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The exponential degree distribution in complex networks: Non-equilibrium network theory, numerical simulation and empirical data

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Listed:
  • Deng, Weibing
  • Li, Wei
  • Cai, Xu
  • Wang, Qiuping A.

Abstract

The exponential degree distribution has been found in many real world complex networks, based on which, the random growing process has been introduced to analyze the formation principle of such kinds of networks. Inspired from the non-equilibrium network theory, we construct the network according to two mechanisms: growing and adjacent random attachment. By using the Kolmogorov–Smirnov Test (KST), for the same number of nodes and edges, we find the simulation results are remarkably consistent with the predictions of the non-equilibrium network theory, and also surprisingly match the empirical databases, such as the Worldwide Marine Transportation Network (WMTN), the Email Network of University at Rovira i Virgili (ENURV) in Spain and the North American Power Grid Network (NAPGN). Our work may shed light on interpreting the exponential degree distribution and the evolution mechanism of the complex networks.

Suggested Citation

  • Deng, Weibing & Li, Wei & Cai, Xu & Wang, Qiuping A., 2011. "The exponential degree distribution in complex networks: Non-equilibrium network theory, numerical simulation and empirical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(8), pages 1481-1485.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:8:p:1481-1485
    DOI: 10.1016/j.physa.2010.12.029
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    References listed on IDEAS

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    1. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
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    Cited by:

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