应用程序感知的视频分享服务通过云存储的来源

Jinjun Liu, D. Feng, Yu Hua, Bin Peng, Pengfei Zuo
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引用次数: 1

摘要

随着视频编辑软件的广泛使用,越来越多的类似视频被上传到云存储的视频分享平台上。大量的近重复视频不仅会让用户不满意,而且会消耗更多的服务提供商资源。由于近重复视频在内容层面具有冗余性,传统的重复数据删除技术不适合解决冗余问题。为了减少冗余,我们提出了一种新的高性能的基于源的视频共享系统,称为Provis。Provis记录视频的来源,并通过存储视频的来源来压缩近重复的视频,从而取代存储视频文件,提高空间效率。当用户尝试上传编辑后的视频时,Provis可以通过收集和上传视频的来源,在云中重建视频,以减少上传视频的网络开销。我们实现了Provis,并将其性能与其他现有的视频压缩技术进行了比较。我们的评估表明,Provis实现了显著的空间节省。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application-aware video-sharing services via provenance in cloud storage
With the wide use of video-editing software, more and more similar videos are uploaded to the video-sharing platforms in cloud storage. The large number of near-duplicate videos would not only make the users not satisfactory, but also consume more resources with service providers. Since the near-duplicate videos have redundancy at the content level, the traditional de-duplication technology is not suitable to address the redundancies. In order to decrease the redundancy, we proposed a novel high performance provenance-based video-sharing system, called Provis. Provis records the provenance of the videos and compresses the near-duplicate videos via storing their provenance which replaces storing their video files to improve the space efficiency. When users attempt to upload the edited videos, Provis can rebuild the videos in the cloud via collecting and uploading their provenance to reduce the network overhead of uploading videos. We implemented Provis and compared its performance with other existing video compression techniques. Our evaluation shows that Provis achieves significant space savings.
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