RAN information-assisted TCP congestion control via DRL with reward redistribution
In this paper, we aim to propose a novel transmission control protocol (TCP) congestion
control method from a crosslayer-based perspective and present a deep reinforcement …
control method from a crosslayer-based perspective and present a deep reinforcement …
RAN information-assisted TCP congestion control using deep reinforcement learning with reward redistribution
M Chen, R Li, J Crowcroft, J Wu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this paper, we aim to propose a novel transmission control protocol (TCP) congestion
control method from a cross-layer-based perspective and present a deep reinforcement …
control method from a cross-layer-based perspective and present a deep reinforcement …
RLCC: practical learning-based congestion control for the internet
Z Xia, J Wu, L Wu, J Yuan, J Zhang… - … Joint Conference on …, 2021 - ieeexplore.ieee.org
With the networks becoming complex, traditional congestion control protocols face
increasing challenges in providing high-quality services for users. Traditional TCP and its …
increasing challenges in providing high-quality services for users. Traditional TCP and its …
Towards AI-enabled traffic management in multipath TCP: A survey
Numerous applications on the web use transmission control protocol (TCP) as a transport
protocol to ensure efficient and fair sharing of network resources among users. With the …
protocol to ensure efficient and fair sharing of network resources among users. With the …
Experience-driven congestion control: When multi-path TCP meets deep reinforcement learning
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 …
leveraging emerging deep learning, to develop an experience-driven approach, which …
TCP congestion control with multiagent reinforcement and transfer learning
TCP congestion control, although prevalently used in network technologies, is not optimal
for video streaming applications. High throughput and low latency requirements of video …
for video streaming applications. High throughput and low latency requirements of video …
TCP-PPCC: Online-learning proximal policy for congestion control
J Li, Y Guan, P Ding, S Wang - 2020 21st Asia-Pacific Network …, 2020 - ieeexplore.ieee.org
Effective network congestion control strategies are the key to secure the normal operation of
complex and changeable networks. The fundamental assumptions of many existing TCP …
complex and changeable networks. The fundamental assumptions of many existing TCP …
Towards fair and efficient learning-based congestion control
Recent years have witnessed a plethora of learning-based solutions for congestion control
(CC) that demonstrate better performance over traditional TCP schemes. However, they fail …
(CC) that demonstrate better performance over traditional TCP schemes. However, they fail …
DRLFcc: Deep Reinforcement Learning-empowered Congestion Control Mechanism for TCP Fast Recovery in High Loss Wireless Networks
TCP is currently the most widely used Internet transmission protocol, which is extensively
applied to applications on the Internet to enable reliable data transmission. The TCP …
applied to applications on the Internet to enable reliable data transmission. The TCP …
MA-CC: Cross-Layer Congestion Control via Multi-agent Reinforcement Learning
Deep reinforcement learning (DRL) injects vigorous vitality into congestion control (CC) to
efficiently utilize network capacity for Internet communication applications. Existing methods …
efficiently utilize network capacity for Internet communication applications. Existing methods …