Degree distributions of evolving networks

D. SHI, Liming LIU, S. X. ZHU, H. ZHOU

Research output: Journal PublicationsJournal Article (refereed)Researchpeer-review

25 Citations (Scopus)

Abstract

In this paper, we propose a simple evolving network model with link and node removals as well as additions and show that this evolving network is scale free with a degree exponent varying in (1,4] depending on the network parameter values. By establishing a relation between the network evolution and a set of non-homogeneous birth-and-death processes, we develop an efficient algorithm to compute the network degree distribution. Our numerical results match simulation well and show how the network evolves into the scale-free state.
Original languageEnglish
Pages (from-to)731-737
Number of pages7
JournalEurophysics Letters
Volume76
Issue number4
DOIs
Publication statusPublished - 1 Jan 2006
Externally publishedYes

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SHI, D. ; LIU, Liming ; ZHU, S. X. ; ZHOU, H. / Degree distributions of evolving networks. In: Europhysics Letters. 2006 ; Vol. 76, No. 4. pp. 731-737.
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Degree distributions of evolving networks. / SHI, D.; LIU, Liming; ZHU, S. X.; ZHOU, H.

In: Europhysics Letters, Vol. 76, No. 4, 01.01.2006, p. 731-737.

Research output: Journal PublicationsJournal Article (refereed)Researchpeer-review

TY - JOUR

T1 - Degree distributions of evolving networks

AU - SHI, D.

AU - LIU, Liming

AU - ZHU, S. X.

AU - ZHOU, H.

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N2 - In this paper, we propose a simple evolving network model with link and node removals as well as additions and show that this evolving network is scale free with a degree exponent varying in (1,4] depending on the network parameter values. By establishing a relation between the network evolution and a set of non-homogeneous birth-and-death processes, we develop an efficient algorithm to compute the network degree distribution. Our numerical results match simulation well and show how the network evolves into the scale-free state.

AB - In this paper, we propose a simple evolving network model with link and node removals as well as additions and show that this evolving network is scale free with a degree exponent varying in (1,4] depending on the network parameter values. By establishing a relation between the network evolution and a set of non-homogeneous birth-and-death processes, we develop an efficient algorithm to compute the network degree distribution. Our numerical results match simulation well and show how the network evolves into the scale-free state.

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