UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Evaluating and Optimising Models of Network Growth

Clegg, RG; Landa, R; Harder, U; Rio, M; (2009) Evaluating and Optimising Models of Network Growth. Green open access

[thumbnail of 1341577_0904.0785v1.pdf]
Available under License : See the attached licence file.

Download (308kB)


This paper presents a statistically sound method for measuring the accuracy with which a probabilistic model reflects the growth of a network, and a method for optimising parameters in such a model. The technique is data-driven, and can be used for the modeling and simulation of any kind of evolving network. The overall framework, a Framework for Evolving Topology Analysis (FETA), is tested on data sets collected from the Internet AS-level topology, social networking websites and a co-authorship network. Statisticalmodels of the growth of these networks are produced and tested using a likelihoodbased method. The models are then used to generate artificial topologies with the same statistical properties as the originals. This work can be used to predict future growth patterns for a known network, or to generate artificial models of graph topology evolution for simulation purposes. Particular application examples include strategic network planning, user profiling in social networks or infrastructure deployment in managed overlay-based services.

Type: Report
Title: Evaluating and Optimising Models of Network Growth
Open access status: An open access version is available from UCL Discovery
Publisher version: http://arxiv.org/abs/0904.0785
Language: English
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
URI: https://discovery.ucl.ac.uk/id/eprint/1341577
Downloads since deposit
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item