Francis Y. Yan, Jestin Ma, and Greg D. Hill, Stanford University; Deepti Raghavan, Massachusetts Institute of Technology; Riad S. Wahby, Philip Levis, and Keith Winstein, Stanford University
Awarded Best Paper!
Internet transport algorithms are foundational to the performance of network applications. But a number of practical challenges make it difficult to evaluate new ideas and algorithms in a reproducible manner. We present the Pantheon, a system that addresses this by serving as a community "training ground" for research on Internet transport protocols and congestion control (https://pantheon.stanford.edu). It allows network researchers to benefit from and contribute to a common set of benchmark algorithms, a shared evaluation platform, and a public archive of results.
We present three results showing the Pantheon's value as a research tool. First, we describe a measurement study from more than a year of data, indicating that congestion-control schemes vary dramatically in their relative performance as a function of path dynamics. Second, the Pantheon generates calibrated network emulators that capture the diverse performance of real Internet paths. These enable reproducible and rapid experiments that closely approximate real-world results. Finally, we describe the Pantheon's contribution to developing new congestion-control schemes, two of which were published at USENIX NSDI 2018, as well as data-driven neural-network-based congestion-control schemes that can be trained to achieve good performance over the real Internet.
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author = {Francis Y. Yan and Jestin Ma and Greg D. Hill and Deepti Raghavan and Riad S. Wahby and Philip Levis and Keith Winstein},
title = {Pantheon: the training ground for Internet congestion-control research},
booktitle = {2018 USENIX Annual Technical Conference (USENIX ATC 18)},
year = {2018},
isbn = {978-1-939133-01-4},
address = {Boston, MA},
pages = {731--743},
url = {https://www.usenix.org/conference/atc18/presentation/yan-francis},
publisher = {USENIX Association},
month = jul
}