Abstract
The popularization of video capture devices has created strong storage demand for encoded videos. Approximate storage can ease this demand by enabling denser storage at the expense of occasional errors. Unfortunately, even minor storage errors, such as bit flips, can result in major visual damage in encoded videos. Similarly, video encryption, widely employed for privacy and digital rights management, may create long dependencies between bits that show little or no tolerance to storage errors.
In this paper we propose VideoApp, a novel and efficient methodology to compute bit-level reliability requirements for encoded videos by tracking visual and metadata dependencies within encoded bitstreams. We further show how VideoApp can be used to trade video quality for storage density in an optimal way. We integrate our methodology into a popular H.264 encoder to partition an encoded video stream into multiple streams that can receive different levels of error correction according to their reliability needs. When applied to a dense and highly error-prone multi-level cell storage substrate, our variable error correction mechanism reduces the error correction overhead by half under the most error-intolerant encoder settings, achieving quality/density points that neither compression nor approximation can achieve alone. Finally, we define the basic invariants needed to support encrypted approximate video storage. We present an analysis of block cipher modes of operation, showing that some are fully compatible with approximation, enabling approximate and secure video storage systems.
- High efficiency video coding: Recommendation ITU-T H.265. https://www.itu.int/rec/T-REC-H.265.Google Scholar
- Advanced video coding for generic audiovisual services: Recommendation ITU-T H.264. https://www.itu.int/rec/T-REC-H.264.Google Scholar
- VideoLAN x264 library and application. http://www.videolan.org/developers/x264.html.Google Scholar
- F. Frescura, M. Giorni, C. Feci, and S. Cacopardi. JPEG2000 and MJPEG2000 Transmission in 802.11 Wireless Local Area Networks. IEEE Transactions on Consumer Electronics, 49 (4): 861--871, Nov. 2003. Google Scholar
Digital Library
- Q. Guo, K. Strauss, L. Ceze, and H. Malvar. High-Density Image Storage Using Approximate Memory Cells. In Proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2016. Google Scholar
Digital Library
- Z. Guo, Y. Nishikawa, R. Y. Omaki, T. Onoye, and Shirakawa. A Low-Complexity FEC Assignment Scheme for Motion JPEG2000 over Wireless Network. IEEE Transactions on Consumer Electronics, 52 (1): 81--86, Feb. 2006.Google Scholar
Digital Library
- J. Kastrenakes. Google Announces Unlimited Pictures and Video Storage with new Photos App. http://www.theverge.com/2015/5/28/8678629/google-photos-app-announced, 2015.Google Scholar
- S. Liu, K. Pattabiraman, T. Moscibroda, and B. G. Zorn. Flikker: Saving DRAM Refresh-power Through Critical Data Partitioning. In In Proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2011. Google Scholar
Digital Library
- J. Lucas, M. Alvarez-Mesa, M. Andersch, and B. Juurlink. Sparkk: Quality-Scalable Approximate Storage in DRAM. In The Memory Forum, 2014.Google Scholar
- D. MacKay. Information Theory, Inference, and Learning Algorithms. Cambridge University Press, 2003.Google Scholar
- D. Marpe, H. Schwarz, and T. Wiegand. Context-Based Adaptive Binary Arithmetic Coding in the H.264/AVC Video Compression Standard. IEEE Transactions on Circuits and Systems for Video Technology, 13 (7): 604--632, July 2003. Google Scholar
Digital Library
- L. Merritt and R. Vanam. Improved Rate Control and Motion Estimation for H.264 Encoder. In IEEE International Conference on Image Processing, 2007.Google Scholar
Cross Ref
- ]vqmtMultimedia Signal Processing Group. VQMT: Video Quality Measurement Tool. http://mmspg.epfl.ch/vqmt.Google Scholar
- 001)]NistAESNational Institute of Standards and Technology. Advanced Encryption Standard (AES). http://www.nist.gov/, 2001.Google Scholar
- I. Richardson. The H.264 Advanced Video Compression Standard. John Wiley and Sons, 2nd edition, 2010. Google Scholar
Cross Ref
- A. Sampson, W. Dietl, E. Fortuna, D. Gnanapragasam, L. Ceze, and D. Grossman. EnerJ: Approximate Data Types for Safe and General Low-power Computation. In Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation, 2011. Google Scholar
Digital Library
- A. Sampson, J. Nelson, K. Strauss, and L. Ceze. Approximate Storage in Solid-State Memories. In Proceedings of the International Symposium on Microarchitecture (MICRO), 2013. Google Scholar
Digital Library
- ]sssiSolid State Storage Initiative. NAND Flash Solid State Storage for the Enterprise: An In-depth Look at Reliability. http://www.snia.org/sites/default/files/SSSI Reliability White Paper 4-09 B.pdf.Google Scholar
- 016)]YouTube2016Team FanBridge. YouTube Trends of 2016 (So Far). https://www.fanbridge.com/blog/youtube-trends-of-2016, 2016.Google Scholar
- 016)]vmafThe Netflix Tech Blog. Toward A Practical Perceptual Video Quality Metric. http://techblog.netflix.com/2016/06/toward-practical-perceptual-video.html, 2016.Google Scholar
- S. Winkler and P. Mohandas. The Evolution of Video Quality Measurement: From PSNR to Hybrid Metrics. IEEE Transactions on Broadcasting, 54 (3): 660--668, Sept. 2008. Google Scholar
Cross Ref
- XiphXiph.Org Foundation. Xiph.org Video Test Media. https://media.xiph.org/video/derf/.Google Scholar
Index Terms
Approximate Storage of Compressed and Encrypted Videos
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