A unified congestion control framework for diverse application preferences and network conditions
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 …
algorithms (CCAs) do not accommodate this complicated reality. Previous classic CCAs are …
Satfed: A resource-efficient leo satellite-assisted heterogeneous federated learning framework
Traditional federated learning (FL) frameworks rely heavily on terrestrial networks, where
coverage limitations and increasing bandwidth congestion significantly hinder model …
coverage limitations and increasing bandwidth congestion significantly hinder model …
Astraea: 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 …
EdAR: An experience-driven multipath scheduler for seamless handoff in mobile networks
Multipath TCP (MPTCP) improves the bandwidth utilization in wireless network scenarios,
since it can simultaneously utilize multiple interfaces for data transmission. However, with …
since it can simultaneously utilize multiple interfaces for data transmission. However, with …
Restoring application traffic of latency-sensitive networked systems using adversarial autoencoders
The Internet of Things (IoT), coupled with the edge computing paradigm, is enabling several
pervasive networked applications with stringent real-time requirements, such as …
pervasive networked applications with stringent real-time requirements, such as …
HINT: Supporting congestion control decisions with P4-driven in-band network telemetry
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 …
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 …
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
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 …
degradation and reduce the Quality of Experience (QoE) for end users. Many common 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 …
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 …
gained increasing popularity and new applications, such as immersive applications, have …