On accounting for screen resolution in adaptive video streaming: QoE‐driven bandwidth sharing framework,International Journal of Network Management

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On accounting for screen resolution in adaptive video streaming: QoE‐driven bandwidth sharing framework
International Journal of Network Management ( IF 1.5 ) Pub Date : 2020-07-13 , DOI: 10.1002/nem.2128
Othmane Belmoukadam ₁ , Muhammad Jawad Khokhar ₁ , Chadi Barakat ₁

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Screen resolution along with network conditions are main objective factors impacting the user experience, in particular for video streaming applications. User terminals on their side feature more and more advanced characteristics resulting in different network requirements for good visual experience. Previous studies tried to link mean opinion score (MOS) to video bitrate for different screen types (e.g., Common Intermediate Format [CIF], Quarter Common Intermediate Format [QCIF], and High Definition [HD]). We leverage such studies and formulate a Quality of Experience (QoE)‐driven resource allocation problem to pinpoint the optimal bandwidth allocation that maximizes the QoE over all users of a network service provider located behind the same bottleneck link, while accounting for the characteristics of the screens they use for video playout. For our optimization problem, QoE functions are built using curve fitting on datasets capturing the relationship between MOS, screen characteristics, and bandwidth requirements. We propose a simple heuristic based on Lagrangian relaxation and Karush Kuhn Tucker (KKT) conditions to efficiently solve the optimization problem. Our numerical simulations show that the proposed heuristic is able to increase overall QoE up to 20% compared to an allocation with a TCP look‐alike strategy implementing max‐min fairness.

中文翻译：

在自适应视频流中考虑屏幕分辨率：QoE驱动的带宽共享框架

屏幕分辨率以及网络状况是影响用户体验的主要客观因素，尤其是对于视频流应用而言。用户端的功能越来越先进，导致对网络的要求不同，以提供良好的视觉体验。先前的研究试图将平均意见得分（MOS）与不同屏幕类型（例如，通用中间格式[CIF]，季度通用中间格式[QCIF]和高清[HD]）的视频比特率相关联。我们利用这些研究并制定由体验质量（QoE）驱动的资源分配问题，以查明最佳带宽分配，该带宽分配可以使位于同一瓶颈链路后面的网络服务提供商的所有用户的QoE最大化。用于视频播放的屏幕。对于我们的优化问题，QoE函数是使用曲线拟合在捕获MOS，屏幕特性和带宽要求之间的关系的数据集上构建的。我们提出一种基于拉格朗日松弛和Karush Kuhn Tucker（KKT）条件的简单启发式方法，以有效解决优化问题。我们的数值模拟表明，与采用TCP相似策略实现最大-最小公平性的分配相比，所提出的启发式方法能够将总体QoE提高20％。

更新日期：2020-07-13

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