A threshold model of cascading failure on random hypergraphs

Liu, Run-Ran; Jia, Chun-Xiao; Li, Ming; Meng, Fanyuan

doi:10.1016/j.chaos.2023.113746

Cited by 12 publications

(1 citation statement)

References 41 publications

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“…The dynamics continues until no node changes its state. The threshold model has been extensively used to model information cascades on social networks 7 – 10 , contagion in financial networks 11 , 12 and cascading failures in different various networks, e.g., multilayer networks 13 , 14 and hypergraphs 15 . It was shown that the size of cascade depends on the size of the initially active nodes (seed size) 16 , 17 , the selection strategy of the initiators 10 and distribution of threshold values among nodes 18 .…”

Section: Introductionmentioning

confidence: 99%

Control of cascading failures using protective measures

Fazli,

Khanjanianpak,

Azimi-Tafreshi

2024

Sci Rep

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Cascading failures, triggered by a local perturbation, can be catastrophic and cause irreparable damages in a wide area. Hence, blocking the devastating cascades is an important issue in real world networks. One of the ways to control the cascade is to use protective me‌asures, so that the agents decide to be protected against failure. Here, we consider a coevolution of the linear threshold mo‌del for the spread of cascading failures and a decision-making game based on the perceived risk of failure. Protected agents are less vulnerable to failure and in return the size of the cascade affects the agent’s decision to get insured. We find at what range of protection efficiency and cost of failure, the global cascades stop. Also we observe that in some range of protection efficiency, a bistable region emerges for the size of cascade and the prevalence of protected agents. Moreover, we show how savings or the ability of agents to repair can prevent cascades from occurring.

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