PCC Vivace: Online-Learning Congestion Control

By Mo Dong, Tong Meng, Doron Zarchy, Engin Arslan, Yossi Gilad, Brighten Godfrey, Michael Schapira. Symposium on Networked Systems Design and Implementation, 2018

418 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/97e7a468dea46c4233ff353d3021da15a979494d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Venkat Arun
2. Nathan H. Jay
3. Noga H. Rotman
4. Brighten Godfrey
5. Michael Schapira
6. Aviv Tamar
7. Hari Balakrishnan
8. Sergey Levine

Citations in the corpus

• Copa: Practical Delay-Based Congestion Control for the Internet (2018, methodology): “A fourth, and most recent, thread of end-to-end congestion control research has argued that the space of congestion control signals and actions is too complicated for human engineering, and that algorithms can produce better actions than humans (e.g., Remy [37, 43], PCC [9], and PCC-Vivace [10]).”
• A Deep Reinforcement Learning Perspective on Internet Congestion Control (2019, methodology): “Our model achieves near-perfect link utilization at all capacities, with latency far below TCP, and comparable to PCC-Vivace.”