A unified congestion control framework for diverse application preferences and network conditions

Z Du, J Zheng, H Yu, L Kong, G Chen - Proceedings of the 17th …, 2021 - dl.acm.org
With the increase of diversity in application needs and networks, existing congestion control
algorithms (CCAs) do not accommodate this complicated reality. Previous classic CCAs are …

Satfed: A resource-efficient leo satellite-assisted heterogeneous federated learning framework

Y Zhang, Z Lin, Z Chen, Z Fang, W Zhu, X Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
Traditional federated learning (FL) frameworks rely heavily on terrestrial networks, where
coverage limitations and increasing bandwidth congestion significantly hinder model …

Astraea: Towards Fair and Efficient Learning-based Congestion Control

X Liao, H Tian, C Zeng, X Wan, K Chen - Proceedings of the Nineteenth …, 2024 - dl.acm.org
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 …

EdAR: An experience-driven multipath scheduler for seamless handoff in mobile networks

J Han, K Xue, J Li, R Zhuang, R Li, R Yu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Multipath TCP (MPTCP) improves the bandwidth utilization in wireless network scenarios,
since it can simultaneously utilize multiple interfaces for data transmission. However, with …

Restoring application traffic of latency-sensitive networked systems using adversarial autoencoders

A Sacco, F Esposito, G Marchetto - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The Internet of Things (IoT), coupled with the edge computing paradigm, is enabling several
pervasive networked applications with stringent real-time requirements, such as …

HINT: Supporting congestion control decisions with P4-driven in-band network telemetry

A Sacco, A Angi, F Esposito… - 2023 IEEE 24th …, 2023 - ieeexplore.ieee.org
Years of research on congestion controls have highlighted how end-to-end and in-network
protocols might perform poorly in some contexts. Recent advances in data plane network …

Partially oblivious congestion control for the internet via reinforcement learning

A Sacco, M Flocco, F Esposito… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Despite years of research on transport protocols, the tussle between in-network and end-to-
end congestion control has not been solved. This debate is due to the variance of conditions …

Real-time TCP Packet Loss Prediction Using Machine Learning

M Welzl, S Islam, M Von Stephanides - IEEE Access, 2024 - ieeexplore.ieee.org
Congestion and resulting packet loss in TCP connections can lead to performance
degradation and reduce the Quality of Experience (QoE) for end users. Many common TCP …

Towards fair and efficient learning-based congestion control

X Liao, H Tian, C Zeng, X Wan, K Chen - arXiv preprint arXiv:2403.01798, 2024 - arxiv.org
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 …

L4S Congestion Control Algorithm for Interactive Low Latency Applications over 5G

J Son, Y Sanchez, C Hampe… - … on Multimedia and …, 2023 - ieeexplore.ieee.org
In recent years, applications such as cloud gaming and virtual video conferencing have
gained increasing popularity and new applications, such as immersive applications, have …