Accurately modeling the Internet topology

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  • 5 February 2004
Abstract
To model the behavior of a network it is crucial to obtain a good description of its topology because structure affects function. When studying the topological properties of the Internet, we found out that there are two mechanisms which are necessary for the correct modeling of the Internet: a nonlinear preferential growth, where the growth is described by a positive-feedback mechanism, and the appearance of new links between already existing nodes. We show that the Positive-Feedback Preference (PFP) model, which is based on the above mechanisms, reproduces topological properties of the Internet such as: degree distribution, tier structure (rich-club connectivity), shortest path length, neighbor clustering, network redundancy (triangle and rectangle coefficient), disassortative mixing (nearest-neighbors average degree) and information flow pattern (betweenness centrality). We believe that these growth mechanisms need further study because they provide a novel insight into the evolutionary dynamics of real complex networks.

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