English

Cavity-based robustness analysis of interdependent networks: Influences of intranetwork and internetwork degree-degree correlations

Disordered Systems and Neural Networks 2014-02-11 v2 Statistical Mechanics

Abstract

We develop a methodology for analyzing the percolation phenomena of two mutually coupled (interdependent) networks based on the cavity method of statistical mechanics. In particular, we take into account the influence of degree-degree correlations inside and between the networks on the network robustness against targeted attacks and random failures. We show that the developed methodology is reduced to the well-known generating function formalism in the absence of degree-degree correlations. The validity of the developed methodology is confirmed by a comparison with the results of numerical experiments. Our analytical results imply that the robustness of the interdependent networks depends considerably on both the intra- and internetwork degree-degree correlations in the case of targeted attacks, whereas the significance of the degree-degree correlations is relatively low for random failures.

Keywords

Cite

@article{arxiv.1308.1210,
  title  = {Cavity-based robustness analysis of interdependent networks: Influences of intranetwork and internetwork degree-degree correlations},
  author = {Shunsuke Watanabe and Yoshiyuki Kabashima},
  journal= {arXiv preprint arXiv:1308.1210},
  year   = {2014}
}

Comments

12 pages, 6 figures