用 Machine Learning 改善 Streaming 品質的服務與論文

Hacker News 上看到「Puffer」這個服務,裡面利用了 machine learning algorithm 動態調整 bitrate,以提昇傳輸品質。

測試得到的數據後來被整理起來一起放進論文:「Continual learning improves Internet video streaming」。

在開頭介紹了 Fugu 這個演算法:

We describe Fugu, a continual learning algorithm for bitrate selection in streaming video.

而 Puffer 就是實驗網站:

We evaluate Fugu with Puffer, a public website we built that streams live TV using Fugu and existing algorithms. Over a nine-day period in January 2019, Puffer streamed 8,131 hours of video to 3,719 unique users.

這個站台提供了許多真實的頻道進行測試:

Stream live TV in your browser. There's no charge. You can watch U.S. TV stations affiliated with the NBC, CBS, ABC, PBS, FOX, and Univision networks.

可以看到 Fugu 的結果很好,比起其他提出的方案是全面性的改善:

這邊是用 WebSocket 測試,並且配合了不同的 TCP congestion algorithm,沒有太考慮額外的計算成本...

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