Applying advanced statistical techniques, we characterize the peculiarities of a locally observed peer population in a popular P2P overlay network. The latter is derived from a mesh-pull architecture. Using flow data collected at a single peer, we show how Pareto and Generalized Pareto models can be applied to classify the local behavior of the population feeding a peer. Our approach is illustrated both by file sharing data of a P2P session generated by a mobile BitTorrent client in a WiMAX testbed and by video data streamed to a stationary client in a SopCast session. These techniques can help us to cope with an efficient adaptation of P2P dissemination protocols to mobile environments. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Markovich, N. M., & Krieger, U. R. (2013). Analysis of packet transmission processes in peer-to-peer networks by statistical inference methods. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7754, 104–119. https://doi.org/10.1007/978-3-642-36784-7_5
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