Measuring the likelihood of models for network evolution

Authors:
Richard G. Clegg;Raul Landa;Hamed Haddadi;Miguel Rio
Affiliations:
Dept of Elec. Eng., University College London, London, UK;Dept of Elec. Eng., University College London, London, UK;Max Planck Institute for Software Systems, Kaiserslautern, Saarbrücken, Germany;Dept of Elec. Eng., University College London, London, UK
Venue:
INFOCOM'09 Proceedings of the 28th IEEE international conference on Computer Communications Workshops
Year:
2009

Citing 3
Cited 1

Orbis: rescaling degree correlations to generate annotated internet topologies

Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
An integrated model of traffic, geography and economy in the internet

ACM SIGCOMM Computer Communication Review
Network topologies: inference, modeling, and generation

IEEE Communications Surveys & Tutorials

A likelihood based framework for assessing network evolution models tested on real network data

Proceedings of the 1st Annual Workshop on Simplifying Complex Network for Practitioners

Quantified Score

Hi-index	0.00

Visualization

Abstract

Many researchers have hypothesised models which explain the evolution of the topology of a target network. The framework described in this paper gives the likelihood that the target network arose from the hypothesised model. This allows rival hypothesised models to be compared for their ability to explain the target network. A null model (of random evolution) is proposed as a baseline for comparison. The framework also considers models made from linear combinations of model components. A method is given for the automatic optimisation of component weights. The framework is tested on simulated networks with known parameters and also on real data.