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Scientific paper - Original scientific paper
Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks
Scientific Reports, 5 (2015); 14286. https://doi.org/10.1038/srep14286
Podobnik, Boris; Lipić, Tomislav; Horvatić, Davor; Majdandžić, Antonio; Bishop, Steven R.; Stanley, H. Eugene

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Podobnik, B., Lipić, T., Horvatić, D., Majdandžić, A., Bishop, S. R. & Stanley, H. E. (2015). Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks. Scientific Reports, 5.. doi: 10.1038/srep14286

Podobnik, Boris, et al. "Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks." Scientific Reports, vol. 5, 2015. https://doi.org/10.1038/srep14286

Podobnik, Boris, Tomislav Lipić, Davor Horvatić, Antonio Majdandžić, Steven R. Bishop and H. Eugene Stanley. "Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks." Scientific Reports 5 (2015). https://doi.org/10.1038/srep14286

Podobnik, B., et al. (2015) 'Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks', Scientific Reports, 5. doi: 10.1038/srep14286

Podobnik B, Lipić T, Horvatić D, Majdandžić A, Bishop SR, Stanley HE. Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks. Scientific Reports [Internet]. 2015 [cited 2024 May 28];5. doi: 10.1038/srep14286

B. Podobnik, T. Lipić, D. Horvatić, A. Majdandžić, S. R. Bishop and H. E. Stanley, "Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks", Scientific Reports, vol. 5, 2015. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:217:081879. [Accessed: 28 May 2024]

Metadata
Title (english)Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks
AuthorBoris Podobnik
AuthorTomislav Lipić
AuthorDavor Horvatić
AuthorAntonio Majdandžić
AuthorSteven R. Bishop
AuthorH. Eugene Stanley
Author's institutionUniversity of Zagreb
Faculty of Science
(Department of Physics)
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Physics
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract (english)
Estimating the critical points at which complex systems abruptly flip from one state to another is one of the remaining challenges in network science. Due to lack of knowledge about the underlying stochastic processes controlling critical transitions, it is widely considered difficult to determine the location of critical points for real-world networks, and it is even more difficult to predict the time at which these potentially catastrophic failures occur. We analyse a class of decaying dynamic networks experiencing persistent failures in which the magnitude of the overall failure is quantified by the probability that a potentially permanent internal failure will occur. When the fraction of active neighbours is reduced to a critical threshold, cascading failures can trigger a total network failure. For this class of network we find that the time to network failure, which is equivalent to network lifetime, is inversely dependent upon the magnitude of the failure and logarithmically dependent on the threshold. We analyse how permanent failures affect network robustness using network lifetime as a measure. These findings provide new methodological insight into system dynamics and, in particular, of the dynamic processes of networks. We illustrate the network model by selected examples from biology, and social science.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleScientific Reports
Numberingvol. 5, 14286
e-ISSN2045-2322
DOIhttps://doi.org/10.1038/srep14286
URN:NBNurn:nbn:hr:217:081879
Publication2015
Document URLhttps://www.nature.com/articles/srep14286
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Public noteThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0. Received: 10 February 2015. Accepted: 11 August 2015. Published online: 21 September 2015.
Created on2020-01-18 18:57:02