Accurately modeling the Internet topology

TL;DR

This paper introduces the Positive-Feedback Preference (PFP) model, which accurately captures the complex topological features of the Internet at the Autonomous Systems level by incorporating mechanisms like interactive growth and nonlinear preferential attachment.

Contribution

The paper presents the PFP model that combines two key mechanisms to accurately reproduce the Internet's topology, offering new insights into complex network evolution.

Findings

PFP model reproduces degree distribution and rich-club connectivity.

It accurately models maximum degree, shortest path length, and disassortative mixing.

The model provides a novel understanding of Internet's evolutionary dynamics.

Abstract

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.