English

Deterministic weighted scale-free small-world networks

Statistical Mechanics 2011-02-03 v2 Disordered Systems and Neural Networks Physics and Society

Abstract

We propose a deterministic weighted scale-free small-world model for considering pseudofractal web with the coevolution of topology and weight. In the model, we have the degree distribution exponent γ\gamma restricted to a range between 2 and 3, simultaneously tunable with two parameters. At the same time, we provide a relatively complete view of topological structure and weight dynamics characteristics of the networks: weight and strength distribution; degree correlations; average clustering coefficient and degree-cluster correlations; as well as the diameter. We show that our model is particularly effective at mimicing weighted scale-free small-world networks with a high and relatively stable clustering coefficient, which rapidly decline with the network size in most previous models.

Keywords

Cite

@article{arxiv.0910.1140,
  title  = {Deterministic weighted scale-free small-world networks},
  author = {Yichao Zhang and Zhongzhi Zhang and Shuigeng Zhou and Jihong Guan},
  journal= {arXiv preprint arXiv:0910.1140},
  year   = {2011}
}

Comments

a paper with 15 pages and 5 figures

R2 v1 2026-06-21T13:55:01.331Z