Cascading failures in multiplex network under flow redistribution

Pei, Jianxin; Liu, Ying; Wang, Wei; Gong, Jianya

doi:10.1016/j.physa.2021.126340

Cited by 9 publications

(3 citation statements)

References 33 publications

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“…Resilience [14] generally refers to the ability of the system to return to a normal state after fault, which includes not only the fault stage but also the recovery stage. The previous evaluation indicators of key nodes mainly focus on the cascading failures [15][16][17][18] of nodes in the network, that is, which failed node will affect more nodes in the network. On the other hand, during the recovery stage, the failed nodes are repaired.…”

Section: Introductionmentioning

confidence: 99%

Key Repairing Node Identification in Double-Layer Logistic Networks

et al. 2022

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As important infrastructure, logistic networks need to be designed not only for robustness but also for transportation efficiency. In order to improve transportation efficiency, different types of logistic networks integrate to form a double-layer coupled network. When some nodes fail in this double-layer coupled network, especially in the case of limited repair resources, how to evaluate the node that needs to give priority to repair is of great significance. In this study, an evaluation method of key repairing node is proposed to find the key node which should be repaired first to restore the network performance. By comparing with traditional evaluation methods of key nodes, the effectiveness of the proposed method is verified.

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Section: Introductionmentioning

confidence: 99%

Key Repairing Node Identification in Double-Layer Logistic Networks

et al. 2022

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“…Cascading failures on the RN and PN mainly focus on a single system, and a few studies concern the interdependence between them. Interdependent network is a useful tool to characterize the complex interactions among infrastructures [13]- [16]. Primary studies of cascading failures on the interdependent network can be classified into two types: (1) Analyze the influence of different topological structures on the network vulnerability, which includes the dependent pattern [17] (e.g., partial interdependence [18], weak interdependence [8]), and the network type (e.g., Erdos-Renyi (ER) network, Barabasi-Albert (BA) scale-free network).…”

Section: Introductionmentioning

confidence: 99%

“…( 2) Study the overload behavior and construct the flow redistribution mechanism. Pei et al [13] proposed a new flow redistribution model with overlapping edges in multiplex networks. Wang et al [9] investigated the effect of the load redistribution mechanism on network robustness and obtained the optimal values of the parameters that enable the network to achieve the best robust level through testing.…”

Section: Introductionmentioning

confidence: 99%

Vulnerability Assessment of Interdependent Infrastructures Based on a Cascading Failure Model

Wang

Guo

et al. 2022

2022 6th International Conference on System Reliability and Safety (ICSRS)

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Road and power systems are the backbone of a city. With rapid urbanization, the two facilities are highly interconnected. The vulnerability of the Interdependent Road-Power Systems (IRPS) can cause large-scale failures and even catastrophic disasters with severe social and economic consequences. In this paper, the IRPS is composed of nodes, edges, and links between layers. Distance between junction nodes with traffic lights in the Road Network (RN) and power stations in the Power Network (PN) is used to construct the functional interdependence. A non-linear load-capacity model is proposed to describe the capacity and ability of IRPS to handle allocated loads. Considering the current ability of neighbor nodes, we propose an intelligent node loads redistribution rule. The vulnerability level of RN, PN, and IRPS are measured, respectively. A case study based on real road data in Xi'an, China is conducted to validate the model. Results show that: (1) The redistribution rule is an important tool to decrease the vulnerability of the RN, while the capacity tolerance degree is more influential for the PN. (2) Parameters for the global vulnerability, there is a cross-impact between the capacity tolerance parameters.

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