Affiliations: School of Computer Science and Informatics, University College Dublin, Dublin, Ireland. E-mails: [email protected], [email protected], [email protected] | Clique Research Cluster, University College Dublin, Dublin, Ireland
Note: [] Corresponding author: Kiril Dichev, School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland. E-mail: [email protected]
Abstract: In the area of network performance and discovery, network tomography focuses on reconstructing network properties using only end-to-end measurements at the application layer. One challenging problem in network tomography is reconstructing available bandwidth along all links during multiple source/multiple destination transmissions. The traditional measurement procedures used for bandwidth tomography are extremely time consuming. We propose a novel solution to this problem. Our method counts the fragments exchanged during a BitTorrent broadcast. While this measurement has a high level of randomness, it can be obtained very efficiently, and aggregated into a reliable metric. This data is then analyzed with state-of-the-art algorithms, which correctly reconstruct logical clusters of nodes interconnected by high bandwidth, as well as bottlenecks between these logical clusters. Our experiments demonstrate that the proposed two-phase approach efficiently solves the presented problem for a number of settings on a complex grid infrastructure.
Keywords: Network tomography, BitTorrent, clustering, bandwidth, bottleneck link
