A stochastic fluid model for on-demand peer-to-peer streaming services

On-demand video streaming services have become popular in recent years. In current streaming services, however, the growth of user population leads to the lack of the upload rate of the video server. This mainly causes starvation in the playout buffer at a client, resulting in the degradation of user-level quality of service (QoS). In this paper, we consider an on-demand streaming service based on a peer-to-peer (P2P) technology. Focusing on the stochastic behavior of streaming data contents in the playout buffer at a client peer, we consider an analytical stochastic fluid model, which takes into account the heterogeneity among peer nodes and the peer churn. We derive the starvation probability that the playout buffer is empty. Numerical examples show that the starvation probability increases when the population of peer nodes grows. It is also shown that even when the population of peer nodes is extremely large, a small increase in the upload rate at ordinary-peer nodes significantly improves the QoS of P2P streaming services.

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