BBR2

A combined team from ESnet and Lehigh University was awarded the best paper for Exploring the BBRv2 Congestion Control Algorithm for use on Data Transfer Nodes at the 8th IEEE/ACM International Workshop on Innovating the Network for Data-Intensive Science (INDIS 2021), which was held in conjunction with the 2021 IEEE/ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SC21) on Monday, November 15, 2021.

The team was comprised of:

Brian Tierney, Energy Sciences Network (ESnet)
Eli Dart, Energy Sciences Network (ESnet)
Ezra Kissel, Energy Sciences Network (ESnet)
Eashan Adhikarla, Lehigh University

The paper can be found here. Slides from the presentation are here. In this Q+A, ESnet spoke with the award-winning team about their research — answers are from the team as a whole.

The paper is based on extensive testing and controlled experiments with the BBR (Bottleneck Bandwidth and Round-trip propagation time), BBRv2 and the Cubic Function Binary Increase Congestion Control (CUBIC) Transmission Control Protocol (TCP) Internet congestion algorithms. What was the biggest lesson from this testing?

BBRv2 represents a fundamentally different approach to TCP congestion control. CUBIC (as well as Hamilton, Reno, and many others) are loss-based, meaning that they interpret packet loss as congestion and therefore require significant network engineering effort to achieve high performance. BBRv2 is different in that it measures the network path and builds a model of the path – it then paces itself to avoid loss and queueing. In practical terms, this means that BBRv2 is resilient to packet loss in a way that CUBIC is not. This comes through loud and clear in our data.

What part of the testing was the most difficult and/or interesting?

We ran a large number of tests in a wide range of scenarios. It can be difficult to keep track of all the test configurations, so we wrote a “test harness” in python that allowed us to keep track of all the testing parameters and resulting data sets.

The harness also allowed us to better compare results collected over real-world paths to those in our testbed environments. Managing the deployment of the testing environment though containers also allowed for rapid setup and improved reproducibility.

You provide readers with links to great resources so they can do their own testing and learn more about BBRv2. What do you hope readers will learn?

We hope others will test BBRv2 in high-performance research and education environments. There are still some things that we don’t fully understand, for example there are some cases where CUBIC outperforms BBRv2 on paths with very large buffers. It would be great for this to be better characterized, especially in R&E network environments.

What’s the next step for ESnet research into BBRv2? How will you top things next year?

We want to further explore how well BBRv2 performs at 100G and 400G. We would also like to spend additional time performing a deeper analysis of the current (and newly generated) results to gain insights into how BBRv2 performs compared to other algorithms across varied networking infrastructure. Ideally we would like to provide strongly substantiated recommendations on where it makes sense to deploy BBRv2 in the context of research and educational network applications.

ESnet’s first 40 Gb/s public data transfer node (DTN) has been deployed and is now available for community testing. This new DTN is the first of a new generation of publicly available networking test units, provided by ESnet to the global research and engineering network community as part of promoting high-speed scientific data mobility. This 40G DTN will provide four times the speed of previous-generation DTN test units, as well as the opportunity to test a variety of network transfer tools and calibrated data sets.

The 40G DTN server, located at ESnet’s El Paso location, is based on an updated reference implementation of our Science DMZ architecture. This new DTN (and others that will soon follow in other locations) will allow our collaborators throughout the global research and engineering network community to test high speed, large, demanding data transfers as part of improving their own network performance. The deployment provides a resource enabling the global science community to reach levels of data networking performance first demonstrated in 2017 as part of the ESnet Petascale DTN project.

The El Paso 40G DTN has Globus installed for gridFTP and parallel file transfer testing. Additional data transfer applications may be installed in the future. To facilitate user evaluation of their own network capabilities ESnet Data Mobility Exhibition (DME), test data sets will be loaded on this new 40G DTN shortly.

All ESnet DTN public servers can be found at https://app.globus.org/file-manager. ESnet will continue to support existing 10G DTNs located at Sunnyvale, Starlight, New York, and CERN.

ESnet's 40G DTN Reference Architecture Block Diagram — ESnet’s 40G DTN Reference Architecture Block Diagram

The full 40G DTN Reference architecture and more information on the design of these new DTN can be found here:

A second 40G DTN will be available in the next few weeks, and will be deployed in Boston. It will feature Google’s bottleneck bandwidth and round-trip propagation time (BBR2) software, allowing improved round-trip-time measurement and the ability for users to explore BBR2 enhancements to standard TCP congestion control algorithms.

In an upcoming blog post, I will describe the Boston/BBR2-enabled 40G DTN and perfSONAR servers. In the meantime, ESnet and the deployment team hope that the new El Paso DTN will be of great use to the global research community!