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Online multipath convolutional coding for real-time transmission

机译:在线多径卷积编码用于实时传输

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摘要

Most of multipath multimedia streaming proposals use Forward Error Correction (FEC) approach to protect from packet losses. However, FEC does not sustain well burst of losses even when packets from a given FEC block are spread over multiple paths. In this article, we propose an online multipath convolutional coding for real-time multipath streaming based on an on-the-fly coding scheme called Tetrys. We evaluate the benefits brought out by this coding scheme inside an existing FEC multipath load splitting proposal known as Encoded Multipath Streaming (EMS). We demonstrate that Tetrys consistently outperforms FEC in both uniform and burst losses with EMS scheme. We also propose a modification of the standard EMS algorithm that greatly improves the performance in terms of packet recovery. Finally, we analyze different spreading policies of the Tetrys redundancy traffic between available paths and observe that the longer propagation delay path should be preferably used to carry repair packets.
机译:大多数多径多媒体流提议使用前向纠错(FEC)方法来防止数据包丢失。但是,即使来自给定FEC块的数据包分布在多条路径上,FEC也无法维持良好的丢失突发。在本文中,我们提出了一种基于实时编码方案Tetrys的在线多径卷积编码,用于实时多径流传输。我们评估这种编码方案在现有的FEC多路径负载分配建议(称为编码多路径流(EMS))中带来的好处。我们证明,在EMS方案下,Tetrys在均匀损失和突发损失方面始终优于FEC。我们还建议对标准EMS算法进行修改,以极大地提高数据包恢复的性能。最后,我们分析了可用路径之间的Tetrys冗余流量的不同扩展策略,并观察到较长的传播延迟路径应优选用于承载修复数据包。

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