Network Robustness and Fragility: Percolation on Random Graphs
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- 18 December 2000
- journal article
- research article
- Published by American Physical Society (APS) in Physical Review Letters
- Vol. 85 (25) , 5468-5471
- https://doi.org/10.1103/physrevlett.85.5468
Abstract
Recent work on the Internet, social networks, and the power grid has addressed the resilience of these networks to either random or targeted deletion of network nodes or links. Such deletions include, for example, the failure of Internet routers or power transmission lines. Percolation models on random graphs provide a simple representation of this process but have typically been limited to graphs with Poisson degree distribution at their vertices. Such graphs are quite unlike real-world networks, which often possess power-law or other highly skewed degree distributions. In this paper we study percolation on graphs with completely general degree distribution, giving exact solutions for a variety of cases, including site percolation, bond percolation, and models in which occupation probabilities depend on vertex degree. We discuss the application of our theory to the understanding of network resilience.Keywords
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This publication has 12 references indexed in Scilit:
- Resilience of the Internet to Random BreakdownsPhysical Review Letters, 2000
- Error and attack tolerance of complex networksNature, 2000
- Graph structure in the WebComputer Networks, 2000
- Scaling and percolation in the small-world network modelPhysical Review E, 1999
- Growth dynamics of the World-Wide WebNature, 1999
- Diameter of the World-Wide WebNature, 1999
- On power-law relationships of the Internet topologyACM SIGCOMM Computer Communication Review, 1999
- The Size of the Giant Component of a Random Graph with a Given Degree SequenceCombinatorics, Probability and Computing, 1998
- Epidemics with two levels of mixingThe Annals of Applied Probability, 1997
- A critical point for random graphs with a given degree sequenceRandom Structures & Algorithms, 1995