2005/12/31 by Shi Zhou · 1 citation
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Network Traffic and Congestion Control #Opinion Dynamics and Social Influence #cs.NI
paper · pdf · doi:10.1103/physreve.74.016124
published as Physical Review E, vol. 70, no. 016124, July 2006. · 15 figures
arxiv created 2006/07/13 · openalex publication_date 2006/07/31 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.