Understanding the internet topology evolution mechanisms

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  • 2 December 2005
Abstract
As of this writing, the most precise and complete internet AS-level topology generator is the recently introduced Positive-Feedback Preference (PFP) model. The model uses two mechanisms, namely the interactive growth and the positive-feedback preference. To understand the success of the model in capturing so many important topology characteristics, this paper comparatively examines two limiting cases of the PFP model and numerically investigates the model's sensitivity to its two parameters. This paper presents detailed analysis on how the two mechanisms profoundly affect network evolution dynamics and therefore effectively change the obtained topology properties. This paper provides a number of insightful results, for example the rich-club connectivity is exclusively controlled by the interactive growth mechanism and the PFP model is able to generate a wide range of disassortative mixing networks encompassing most reported technological and biological networks. This work represents a good step towards understanding the internet topology evolution mechanisms.

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