Spatio-temporal propagation of cascading overload failures in spatially embedded networks

Jichang Zhao, Daqing Li, Hillel Sanhedrai, Reuven Cohen, Shlomo Havlin

Research output: Contribution to journalArticlepeer-review

117 Scopus citations

Abstract

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.

Original languageEnglish
Article number10094
JournalNature Communications
Volume7
DOIs
StatePublished - 12 Jan 2016

Bibliographical note

Funding Information:
We thank the support from Collaborative Innovation Center for industrial Cyber-Physical System. D.L. is also supported by the National Natural Science Foundation of China (Grant 61104144) and the National Basic Research Program of China (2012CB725404). S.H. thanks DTRA, ONR, the LINC and the Multiplex (No. 317532) EU projects, the DFG, and the Israel Science Foundation for support. J.Z. was partially supported by NSFC (Grant Nos 71501005 and 71531001) and 863 Program (Grant No. SS2014AA012303).

Funding

We thank the support from Collaborative Innovation Center for industrial Cyber-Physical System. D.L. is also supported by the National Natural Science Foundation of China (Grant 61104144) and the National Basic Research Program of China (2012CB725404). S.H. thanks DTRA, ONR, the LINC and the Multiplex (No. 317532) EU projects, the DFG, and the Israel Science Foundation for support. J.Z. was partially supported by NSFC (Grant Nos 71501005 and 71531001) and 863 Program (Grant No. SS2014AA012303).

FundersFunder number
LINC317532
Office of Naval Research
National Institute on Alcohol Abuse and AlcoholismR37AA012303
Defense Threat Reduction Agency
Deutsche Forschungsgemeinschaft
National Natural Science Foundation of China71531001, 71501005, 61104144
Israel Science Foundation
National High-tech Research and Development ProgramSS2014AA012303
National Key Research and Development Program of China2012CB725404

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