Historically, researchers developing network algorithms have had to study and test those algorithms in simulation or in small, real-world testbeds. Puffer’s secret sauce is that video is streamed over real internet connections to real users so that its algorithms can learn from live traffic in situ, not from simulated data. “So then we can learn what algorithms work best.” “The purpose of this website is to recruit people all across the country on different kinds of internet connections so that the different algorithms can learn what the real internet is like,” Winstein said. Puffer currently receives signals from NBC, CBS, ABC, PBS, FOX and Univision networks from an antenna perched atop the Packard Electrical Engineering Building. The website allows users –– whom Puffer’s researchers call “academic study participants” –– to create an account and watch live cable television on their computers, ad-free and at no cost.
#Projecting live visuals free#
Yan and his team built a live cable television streaming platform, which is available to the public free of charge. While Puffer is, first and foremost, an academic exploration and by no means a commercial endeavor, the Puffer team launched a quasi-product to gather data for research. Puffer’s algorithm is unique in its ability to learn continuously from a real-world environment, compared to existing algorithms which are only trained once and learn from a simulation of data. The paper revealed that the new video-streaming algorithm developed by Yan delivers a significantly better quality of video-streaming experience compared to prior algorithms. Because the paper was submitted anonymously, the name of the conference has been withheld. The Puffer research team recently submitted a paper evaluating the preliminary results of their research to a well-known computer science conference. The team, advised by Keith Winstein and Phil Levis, is conducting research in an attempt to eliminate the thorns that often plague online video. He leads a team comprised of fellow doctoral students Sadjad Fouladi and Hudson Ayers and Tsinghua University student Chenzhi Zhu. Francis Yan, a Stanford computer science doctoral student, developed a research project known as Puffer to test existing algorithms and train novel ones to improve the quality of video streaming. Ever been frustrated about how long it takes for your Netflix episode to buffer or how blurry the resolution of your YouTube video is?Ī team of computer science researchers at Stanford think they can ameliorate video-streaming standards.