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FLIP-CPM: A Parallel Community Detection Method

Uncovering the underlying community structure of the Internet at the AS level is essential way to gain insight both into its structure and its functional organization. Of all the de?nitions of community proposed by researchers, we focused on the k-clique community de?nition as we believe it best catches the characteristics of the Internet AS-level topology. Extracting k-clique communities using the methods available in the literature requires a formidable amount of computational load and memory resources. In this paper we propose a new parallel method that has proved its capability in extracting communities e?ciently and e?ectively from realworld complex networks, including the Internet at the AS level. This innovative method is much less resource intensive than Clique Percolation Method and experimental results show it is always at least an order of magnitude faster. In addition, tests run on parallel architectures show a noticeable speedup factor, in some cases linear with the number of cores.


26th International Symposium on Computer and Information Sciences (ISCIS 2011), London (UK), 2011

Autori esterni: Luciano Lenzini (Dept. of Information Engineering University of Pisa, Italy)
Autori IIT:

Enrico Gregori

Foto di Enrico Gregori

Simone Mainardi

Foto di Simone Mainardi

Chiara Orsini

Foto di Chiara Orsini

Tipo: Articolo in Atti di convegno internazionale con referee
Area di disciplina: Information Technology and Communication Systems
Da pagina 249 a pagina 255

Attività: Internet Measurements & Design