Robustness of Cyber-Physical Supply Networks in Cascading Failures

Abstract

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.

Analysis on Cascading Failures of Directed–Undirected Interdependent Networks with Different Coupling Patterns

“…Mu et al [ 21 ] proposed a realistic cascading model of the cyber-physical supply network to construct an information—physical-supply interdependent network, considering that overload of the cyber-power network triggers cascading failures and underload of the physical power supply network triggers chain failures. Wang et al [ 22 ] proposed a high-level architecture (HLA)-based co-simulation method for critical infrastructure networks and established a case study of a dependent network consisting of two undirected subnets for two interdependent power and water systems. Tang et al [ 23 ] analyzed the robustness of a one-to-one complex interdependent supply chain network consisting of a directed physical layer network and an undirected network layer network and developed a priority load redistribution strategy when modeling the network.…”

Cyberphysical System Modeled with Complex Networks and Hybrid Automata to Diagnose Multiple and Concurrent Faults in Manufacturing Systems

“…The virtual digital and analog values from inputs and outputs are added. An analysis of the previous virtual state and the current digital virtual state is performed with Equation ( 15) for DId VS k and Equation (17) for DOd VS k . These input and output differences are assigned to DImVSk by ( 16) and DOmVSk by (18), respectively.…”

“…Adjacency matrices are constructed for the analysis of complex networks, which places correspondences to the connected nodes [14][15][16]. From the reading of sensors and the activation and deactivation of actuators of the physical system, information is saved in the adjacency matrix using arbitrary weights, corresponding to the space assigned by each sensor or actuator [17].…”