehensive Technological Survey on Dependable Self-Managing CPS: The Decade of Researches on Correctness and Dependability

“…To overcome the incomparable of the dual conjunctive scheme, a method is developed for verifying Ninference diagnosability [205]. To evaluate the ability of withstanding and recovering from irresistible catastrophic, Alexander A. G introduced the concept of resilience and present two classes of formal models, which are multi-level directed acyclic graphs and interdependent coupled networks [206]. To formalize and assess the reconfigurable CPS, Linas L et al formally defined the dynamic system architecture in Event-B, and verified the correctness based on derived model.…”