Experience-driven congestion control: When multi-path TCP meets deep reinforcement learning

Z Xu, J Tang, C Yin, Y Wang… - IEEE Journal on Selected …, 2019 - ieeexplore.ieee.org
In this paper, we aim to study networking problems from a whole new perspective by
leveraging emerging deep learning, to develop an experience-driven approach, which …

Improving TCP congestion control with machine intelligence

Y Kong, H Zang, X Ma - Proceedings of the 2018 Workshop on Network …, 2018 - dl.acm.org
In a TCP/IP network, a key to ensure efficient and fair sharing of network resources among
its users is the TCP congestion control (CC) scheme. Previously, the design of TCP CC …

DeepCC: Multi-agent deep reinforcement learning congestion control for multi-path TCP based on self-attention

B He, J Wang, Q Qi, H Sun, J Liao, C Du… - … on Network and …, 2021 - ieeexplore.ieee.org
With the development of the Internet of Things (IoT) and 5G, there are ubiquitous smart
devices and network functions providing emerging network services efficiently and optimally …

{PCC} vivace:{Online-Learning} congestion control

M Dong, T Meng, D Zarchy, E Arslan, Y Gilad… - … USENIX Symposium on …, 2018 - usenix.org
TCP's congestion control architecture suffers from notoriously bad performance.
Consequently, recent years have witnessed a surge of interest in both academia and …

A software defined network based fuzzy normalized neural adaptive multipath congestion control for the internet of things

F Naeem, G Srivastava, M Tariq - IEEE transactions on network …, 2020 - ieeexplore.ieee.org
Multipath Transmission Control Protocol (MPTCP) enables multi-homed devices to establish
multiple simultaneous routes for data transmission. Congestion Control (CC) is a …

TCP-Drinc: Smart congestion control based on deep reinforcement learning

K Xiao, S Mao, JK Tugnait - IEEE Access, 2019 - ieeexplore.ieee.org
As wired/wireless networks become more and more complex, the fundamental assumptions
made by many existing TCP variants may not hold true anymore. In this paper, we develop a …

Dynamic TCP initial windows and congestion control schemes through reinforcement learning

X Nie, Y Zhao, Z Li, G Chen, K Sui… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
Despite many years of improvements to it, TCP still suffers from an unsatisfactory
performance. For services dominated by short flows (eg, web search and e-commerce), TCP …

QTCP: Adaptive congestion control with reinforcement learning

W Li, F Zhou, KR Chowdhury… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Next generation network access technologies and Internet applications have increased the
challenge of providing satisfactory quality of experience for users with traditional congestion …

{PCC}: Re-architecting congestion control for consistent high performance

M Dong, Q Li, D Zarchy, PB Godfrey… - 12th USENIX Symposium …, 2015 - usenix.org
TCP and its variants have suffered from surprisingly poor performance for decades. We
argue the TCP family has little hope of achieving consistent high performance due to a …

Eagle: Refining congestion control by learning from the experts

S Emara, B Li, Y Chen - IEEE INFOCOM 2020-IEEE Conference …, 2020 - ieeexplore.ieee.org
Traditional congestion control algorithms were designed with a hardwired heuristic mapping
between packet-level events and predefined control actions in response to these events …