Weighted Network Models Based on Local and Global Rules

Details Weighted Network Models Based on Local and Global Rules Weighted Network Models Based on Local and Global Rules

2005-05-17

arxiv.org/abs/cond-mat/0505417v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

9 pages, 11 figures, submitted to PRE

Scientific paper

We will introduce two evolving models that characterize weighted complex networks. Though the microscopic dynamics are different, these models are found to bear a similar mathematical framework, and hence exhibit some common behaviors, for example, the power-law distributions and evolution of degree, weight and strength. We also study the nontrivial clustering coefficient C and tunable degree assortativity coefficient r, depending on specific parameters. Most results are supported by present empirical evidences, and may provide us with a better description of the hierarchies and organizational architecture of weighted networks. Our models have been inspired by the weighted network model proposed by Alain Barrat et al. (BBV for short), and can be considered as a meaningful development of their original work.

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