Energy-Efficient and QoE-Aware 360-Degree Video Streaming on Mobile Devices

Xianda Chen, Guohong Cao
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引用次数: 4

Abstract

Tile-based streaming has been widely used in 360° video streaming to adapt to varying network conditions. However, downloading and processing many small tiles consumes a large amount of energy on mobile devices. To address this issue, we propose techniques to encode video by considering the viewing popularity, where the tiles requested by users of similar interests are encoded as a large tile (called Ptile). When encoding Ptiles, we propose to further save energy by reducing the insignificant frames in each video segment, i.e., reducing the frame rate to save energy while satisfying some QoE constraint. Based on real video traces, we model the impact of video features (i.e., video bitrate, frame rate) and user behavior (i.e., view switching) on QoE, and model the impact of video features on power consumption. Based on the QoE model and the power model, we formulate the energy-efficient and QoE-aware 360° video streaming problem as an optimization problem, and propose a control theory based algorithm to solve it. Through extensive evaluations based on real traces, we demonstrate that the proposed algorithm can significantly reduce the energy consumption (49.7%) and improve the QoE (7.4%).
移动设备上的节能和qos感知360度视频流
在360°视频流中,基于tile的流被广泛应用,以适应不同的网络条件。然而,在移动设备上下载和处理许多小块会消耗大量的能量。为了解决这个问题,我们提出了通过考虑观看流行度来编码视频的技术,其中具有相似兴趣的用户请求的图像被编码为一个大图像(称为Ptile)。在编码ptile时,我们提出通过减少每个视频片段中不重要的帧来进一步节省能量,即在满足一定QoE约束的同时降低帧率来节省能量。基于真实视频轨迹,我们模拟了视频特征(即视频比特率、帧率)和用户行为(即视图切换)对QoE的影响,并模拟了视频特征对功耗的影响。在QoE模型和功率模型的基础上,将节能且感知QoE的360°视频流问题作为优化问题,提出了一种基于控制理论的算法来解决该问题。通过基于真实轨迹的广泛评估,我们证明了该算法可以显著降低能耗(49.7%),提高QoE(7.4%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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