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EAAT: Environment-Aware Adaptive Transmission for Split-Screen Video Streaming

机译:EAAT:环境感知用于筛选视频流的自适应传输

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摘要

With the tremendous growth of video contents and mobility demands, there is a need to develop more personalized video services. Split-screen services, such as picture in picture become more and more popular. Furthermore, the user’s viewing environment affects the user’s quality of experience (QoE). Therefore, video transmission of split-screen services face several major challenges, such as to quantify the impact of environmental factors on user’s QoE; how to assess the user’s QoE of the split-screen services; how to choose the bit-rate of each video stream to maximize user’s QoE of the split-screen services. To address these challenges, in the paper, an environment-aware adaptive transmission (EAAT) scheme for split-screen video streaming is first presented. Then, we introduce a mathematical model for characterizing user’s QoE to be affected by environmental factors in the proposed EAAT. In the model, the QoE of user’s relationship with the viewing environment is proposed. Based on the model, a problem of maximizing user’s QoE is formulated, and we develop a heuristic algorithm to solve the optimization problem. In addition, we conduct various trace-bandwidth experiments to rigorously evaluate the proposed EAAT scheme in different network environments, and show that EAAT can enrich the video quality while saving network resources.
机译:随着视频内容和移动性需求的巨大增长,需要开发更多个性化的视频服务。拆分屏幕服务,如图片中的图片变得越来越受欢迎。此外,用户的观看环境影响用户的体验质量(QoE)。因此,拆分屏幕服务的视频传输面临着几种主要挑战,例如量化环境因素对用户QoE的影响;如何评估用户的Qoe屏幕服务;如何选择每个视频流的比特率,以最大化拆分屏幕服务的用户QoE。为了解决这些挑战,在论文中,首先呈现用于分流屏幕视频流的环境感知自适应传输(EAAT)方案。然后,我们介绍了一个数学模型,用于表征用户的QoE受到拟议的EAAT中的环境因素的影响。在模型中,提出了用户与观看环境的关系的QoE。基于该模型,制定了最大化用户QoE的问题,我们开发了一种启发式算法来解决优化问题。此外,我们进行各种微量带宽实验,以严格评估不同网络环境中的拟议的EAAT方案,并显示EAAT可以在节省网络资源时丰富视频质量。

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