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

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.