On the power-law random graph model of massive data networks

Hannu Reittu, Ilkka Norros (Corresponding Author)

Research output: Contribution to journalArticleScientificpeer-review

36 Citations (Scopus)

Abstract

Simplifying stochastic models of the topology of Internet have been studied intensively during the past few years. One of the most interesting ones is a random graph, where the degrees of the N nodes are drawn independently from a distribution with a Pareto tail with index τ∈(2,3) (finite mean and infinite variance), and the connections are then made randomly. We show that, asymptotically almost surely, the graph has a giant component, and the distance between two randomly selected nodes of the giant component is of the order log log N. This high connectivity is a consequence of the spontaneous emergence of a “core network” consisting of nodes with high degrees. Our result sheds light on the structure of the random graph model and raises interesting issues on its similarities and dissimilarities with the real Internet.
Original languageEnglish
Pages (from-to)3 - 23
Number of pages21
JournalPerformance Evaluation
Volume55
Issue number1-2
DOIs
Publication statusPublished - 2004
MoE publication typeA1 Journal article-refereed

Fingerprint

Graph Model
Random Graphs
Giant Component
Power Law
Internet
Stochastic models
Vertex of a graph
Infinite Variance
Topology
Dissimilarity
Pareto
Stochastic Model
Tail
Connectivity
Graph in graph theory

Keywords

  • power law
  • data networks
  • internet
  • stochastic models
  • random graph model

Cite this

Reittu, Hannu ; Norros, Ilkka. / On the power-law random graph model of massive data networks. In: Performance Evaluation. 2004 ; Vol. 55, No. 1-2. pp. 3 - 23.
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On the power-law random graph model of massive data networks. / Reittu, Hannu; Norros, Ilkka (Corresponding Author).

In: Performance Evaluation, Vol. 55, No. 1-2, 2004, p. 3 - 23.

Research output: Contribution to journalArticleScientificpeer-review

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