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QoE-optimal rate adaptation for HTTP adaptive streaming

机译:HTTP自适应流的QoE最佳速率自适应

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HTTP Adaptive Streaming(HAS) has become widely deployed in multimedia services for its ability for providing the best Quality of Experience(QoE) for viewers with limited resource, especially in fluctuating wireless networkings. With its client-driven rate adaptation mechanism, HAS is able to adapt to fluctuating network condition and various terminals dynamically. The rate adaptation algorithm is crucial in HAS for its direct impact on the QoE. Most of researches focus on optimizing objective indicators, such as elevating mean bit-rate, lessening playout interruption, and avoiding quality switches, etc. However, the promotion in objective indicators doesn't indicate better experience of end users directly. In this paper, a novel QoE-Optimal Rate Adaptation(QORA) algorithm is proposed to achieve the best QoE. Firstly, a QoE model with iterative form is deduced for on-line evaluation. According to this model, the QORA is able to predict the possible QoE of each bit-rate level in candidate, then greedily choose the one with the highest QoE. The perceptual quality of HAS is optimized by the QORA directly and quantitatively. The simulation result shows that the proposed QORA is able to provide the optimal QoE compared with other rate adaptation schemes, although some of them have better performance in a single objective indicator.
机译:HTTP自适应流(具有)已广泛部署在多媒体服务中,以便为具有有限资源的观众提供最佳体验(QoE)的能力,特别是在波动的无线网络中。利用其客户端驱动的速率适应机制,能够动态地适应网络状况和各种终端的波动。速率适应算法对于其对QoE的直接影响至关重要。大多数研究专注于优化客观指标,例如提升平均比特率,减少播出中断,避免质量开关等。然而,客观指标的促销不会直接表明最终用户的更好体验。本文提出了一种新颖的QoE - 最佳速率适应(Qora)算法来实现最佳QoE。首先,推导出具有迭代形式的QoE模型进行在线评估。根据该模型,Qora能够在候选人中预测每个比特率水平的可能QoE,然后贪婪地选择具有最高QoE的那个。感知质量已经由Qora直接和定量地优化。仿真结果表明,与其他速率适应方案相比,所提出的Qora能够提供最佳QoE,但其中一些在单个客观指标中具有更好的性能。

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