~/talk

Medley: Optimizing Midgress Bandwidth for Commercial Live Streaming CDNs

on YouTube 16m
Talkat NSDI '26 · 2026-05-04..05-06· [networking]

speakers

name:Haiping Wang
links:none on file
name:Wanxin Shi
links:none on file
name:Sandesh Dhawaskar Sathyanarayana
links:none on file
name:Shu Shi
links:none on file
name:Feng Qian
linkedin:fqian
name:Yinghao Yang
links:none on file
name:La Zuo
links:none on file
name:Hebin Yu
links:none on file
name:Ruixiao Zhang
links:none on file
name:Ruoshi Sun
links:none on file
name:Yajie Peng
links:none on file
name:Xiaofei Pang
links:none on file
name:Ruili Fang
links:none on file
name:Zhenpeng Zhu
links:none on file
name:Weiqi Chen
links:none on file
name:Yang Xu
links:none on file

resources

video:https://youtu.be/o17bWCav_vo
slides:none on file

summary

Medley implements a substream-based CDN that splits each live video into k substreams so each edge node caches 1/k of the stream, claiming a 76.83% midgress bandwidth reduction in production. A utility-driven K scaling component adjusts k in real time trading midgress gain vs. overhead; a hybrid scheduler assigns frames by type and size to avoid I-frame overload; and first-go isolation and fast request recover missing substreams. Deployed at ByteDance, it handles ~0.85M concurrent viewing requests per minute in live traffic.

AI-written summary · about

chapters (10)

  1. 0:00Medley and live streaming CDN
  2. 2:25Midgress traffic and costs
  3. 3:30Midgress waste in CDNs
  4. 6:39Medley’s substring splitting
  5. 8:50Implementing Medley challenges
  6. 10:14Dynamic substring scaling
  7. 11:18Balancing frame distribution
  8. 13:07Mitigating subscreen blocking
  9. 14:14Production results and savings
  10. 15:20Key takeaways and future

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