Keeping an Eye on Congestion Control in the Wild with Nebby

被引:1
作者
Mishra, Ayush [1 ]
Rastogi, Lakshay [2 ]
Joshi, Raj [1 ]
Leong, Ben [1 ]
机构
[1] Natl Univ Singapore, Singapore, Singapore
[2] Indian Inst Technol, Kanpur, Uttar Pradesh, India
来源
PROCEEDINGS OF THE 2024 ACM SIGCOMM 2024 CONFERENCE, ACM SIGCOMM 2024 | 2024年
关键词
congestion control; measurement study; HIGH-SPEED; TCP; ALGORITHM;
D O I
10.1145/3651890.3672223
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Internet congestion control landscape is rapidly evolving. Since the introduction of BBR and the deployment of QUIC, it has become increasingly commonplace for companies to modify and implement their own congestion control algorithms (CCAs). To respond effectively to these developments, it is crucial to understand the state of CCA deployments in the wild. Unfortunately, existing CCA identification tools are not future-proof and do not work well with modern CCAs and encrypted protocols like QUIC. In this paper, we articulate the challenges in designing a future-proof CCA identification tool and propose a measurement methodology that directly addresses these challenges. The resulting measurement tool, called Nebby, can identify all the CCAs currently available in the Linux kernel and BBRv2 with an average accuracy of 96.7%. We found that among the Alexa Top 20k websites, the share of BBR has shrunk since 2019 and that only 8% of them responded to QUIC requests. Among these QUIC servers, CUBIC and BBR seem equally popular. We show that Nebby is extensible by extending it for Copa and an undocumented family of CCAs that is deployed by 6% of the measured websites, including major corporations like Hulu and Apple.
引用
收藏
页码:136 / 150
页数:15
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