While the evolution of mobile computing is experiencing a considerable growth, it is at the same time seriously threatened by the limitations of the battery technology, which does not keep pace with the evergrowing increase in energy requirements of mobile applications. A novel approach for reducing the energy appetite of mobile apps comes from the approximate computing field, which proposes techniques that in a controlled manner sacrifice computation accuracy for higher energy savings. Building on this philosophy we propose a context-aware mobile video quality adaptation that reduces the energy needed for video playback, while ensuring that a user's quality expectations with respect to the mobile video are met. We confirm that the decoding resolution can play a significant role in reducing the overall power consumption of a mobile device and conduct two user studies to investigate how the context in which a video is played, its content, and the user's personality, modulate a user's quality expectations. We discover that a user's physical activity, the spatial/temporal properties of the video, and the user's personality traits interact and jointly influence the minimal acceptable playback resolution, paving the way for context-adaptable approximate mobile computing.
翻译:虽然移动计算的发展正在经历相当大的增长,但它同时也受到电池技术局限性的严重威胁,电池技术的局限性与移动应用的能源需求的不断增加不同步。降低移动应用的能源食用量的新办法来自近似计算领域,它提出了以控制方式牺牲计算准确性以节省高能源的技术。基于这一理念,我们提议了一种符合背景的移动视频质量适应,以减少视频播放所需的能量,同时确保满足用户对移动视频的质量期望。我们确认,解码解决方案可以在减少移动设备总体电力消耗方面发挥重要作用,并进行两项用户研究,以调查视频的播放环境、内容和用户的个性,调整用户的质量期望。我们发现,用户的物理活动、视频的空间/时空特性以及用户的个性特征相互作用,共同影响最起码的可接受的回放分辨率,为背景可调适近的移动计算铺平了道路。