Live video analytics at scale with approximation and delay-tolerance

Haoyu Zhang, Ganesh Ananthanarayanan, Peter Bodik, Matthai Philipose, Paramvir Bahl, Michael J. Freedman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

59 Scopus citations

Abstract

Video cameras are pervasively deployed for security and smart city scenarios, with millions of them in large cities worldwide. Achieving the potential of these cameras requires efficiently analyzing the live videos in real-time. We describe VideoStorm, a video analytics system that processes thousands of video analytics queries on live video streams over large clusters. Given the high costs of vision processing, resource management is crucial. We consider two key characteristics of video analytics: resource-quality tradeoff with multi-dimensional configurations, and variety in quality and lag goals. VideoStorm’s offline profiler generates query resource-quality profile, while its online scheduler allocates resources to queries to maximize performance on quality and lag, in contrast to the commonly used fair sharing of resources in clusters. Deployment on an Azure cluster of 101 machines shows improvement by as much as 80% in quality of real-world queries and 7× better lag, processing video from operational traffic cameras.

Original languageEnglish (US)
Title of host publicationProceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017
PublisherUSENIX Association
Pages377-392
Number of pages16
ISBN (Electronic)9781931971379
StatePublished - Jan 1 2017
Event14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017 - Boston, United States
Duration: Mar 27 2017Mar 29 2017

Publication series

NameProceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017

Conference

Conference14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017
CountryUnited States
CityBoston
Period3/27/173/29/17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Networks and Communications

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  • Cite this

    Zhang, H., Ananthanarayanan, G., Bodik, P., Philipose, M., Bahl, P., & Freedman, M. J. (2017). Live video analytics at scale with approximation and delay-tolerance. In Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017 (pp. 377-392). (Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2017). USENIX Association.