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Parity Stream Construction Method Based on Estimated Utility for Multi-Server Video Streaming System

机译:基于多服务器视频流系统的估计实用程序的奇偶校验流施工方法

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In this paper, we propose a parity stream construction method that exploits multiple video streams. In this construction, estimated utility of parity data is considered. The proposed method gives priority to each data of multiple streams in terms of recovery from packet losses, and it is designed for recovering important data with higher probability. The priority of each data is set based on both inherent importance within a stream and loss probabilities of multiple streams. Specifically, this method deals with the data of less received streams as the important data. Moreover, we focus on the creation method of redundant data to be transferred from another server for multiple worse conditioned streams, which greatly affects the recovery capability, and propose the creation method which is less influenced from the network condition. Our simulation results show that the proposed method can recover more important data with higher probability. Furthermore, the proposed method can also achieve almost the same restoration ratio among streams of recovery targets which have different loss probabilities.
机译:在本文中,我们提出了一种利用多个视频流的奇偶校验流构造方法。在这种结构中,考虑了奇偶校验数据的估计效用。所提出的方法在从分组丢失恢复方面优先考虑多个流的每个数据,并且它被设计用于以更高的概率恢复重要数据。基于多流的流和损耗概率内的固有重要性来设置每个数据的优先级。具体地,该方法处理较少收到的流的数据作为重要数据。此外,我们专注于要从另一台服务器传输的冗余数据的创建方法,用于多个更糟糕的条件流,这极大地影响了恢复功能,并提出了从网络条件影响的创建方法。我们的仿真结果表明,该方法可以以更高的概率恢复更重要的数据。此外,所提出的方法还可以在具有不同损失概率的恢复目标流之间实现几乎相同的恢复比。

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