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The robustness of interdependent weighted networks

  • Fan Wang
  • , Lixin Tian
  • , Ruijin Du
  • , Gaogao Dong
  • Jiangsu University
  • Nanjing Normal University

Research output: Contribution to journal › Article › peer-review

31 Scopus citations

Abstract

We analysis the cascading failure of interdependent weighted networks based on percolation theory and local weighted flow redistribution rule. The weight of a node is Bi θ, where Bi is the betweenness of the node. We assume that the two networks A and B of size NA andNB are BA networks, and suppose two different one-to-one interdependent network, one is random, the other based on nodes’ betweenness. Assume that a failed node in network A leads to a redistribution of the flow passing through it to its neighboring nodes and the interdependent node in network B also to be disabled, where the two failure factors happen concurrently, or successively. We find that the one-to-one random interdependent weighted complex network reaches the strongest robustness level when the weight parameter θ =0.5, no matter cascading failure caused by two failure factors happen concurrently, or successively. And when the interdependent relationship based on nodes’ betweenness, θ=0.7 to get the strongest robustness level.

Original languageEnglish
Pages (from-to)675-680
Number of pages6
JournalPhysica A: Statistical Mechanics and its Applications
Volume508
DOIs
StatePublished - 15 Oct 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018

Keywords

  • Cascading failure
  • Percolation theory
  • Redistribution rule

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