MVP2P: Layer-Dependency-Aware Live MVC Video Streaming over Peer-to-Peer Networks
Zhao Liu, Niall Murray, Brian Lee, Enda Fallon, Yuansong Qiao

TL;DR
This paper introduces MVP2P, a novel layer-dependency-aware live MVC video streaming method over P2P networks that optimizes bandwidth usage and reduces server costs while maintaining high video quality.
Contribution
It proposes a maximum flow based model and a new streaming approach that considers layer dependencies and peer relationships in P2P MVC video streaming.
Findings
MVP2P significantly outperforms existing methods in bandwidth efficiency.
The approach effectively manages peer bandwidth, churn, and view switching.
Experimental results demonstrate improved streaming quality and reduced server bandwidth.
Abstract
Multiview video supports observing a scene from different viewpoints. The Joint Video Team (JVT) developed H.264/MVC to enhance the compression efficiency for multiview video, however, MVC encoded multiview video (MVC video) still requires high bitrates for transmission. This paper investigates live MVC video streaming over Peer-to-Peer (P2P) networks. The goal is to minimize the server bandwidth costs whist ensuring high streaming quality to peers. MVC employs intra-view and inter-view prediction structures, which leads to a complicated layer dependency relationship. As the peers' outbound bandwidth is shared while supplying all the MVC video layers, the bandwidth allocation to one MVC layer affects the available outbound bandwidth of the other layers. To optimise the utilisation of the peers' outbound bandwidth for providing video layers, a maximum flow based model is proposed which…
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