~/talk

From Source to Solution: Tackling Packet Losses in Large-scale Cloud Gaming...

Talkat NSDI '26 · 2026-05-04..05-06· [networking, web-performance]
name:Jing Wang
links:none on file
name:Xiao Kong
links:none on file
name:Yunzhe Ni
links:none on file
name:Nian Wen
links:none on file
links:none on file
links:none on file
links:none on file
slides:none on file

Production measurements on Tencent START (≈200,000 hours) show 66.5% of losses arise from network bias against UDP and congestion; LADR implements a TCP-first multi-connection proxy, combines delay-based Pega with a loss-based bitrate controller (LBBC), and replaces receiver NACK with sender-side SACK/RACK-TLP plus opportunistic FEC and reactive rate limiting. Deployed for a year, LADR reports 0.049% packet loss (−59.8% vs. prior) and delivers 99.87% of frames within 100 ms.

AI-written summary · about

  1. 0:00Cloud gaming packet losses
  2. 1:01Loss detection and recovery
  3. 2:49Production stack and measurements
  4. 4:34WebRTC assumptions revisited
  5. 5:39Transport protocol choice and TCP
  6. 6:40Congestion control for shallow buffers
  7. 7:22Loss detection timing and SACK
  8. 8:25FEC limitations and recovery
  9. 9:06Designing LADAR with loss sources
  10. 10:12Multi-connection transport with proxy
  11. 11:14Production results and tail reduction
  12. 13:45Summary and research context
  13. 15:32Acknowledgments
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