Cascaded failures in weighted networks

Baharan Mirzasoleiman, Mahmoudreza Babaei, Mahdi Jalili, and MohammadAli Safari
Phys. Rev. E 84, 046114 – Published 25 October 2011

Abstract

Many technological networks can experience random and/or systematic failures in their components. More destructive situations can happen if the components have limited capacity, where the failure in one of them might lead to a cascade of failures in other components, and consequently break down the structure of the network. In this paper, the tolerance of cascaded failures was investigated in weighted networks. Three weighting strategies were considered including the betweenness centrality of the edges, the product of the degrees of the end nodes, and the product of their betweenness centralities. Then, the effect of the cascaded attack was investigated by considering the local weighted flow redistribution rule. The capacity of the edges was considered to be proportional to their initial weight distribution. The size of the survived part of the attacked network was determined in model networks as well as in a number of real-world networks including the power grid, the internet in the level of autonomous system, the railway network of Europe, and the United States airports network. We found that the networks in which the weight of each edge is the multiplication of the betweenness centrality of the end nodes had the best robustness against cascaded failures. In other words, the case where the load of the links is considered to be the product of the betweenness centrality of the end nodes is favored for the robustness of the network against cascaded failures.

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  • Received 14 August 2011

DOI:https://doi.org/10.1103/PhysRevE.84.046114

©2011 American Physical Society

Authors & Affiliations

Baharan Mirzasoleiman, Mahmoudreza Babaei, Mahdi Jalili*, and MohammadAli Safari

  • Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

  • *Corresponding author: mjalili@sharif.edu

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Issue

Vol. 84, Iss. 4 — October 2011

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