Szemerédi-type clustering of peer-to-peer streaming system

In this work we made a preliminary clustering analysis of an experimental peer-to-peer system, tested in a small scale experiments within PlanetLab. The application was an Internet-TV like streaming system based on Chord architecture. Our clustering is inspired by the Szemeredi's Regularity Lemma (SzRL). Such approach was already demonstrated in biology and appeared to be a powerful tool. Szemeredi's result suggests that the nodes of a large enough graph can be partitioned in few clusters in such a way that link distribution between most of the pairs look like random. Our main goal is to study what can this type of clustering tell us about p2p systems using our experimental system as source of data. We searched clusterings of Szemeredi-type by using max likelihood as guidance. Our graph is directed and weighted. The link direction indicates a client-server relation and the value is the proportion of all chunks obtained from such a link during the whole experiment. We think that the preliminary results are interesting. Most of the cluster pairs have very distinguished patterns of link distribution, indicating that such a novel approach has potential in classifying peers effectively. The values of weights between clusters and their distribution show some apparent patterns. We end up with 9 cluster pairs. Contributions: practical implementations of streaming system by V. P. and analysis by H. R.

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