  Based on measurements of the Internet topology data, we found out that there
are two mechanisms which are necessary for the correct modeling of the Internet
topology at the Autonomous Systems (AS) level: the Interactive Growth of new
nodes and new internal links, and a nonlinear preferential attachment, where
the preference probability is described by a positive-feedback mechanism. Based
on the above mechanisms, we introduce the Positive-Feedback Preference (PFP)
model which accurately reproduces many topological properties of the AS-level
Internet, including: degree distribution, rich-club connectivity, the maximum
degree, shortest path length, short cycles, disassortative mixing and
betweenness centrality. The PFP model is a phenomenological model which
provides a novel insight into the evolutionary dynamics of real complex
networks.
