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Peer-to-Peer protocols currently form the most heavily used protocol class in the Internet, with BitTorrent, the most popular protocol for content distribution, as its flagship. A high number of studies and investigations have been undertaken to measure, analyse and improve the inner workings of the BitTorrent protocol. Approaches such as tracker message analysis, network probing and packet sniffing have been deployed to understand and enhance BitTorrent's internal behaviour. In this paper the authors present a novel approach that aims to collect, process and analyse large amounts of local peer information in BitTorrent swarms. They classify the information as periodic status information able to be monitored in real time and as verbose logging information to be used for subsequent analysis.
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