Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks.

ABSTRACT: 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 networ

SUBMITTER: Podobnik B 

PROVIDER: S-EPMC4585692 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature