Viewing experience optimization based on adaptive requesting window adjustment in peer-to-peer media streaming

In the last few years, great achievements have been made in the field of peer-to-peer (P2P) streaming system. In mesh-based P2P streaming system, retrieving data from multiple parents simultaneously improves resilience of the streaming service. However, it also brings in playback lags. To improve users’ viewing experiences, we should consider both playback lags and resilience of the streaming service. However, it seems there is a natural trade-off between these two goals. In this paper we propose a viewing experience optimization algorithm which adjusts the position of the requesting window adaptively based on different requesting strategies. The novelty of the proposed method is that it utilizes heterogeneous real-time demands for different genres of videos, and can adjust requesting strategies adaptively. Under the condition of guaranteeing basic QoS (Quality of Service), the algorithm achieves a balance between playback lags and resilience. Finally, experiment results show the satisfactory performance of the proposed method.

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► There is a trade-off between playback lags and resilience of P2P streaming service.
► Our method utilizes heterogeneous real-time demands for different genres of videos.
► Our algorithm achieves a balance between playback lags and resilience adaptively.