Enabling High Quality Real-Time Communications with Adaptive Frame-Rate


Zili Meng, Tsinghua University and Tencent Inc.; Tingfeng Wang, Tsinghua University, Tencent Inc., and Beijing University of Posts and Telecommunications; Yixin Shen, Tsinghua University; Bo Wang and Mingwei Xu, Tsinghua University and Zhongguancun Laboratory; Rui Han and Honghao Liu, Tencent Inc.; Venkat Arun, Massachusetts Institute of Technology; Hongxin Hu, University at Buffalo, SUNY; Xue Wei, Tencent Inc.


Emerging high quality real-time communication (RTC) applications stream ultra-high-definition (UHD) videos with high frame rate (HFR). They use edge computing, which enables high bandwidth and low latency streaming. Our measurements, from the cloud gaming platform of one of the largest gaming companies, show that, in this setting, the client-side decoder is often the cause for high latency that hurts user's experience. We therefore propose an Adaptive Frame Rate (AFR) controller that helps achieve ultra-low latency by coordinating the frame rate with network fluctuation and decoder capacity. AFR's design addresses two key challenges: (1) queue measurements do not provide timely feedback for the control loop and (2) multiple factors control the decoder queue, and different actions must be taken depending on why the queue accumulates. Trace-driven simulations and large-scale deployments in the wild demonstrate that AFR can reduce the tail queuing delay by up to 7.4× and the stuttering events measured by end-to-end delay by 34% on average. AFR has been deployed in production in our cloud gaming service for over one year.

NSDI '23 Open Access Sponsored by
King Abdullah University of Science and Technology (KAUST)

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This content is available to:

@inproceedings {285056,
author = {Zili Meng and Tingfeng Wang and Yixin Shen and Bo Wang and Mingwei Xu and Rui Han and Honghao Liu and Venkat Arun and Hongxin Hu and Xue Wei},
title = {Enabling High Quality {Real-Time} Communications with Adaptive {Frame-Rate}},
booktitle = {20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23)},
year = {2023},
isbn = {978-1-939133-33-5},
address = {Boston, MA},
pages = {1429--1450},
url = {https://www.usenix.org/conference/nsdi23/presentation/meng},
publisher = {USENIX Association},
month = apr,
Meng Paper (Prepublication) PDF

Presentation Video