Pregled bibliografske jedinice broj: 789096
Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks
Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks // Scientific Reports, 5 (2015), 14286; 14286-1 doi:10.1038/srep14286 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 789096 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks
Autori
Podobnik, Boris ; Lipić, Tomislav ; Horvatić, Davor ; Majdandzic, Antonio ; Bishop, Steven R. ; Stanley, H. Eugene
Izvornik
Scientific Reports (2045-2322) 5
(2015), 14286;
14286-1
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
complex networks; phase transitions; critical phenomena
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Fizika, Računarstvo
POVEZANOST RADA
Ustanove:
Institut "Ruđer Bošković", Zagreb,
Građevinski fakultet, Rijeka,
Prirodoslovno-matematički fakultet, Zagreb,
Zagrebačka škola ekonomije i managementa, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE
Uključenost u ostale bibliografske baze podataka::
- MEDLINE