Random pseudofractal networks with competition

Lei Wang, Hua-ping Dai and You-xian Sun

Physica A: Statistical Mechanics and its Applications, 2007, vol. 383, issue 2, 763-772

Abstract: In this paper, we present a simple rule which assigns fitness to each edge to generate random pseudofractal networks (RPNs). This RPN model is both scale-free and small-world. We obtain the theoretical results that the power-law exponent is γ=2+1/(1+α) for the tunable parameter α>-1, and that the degree distribution is of an exponential form for others. Analytical results also show that an RPN has a large clustering coefficient and can process hierarchical structure as C(k)∼k-1 that is in accordance with many real networks. And we prove that the mean distance L(N) scales slower logarithmically with network size N. In particular, we explain the effect of nodes with degree 2 on the clustering coefficient. These results agree with numerical simulations very well.

Keywords: Growing networks; Scale-free feature; Small-world effect (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:383:y:2007:i:2:p:763-772

DOI: 10.1016/j.physa.2007.02.115

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