P
Peter Bodik
Researcher at Microsoft
Publications - 47
Citations - 4718
Peter Bodik is an academic researcher from Microsoft. The author has contributed to research in topics: Cloud computing & Analytics. The author has an hindex of 25, co-authored 46 publications receiving 3954 citations. Previous affiliations of Peter Bodik include University of California, Berkeley.
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Proceedings ArticleDOI
Distributed regression: an efficient framework for modeling sensor network data
TL;DR: An evaluation of the algorithm based upon data from a 48-node sensor network deployment at the Intel Research - Berkeley Lab is presented, demonstrating that the distributed algorithm converges to the optimal solution at a fast rate and is very robust to packet losses.
Journal ArticleDOI
Real-Time Video Analytics: The Killer App for Edge Computing
Ganesh Ananthanarayanan,Paramvir Bahl,Peter Bodik,Krishna Chintalapudi,Matthai Philipose,Lenin Ravindranath,Sudipta N. Sinha +6 more
TL;DR: A geographically distributed architecture of public clouds and edges that extend down to the cameras is the only feasible approach to meeting the strict real-time requirements of large-scale live video analytics.
Proceedings ArticleDOI
Chameleon: scalable adaptation of video analytics
TL;DR: Chameleon is a controller that dynamically picks the best configurations for existing NN-based video analytics pipelines, demonstrating that compared to a baseline that picks a single optimal configuration offline, Chameleon can achieve 20-50% higher accuracy with the same amount of resources, or achieve the same accuracy with only 30--50% of the resources.
Proceedings ArticleDOI
Jockey: guaranteed job latency in data parallel clusters
TL;DR: Jockey provides latency SLOs for data parallel jobs written in SCOPE and dynamically adjusts resource allocation in the shared cluster in order to maximize the job's economic utility while minimizing its impact on the rest of the cluster.
Proceedings Article
Live video analytics at scale with approximation and delay-tolerance
Haoyu Zhang,Ganesh Ananthanarayanan,Peter Bodik,Matthai Philipose,Paramvir Bahl,Michael J. Freedman +5 more
TL;DR: VideoStorm is described, a video analytics system that processes thousands of video analytics queries on live video streams over large clusters, considering two key characteristics of video Analytics: resource-quality tradeoff with multi-dimensional configurations, and variety in quality and lag goals.