Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks

Scientific paper - Original scientific paper

• Author: Boris Podobnik
• Author: Tomislav Lipić
• Author: Davor Horvatić
• Author: Antonio Majdandžić
• Author: Steven R. Bishop
• Author: H. Eugene Stanley
• Author's institution: University 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... More 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. Less

• Keywords (english): complex networks; phase transitions; critical phenomena
• Language: english
• Publication type: Scientific paper - Original scientific paper
• Publication status: Published
• Peer review: Peer review - international
• Publication version: Published version
• Journal title: Scientific Reports
• Numbering: vol. 5, 14286
• e-ISSN: 2045-2322
• DOI: https://doi.org/10.1038/srep14286
• URN:NBN: urn:nbn:hr:217:081879
• Publication: 2015
• Document URL: https://www.nature.com/articles/srep14286
• Type of resource: Text
• Access conditions: Open access
• Public note: This 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 on: 2020-01-18 18:57:02