Congestion control for real-time media over QUIC

Engelbart, Mathis; Ott, Jörg

doi:10.1145/3488660.3493801

Cited by 13 publications

(1 citation statement)

References 21 publications

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“…In a follow-up work Mondal and Chakraborty (2020), the authors have shown that the stream multiplexing over the same UDP buffer creates a problem for DASH video and audio channels to synchronize, thus resulting in poor performance. In Engelbart and Ott (2021), the authors have shown that QUIC congestion control needs to be tuned for supporting QoE for multimedia traffic. In the same line, a few other works Palmer et al (2018); Arisu and Begen (2018); Van et al (2018); Perkins and Ott (2018); ; Lorenzi et al (2021) in the literature has also adopted the QUIC protocol to support better streaming performance; however, these works have not fundamentally looked within the interplay between DASH and QUIC instead used QUIC as a service.…”

Section: Adaptive Bitrate Streaming Over Http/3mentioning

confidence: 99%

YouTube over Google's QUIC vs Internet Middleboxes: A Tug of War between Protocol Sustainability and Application QoE

Chaudhary¹,

Sachdeva²,

Mondal³

et al. 2022

Preprint

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Middleboxes such as web proxies, firewalls, etc. are widely deployed in today's network infrastructure. As a result, most protocols need to adapt their behavior to co-exist. One of the most commonly used transport protocols, QUIC, adapts to such middleboxes by falling back to TCP, where they block it. In this paper, we argue that the blind fallback behavior of QUIC, i.e., not distinguishing between failures caused by middleboxes and that caused by network congestion, hugely impacts the performance of QUIC. For this, we focus on YouTube video streaming and conduct a measurement study by utilizing production endpoints of YouTube by enabling TCP and QUIC at a time. In total, we collect over 2600 streaming hours of data over various bandwidth patterns, from 5 different geographical locations and various video genres. To our surprise, we observe that the legacy setup (TCP) either outperforms or performs the same as the QUIC-enabled browser for more than 60% of cases. We see that our observation is consistent across individual QoE parameters, bandwidth patterns, locations, and videos. Next, we conduct a deep-dive analysis to discover the root cause behind such behavior. We find a good correlation (0.3 − 0.7) between fallback and QoE drop events, i.e., quality drop and re-buffering or stalling. We further perform Granger causal analysis and find that fallback Granger causes either quality drop or stalling for 70% of the QUIC-enabled sessions. We believe our study will help designers revisit the decision to enable fallback in QUIC and distinguish between the packet drops caused by middleboxes and network congestion.

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