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GroupCast: Preference-aware cooperative video streaming with scalable video coding

机译:GroupCast:具有可伸缩视频编码的偏好感知协作视频流

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In this paper, we propose a Preference Aware Cooperative video streaming system for videos encoded using Scalable Video Coding (SVC) where all contributing users are interested in watching the same video on a single screen. Each user's willingness to cooperate is subjected to their own constraint such as user data plan (unlimited, 6GB, 2GB, ..., etc). Using SVC, each layer of every chunk can be fetched through only one of the cooperating users. We formulate the quality decisions of video chunks and fetching policy of the SVC layers subject to the available bandwidth, chunk deadlines, and cooperation willingness of the different users as an optimization problem. The objective is to jointly minimize the re-buffering time, maximize the average quality, and minimize the number of quality switches without violating any of the imposed constraints. We propose an offline algorithm to solve the non-convex optimization problem. This algorithm has a complexity that is polynomial in the video length and the number of cooperating users. Further, this algorithm is shown to be optimal in certain special cases. Moreover, we propose an online algorithm for more practical scenarios where erroneous bandwidth prediction for a short window is used. Simulations driven by real SVC encoded video and real bandwidth traces of a public dataset reveal the robustness and high-performance achievement of our scheme. The results motivate our next step of implementing real test bed.
机译:在本文中,我们为使用可伸缩视频编码(SVC)编码的视频提出了一种“偏好感知合作视频流”系统,该系统中所有参与的用户都希望在单个屏幕上观看同一视频。每个用户的合作意愿都受到他们自己的约束,例如用户数据计划(无限,6GB,2GB等)。使用SVC,每个组块的每一层都只能通过一个合作用户来获取。我们根据可用带宽,块期限和不同用户的合作意愿,将视频组块的质量决策和SVC层的获取策略制定为优化问题。目的是在不违反任何强加约束的情况下,共同减少重新缓冲时间,最大化平均质量,并减少质量切换的次数。我们提出了一种离线算法来解决非凸优化问题。该算法的复杂度是视频长度和合作用户数的多项式。此外,在某些特殊情况下,该算法被证明是最佳的。此外,我们提出了一种在线算法,用于更实际的场景,其中使用了针对短窗口的错误带宽预测。由真实的SVC编码视频和公共数据集的真实带宽轨迹驱动的仿真显示了我们方案的鲁棒性和高性能。结果激发了我们实施真实测试平台的下一步。

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