Accurately Modeling the Internet Topology: Introduction of the Positive-Feedback Preference (PFP) Model

Title: Accurately Modeling the Internet Topology: Introduction of the Positive-Feedback Preference (PFP) Model

Research Question: How can we accurately model the complex topology of the Internet at the Autonomous Systems (AS) level using a phenomenological model?

Methodology: The researchers based their model on two key mechanisms necessary for correct modeling of the Internet topology: the appearance of new internal links between existing nodes and a nonlinear preferential growth. They introduced the Positive-Feedback Preference (PFP) model, which accurately reproduces many topological properties of the AS-level Internet, including degree distribution, rich-club connectivity, maximum degree, shortest path length, short cycles, disassortative mixing, and betweenness centrality.

Results: The PFP model provides a novel insight into the evolutionary dynamics of real complex networks. It accurately reproduces the degree distribution, which follows a power-law with an exponent γ ≈ 2.22, similar to the Internet. Additionally, it successfully models the connectivity among high-degree nodes and the maximum degree of the network.

Implications: The PFP model offers a new approach to understanding the complex topology of the Internet at the AS level. It provides a more accurate representation of the network's structure and dynamics than previous models, such as the Barabási-Albert model. This could have significant implications for network science, network analysis, and the design of robust and efficient networks in various fields.

Link to Article: https://arxiv.org/abs/0402011v3 Authors: arXiv ID: 0402011v3