Modeling P2P-TV Traffic

• Maria Antonieta Garcia Politecnico di Torino
• Ana Paula Couto da Silva UFJF
• Michela Meo Politecnico di Torino

Resumo

The increasing success of P2P-TV applications calls for the need of new traffic models that can effectively represent the traffic generated by these applications. In this paper, we consider PPLive; we study and model the traffic generated by PPLive clients. From the analysis of some real traffic traces, we recognize that the peer may follow three typical behaviors, depending on the peer degree of contribution to the video content distribution. We then propose two simple models of the data received or transmitted by a peer: i) the Memoryless model that fits the distribution of traffic exchanged during short time windows; ii) the Hidden-Markov model that introduces also some memory in the traffic generation process so that the autocorrelation function typical of real traces can be matched. The accuracy of the models for all three classes of peer behavior is validated by both directly comparing synthetic traces generated by the models with real traces and considering the performance of a queue fed by these traces. Our results show that the models are quite accurate and can be effectively used as synthetic traffic generators.

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