Percolation Theory on Interdependent Networks Based on Epidemic Spreading
Data Analysis, Statistics and Probability
2012-01-09 v1 Disordered Systems and Neural Networks
Abstract
We consider percolation on interdependent locally treelike networks, recently introduced by Buldyrev et al., Nature 464, 1025 (2010), and demonstrate that the problem can be simplified conceptually by deleting all references to cascades of failures. Such cascades do exist, but their explicit treatment just complicates the theory -- which is a straightforward extension of the usual epidemic spreading theory on a single network. Our method has the added benefits that it is directly formulated in terms of an order parameter and its modular structure can be easily extended to other problems, e.g. to any number of interdependent networks, or to networks with dependency links.
Cite
@article{arxiv.1109.4447,
title = {Percolation Theory on Interdependent Networks Based on Epidemic Spreading},
author = {Seung-Woo Son and Golnoosh Bizhani and Claire Christensen and Peter Grassberger and Maya Paczuski},
journal= {arXiv preprint arXiv:1109.4447},
year = {2012}
}
Comments
6 pages, 5 figures