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Puffer Puffer is a research project in the computer science department at Stanford University Please find more details in the FAQ and our research paper (USENIX NSDI '20 Community Award, IRTF Applied Networking Research Prize '21)
Puffer - Stanford University If you believe your copyright has been violated on a Stanford site, please notify puffer-copyright-notices [at] cs stanford edu and give notice as stated under Reporting of Alleged Copyright Infringement
Puffer - Stanford University Along with our research paper, we are publishing anonymized data collected on Puffer for the research community to investigate As our experiments are ongoing, new data is collected each day
Puffer - Stanford University Puffer is a Stanford University research study about using machine learning to improve video-streaming algorithms: the kind of algorithms used by services such as YouTube, Netflix, and Twitch
Learning in situ: a randomized experiment in video streaming Puffer encodes each video chunk in ten different H 264 versions, using libx264 in veryfast mode The encodings range from 240p60 video with constant rate factor (CRF) of 26 (about 200 kbps) to 1080p60 video with CRF of 20 (about 5,500 kbps)
Puffer - Stanford University Performance of both versions of BOLA-BASIC on Puffer (95% confidence intervals), for all stream speeds (top plot) and slow streams only (bottom plot) Both plots show data from 2020-07-26 to 2020-11-07 (see the Experiment Results page for latest data)
Puffer - Stanford University Selected date (UTC): 2025-12-06T11_2025-12-07T11 (share a permalink) Full results: Storage bucket Retrained model: 20251206-1 tar gz video_sent measurement: video