Understanding the internet topology evolution dynamics

TL;DR

This paper analyzes the Positive-Feedback Preference (PFP) model to understand how it accurately reproduces diverse internet topology properties and reveals the underlying network evolution mechanisms responsible for these characteristics.

Contribution

It provides a detailed analysis of the PFP model's ability to replicate multiple internet topology features and explains the network evolution mechanisms behind these properties.

Findings

PFP model accurately reproduces diverse internet topology features.

Network evolution mechanisms control topology properties.

Insights into correlations between structural characteristics.

Abstract

The internet structure is extremely complex. The Positive-Feedback Preference (PFP) model is a recently introduced internet topology generator. The model uses two generic algorithms to replicate the evolution dynamics observed on the internet historic data. The phenomenological model was originally designed to match only two topology properties of the internet, i.e. the rich-club connectivity and the exact form of degree distribution. Whereas numerical evaluation has shown that the PFP model accurately reproduces a large set of other nontrivial characteristics as well. This paper aims to investigate why and how this generative model captures so many diverse properties of the internet. Based on comprehensive simulation results, the paper presents a detailed analysis on the exact origin of each of the topology properties produced by the model. This work reveals how network evolution mechanisms control the obtained topology properties and it also provides insights on correlations between various structural characteristics of complex networks.