scholarly journals Nonlocal effects and countermeasures in cascading failures

2015 ◽  
Vol 92 (3) ◽  
Author(s):  
Dirk Witthaut ◽  
Marc Timme
2000 ◽  
Vol 62 (13) ◽  
pp. 9077-9082 ◽  
Author(s):  
V. G. Kogan ◽  
S. L. Bud’ko ◽  
I. R. Fisher ◽  
P. C. Canfield
Keyword(s):  

2021 ◽  
Vol 126 (22) ◽  
Author(s):  
Hugo Perrin ◽  
Matthieu Wyart ◽  
Bloen Metzger ◽  
Yoël Forterre

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Muhammad Adnan ◽  
Muhammad Gufran Khan ◽  
Arslan Ahmed Amin ◽  
Muhammad Rayyan Fazal ◽  
Wen Shan Tan ◽  
...  

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Sandip Mandal ◽  
Maxime Nicolas ◽  
Olivier Pouliquen

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 769
Author(s):  
Dong Mu ◽  
Xiongping Yue ◽  
Huanyu Ren

A cyber-physical supply network is composed of an undirected cyber supply network and a directed physical supply network. Such interdependence among firms increases efficiency but creates more vulnerabilities. The adverse effects of any failure can be amplified and propagated throughout the network. This paper aimed at investigating the robustness of the cyber-physical supply network against cascading failures. Considering that the cascading failure is triggered by overloading in the cyber supply network and is provoked by underload in the physical supply network, a realistic cascading model for cyber-physical supply networks is proposed. We conducted a numerical simulation under cyber node and physical node failure with varying parameters. The simulation results demonstrated that there are critical thresholds for both firm’s capacities, which can determine whether capacity expansion is helpful; there is also a cascade window for network load distribution, which can determine the cascading failures occurrence and scale. Our work may be beneficial for developing cascade control and defense strategies in cyber-physical supply networks.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Malgorzata Turalska ◽  
Ananthram Swami

AbstractComplex systems are challenging to control because the system responds to the controller in a nonlinear fashion, often incorporating feedback mechanisms. Interdependence of systems poses additional difficulties, as cross-system connections enable malicious activity to spread between layers, increasing systemic risk. In this paper we explore the conditions for an optimal control of cascading failures in a system of interdependent networks. Specifically, we study the Bak–Tang–Wiesenfeld sandpile model incorporating a control mechanism, which affects the frequency of cascades occurring in individual layers. This modification allows us to explore sandpile-like dynamics near the critical state, with supercritical region corresponding to infrequent large cascades and subcritical zone being characterized by frequent small avalanches. Topological coupling between networks introduces dependence of control settings adopted in respective layers, causing the control strategy of a given layer to be influenced by choices made in other connected networks. We find that the optimal control strategy for a layer operating in a supercritical regime is to be coupled to a layer operating in a subcritical zone, since such condition corresponds to reduced probability of inflicted avalanches. However this condition describes a parasitic relation, in which only one layer benefits. Second optimal configuration is a mutualistic one, where both layers adopt the same control strategy. Our results provide valuable insights into dynamics of cascading failures and and its control in interdependent complex systems.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. M. de Oliveira ◽  
Samuraí Brito ◽  
L. R. da Silva ◽  
Constantino Tsallis

AbstractBoltzmann–Gibbs statistical mechanics applies satisfactorily to a plethora of systems. It fails however for complex systems generically involving nonlocal space–time entanglement. Its generalization based on nonadditive q-entropies adequately handles a wide class of such systems. We show here that scale-invariant networks belong to this class. We numerically study a d-dimensional geographically located network with weighted links and exhibit its ‘energy’ distribution per site at its quasi-stationary state. Our results strongly suggest a correspondence between the random geometric problem and a class of thermal problems within the generalised thermostatistics. The Boltzmann–Gibbs exponential factor is generically substituted by its q-generalisation, and is recovered in the $$q=1$$ q = 1 limit when the nonlocal effects fade away. The present connection should cross-fertilise experiments in both research areas.


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