TY  - JOUR
N2  - 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.
ID  - discovery77144
PB  - AMERICAN PHYSICAL SOC
UR  - http://dx.doi.org/10.1103/PhysRevE.74.016124
SN  - 1539-3755
JF  - Physical Review E
A1  - Zhou, S
KW  - Complex Networks
TI  - Understanding the evolution dynamics of internet topology
AV  - public
VL  - 74
Y1  - 2006/07//
IS  - 1
N1  - ©2006 The American Physical Society
ER  -