Attack resistance of power-law random graphs in the finite-mean, infinite-variance region

Illka Norros, Hannu Reittu

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)

Abstract

We consider a conditionally Poisson random-graph model in which the mean degrees, “capacities,” follow a power-tail distribution with finite mean and infinite variance. Such a graph of size N has a giant component that is supersmall in the sense that the typical distance between vertices is of order log log N. The shortest paths travel through a core consisting of nodes with high mean degrees. In this paper we derive upper bounds for the distance between two random vertices when an upper part of the core is removed, including the case that the whole core is removed.
Original languageEnglish
Pages (from-to)251-266
Number of pages16
JournalInternet Mathematics
Volume5
Issue number3
Publication statusPublished - 2008
MoE publication typeA1 Journal article-refereed

Fingerprint

Infinite Variance
Random Graphs
Power Law
Attack
Giant Component
Graph Model
Shortest path
Tail
Siméon Denis Poisson
Upper bound
Graph in graph theory
Vertex of a graph
Resistance

Cite this

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Attack resistance of power-law random graphs in the finite-mean, infinite-variance region. / Norros, Illka; Reittu, Hannu.

In: Internet Mathematics, Vol. 5, No. 3, 2008, p. 251-266.

Research output: Contribution to journalArticleScientificpeer-review

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