Title :
Characterizing and Modelling Clustering Features in AS-Level Internet Topology
Author :
Yan Li ; Jun-Hong Cui ; Maggiorini, Dario ; Faloutsos, Michalis
Author_Institution :
Univ. of Connecticut, Storrs
Abstract :
The AS-level Internet topology has shown significant clustering features. In this paper, we propose a new set of clustering metrics and conduct extensive measurement on the AS- level Internet topology. We give a thorough characterization on the clustering features and their evolution. We also study the clustering features of different topological structures by comparing the Internet with various topology models. Due to the limitation of existing topology models on capturing clustering features, we design a new topology model based on clustering. Through extensive evaluations, we claim that our model can closely capture the clustering features as well as other common topological properties.
Keywords :
Internet; statistical analysis; telecommunication network topology; AS-level Internet topology; clustering metrics; Clustering algorithms; Communications Society; Computer science; Internet; Network topology; Partitioning algorithms; Peer to peer computing; Robustness; Routing protocols; USA Councils;
Conference_Titel :
INFOCOM 2008. The 27th Conference on Computer Communications. IEEE
Conference_Location :
Phoenix, AZ
Print_ISBN :
978-1-4244-2025-4
DOI :
10.1109/INFOCOM.2008.63