Modelling Video Rate Evolution in Adaptive Bitrate Selection

Yusuf Sani, A. Mauthe, C. Edwards
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引用次数: 20

Abstract

Adaptive bitrate selection adjusts the quality of HTTP streaming video to a changing context. A number of different schemes have been proposed that use buffer state in the selection of the appropriate video rate. However, models describing the relationship between video quality levels and buffer occupancy are mostly based on heuristics, which often results in unstable and/or suboptimal quality. In this paper, we present a QoE-aware video rate evolution model based on buffer state changes. The scheme is evaluated within a real world Internet environment, where it is shown to improve the stability of the video rate. Up to 27% gain in average video rate can be achieved compared to the baseline ABR. The average throughput utilisation at a steady-state reaches 100% in some of the investigated scenarios.
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自适应比特率选择中的视频速率演化建模
自适应比特率选择调整HTTP流视频的质量以适应不断变化的上下文。已经提出了许多不同的方案,使用缓冲状态来选择合适的视频速率。然而,描述视频质量水平和缓冲区占用之间关系的模型大多是基于启发式的,这通常会导致不稳定和/或次优质量。本文提出了一种基于缓存状态变化的qos感知视频速率演化模型。在真实的互联网环境中对该方案进行了评估,结果表明该方案提高了视频速率的稳定性。与基准ABR相比,平均视频速率可获得高达27%的增益。在所调查的一些场景中,稳定状态下的平均吞吐量利用率达到100%。
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