PlanetLab: an overlay testbed for broad-coverage services
ACM SIGCOMM Computer Communication Review
Traffic analysis of peer-to-peer IPTV communities
Computer Networks: The International Journal of Computer and Telecommunications Networking
On the Quality of Experience of SopCast
NGMAST '08 Proceedings of the 2008 The Second International Conference on Next Generation Mobile Applications, Services, and Technologies
Topology Dynamics in a P2PTV Network
NETWORKING '09 Proceedings of the 8th International IFIP-TC 6 Networking Conference
Measurement and modeling of a large-scale overlay for multimedia streaming
The Fourth International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness & Workshops
Characterizing SopCast client behavior
Computer Communications
Characterizing Dynamic Properties of the SopCast Overlay Network
PDP '12 Proceedings of the 2012 20th Euromicro International Conference on Parallel, Distributed and Network-based Processing
A Measurement Study of a Large-Scale P2P IPTV System
IEEE Transactions on Multimedia
Using centrality metrics to predict peer cooperation in live streaming applications
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part II
Fast centrality-driven diffusion in dynamic networks
Proceedings of the 22nd international conference on World Wide Web companion
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P2P-TV applications have attracted a lot of attention from the research community in the last years. Such systems generate a large amount of data which impacts the network performance. As a natural consequence, characterizing these systems has become a very important task to develop better multimedia systems. However, crawling data from P2P live streaming systems is particularly challenging by the fact that most of these applications have private protocols. In this work, we present a set of logs from a very popular P2P live streaming application, the SopCast. We describe our crawling methodology, and present a brief SopCast characterization. We believe that our logs and the characterization can be used as a starting point to the development of new live streaming systems.