Liu Chaoran, Li Daqing, Zio Enrico, Kang Rui
School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, China.
Chair on Systems Science and the Energetic challenge, European Foundation for New Energy-Electricite' de France, Ecole Centrale Paris and Supelec, Paris, France; Dipartimento di Energia, Politecnico di Milano, Milano, Italy.
PLoS One. 2014 Dec 4;9(12):e112363. doi: 10.1371/journal.pone.0112363. eCollection 2014.
System restoration from cascading failures is an integral part of the overall defense against catastrophic breakdown in networked critical infrastructures. From the outbreak of cascading failures to the system complete breakdown, actions can be taken to prevent failure propagation through the entire network. While most analysis efforts have been carried out before or after cascading failures, restoration during cascading failures has been rarely studied. In this paper, we present a modeling framework to investigate the effects of in-process restoration, which depends strongly on the timing and strength of the restoration actions. Furthermore, in the model we also consider additional disturbances to the system due to restoration actions themselves. We demonstrate that the effect of restoration is also influenced by the combination of system loading level and restoration disturbance. Our modeling framework will help to provide insights on practical restoration from cascading failures and guide improvements of reliability and resilience of actual network systems.
从级联故障中进行系统恢复是对网络化关键基础设施灾难性崩溃进行全面防御的一个组成部分。从级联故障爆发到系统完全崩溃，可以采取行动来防止故障在整个网络中传播。虽然大多数分析工作是在级联故障之前或之后进行的，但级联故障期间的恢复很少被研究。在本文中，我们提出了一个建模框架来研究过程中恢复的影响，这在很大程度上取决于恢复行动的时机和力度。此外，在模型中我们还考虑了恢复行动本身对系统造成的额外干扰。我们证明了恢复的效果也受到系统负载水平和恢复干扰组合的影响。我们的建模框架将有助于提供关于从级联故障中进行实际恢复的见解，并指导实际网络系统可靠性和恢复力的改进。
