Name
Abstract | ||
|---|---|---|
In 2016, Google proposed and deployed a new TCP variant called BBR. BBR represents a major departure from traditional congestion control as it uses estimates of bandwidth and round-trip delays to regulate its sending rate. BBR has since been introduced in the upstream Linux kernel and deployed by Google across its data centers. Since the last major study to identify TCP congestion control variants on the Internet was done before BBR, it is timely to conduct a new census to give us a sense of the current distribution of congestion control variants on the Internet. To this end, we designed and implemented Gordon, a tool that allows us to measure the congestion window (cwnd) corresponding to each successive RTT in the TCP connection response of a congestion control algorithm. To compare a measured flow to the known variants, we created a localized bottleneck and introduced a variety of network changes like loss events, changes in bandwidth and delay, while normalizing all measurements by RTT. We built an offline classifier to identify the TCP variant based on the cwnd trace over time.
Our results suggest that CUBIC is currently the dominant TCP variant on the Internet, and is deployed on about 36% of the websites in the Alexa Top 20,000 list. While BBR and its variant BBR G1.1 are currently in second place with a 22% share by website count, their present share of total Internet traffic volume is estimated to be larger than 40%. We also found that Akamai has deployed a unique loss-agnostic rate-based TCP variant on some 6% of the Alexa Top 20,000 websites and there are likely other undocumented variants. Therefore, the traditional assumption that TCP variants ''in the wild'' will come from a small known set is not likely to be true anymore. Our results suggest that some variant of BBR seems poised to replace CUBIC as the next dominant TCP variant on the Internet.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3393691.3394221 | SIGMETRICS '20: ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems
Boston
MA
USA
June, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-7985-4 | 1 |
PageRank | References | Authors |
0.36 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ayush Mishra | 1 | 2 | 0.73 |
| Xiangpeng Sun | 2 | 2 | 0.73 |
| Atishya Jain | 3 | 1 | 0.36 |
| Sameer Pande | 4 | 1 | 0.36 |
| Raj Joshi | 5 | 5 | 2.84 |
| Ben Leong | 6 | 343 | 27.92 |