BBR v3-Cubic smackdown: A Fairness and Convergence Quantitative Evaluation

Clicks: 2
ID: 312699
2025
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #654 of 705 articles by views in Journal of Computing & Biomedical Informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Congestion control has been an important component of TCP for nearly four decades now. Bottleneck Bandwidth and Round-Trip Time (BBR) has brought a major change in the ways the congestion onset can be monitored, and proactive measures can be taken instead of a reactive technique being used in loss-based traditional algorithms, such as Cubic and Reno, for a long time. With the introduction of the latest iteration of BBR, BBR v3, it has been claimed that it has improved its co-existence with Cubic flows with better fairness, but convergence issues within BBR-v3 have been reported. No existing study quantifies BBR v3's fairness with Cubic, and the convergence of BBR v3 for intra-protocol streams needs to be quantified for each stream’s throughput as well. The simulations and emulations generally don’t bring the true picture of the performance of a congestion control algorithm. In this paper, we have evaluated BBR v3 with cubic using our real-time physical testbed using Jain’s Fairness Index to bring a more accurate fairness analysis of BBR v3 and Cubic streams. For convergence, a well-established statistical metric that measures the relative stability of throughput, known as the Coefficient of Variation (CoV), has been calculated for BBR v3/Cubic flows. We used Flent (a FLExible Network Tester) to perform rigorous tests using various pairs of streams in upload, and the results, along with the metadata, have been saved for reproducibility and validation. Our thorough testing on both wired (Ethernet) and wireless (Wi-Fi 4) testbeds confirms that fairness issues between BBR v3 and Cubic streams persist. These issues are particularly serious as the number of streams increases. Similarly, our convergence tests confirm that BBR v3 flows, especially the first stream, obtain a larger share of the bandwidth, and the throughput of each stream remains highly volatile.
Reference Key
imported_1777056110_69ebb96eac652 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Raybal Akhtar
Journal Journal of Computing & Biomedical Informatics
Year 2025
DOI
DOI not found
URL
https://jcbi.org/index.php/Main/article/view/1079
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.