It is challenging to deal with the Internet congestion problem because of several factors such
as ever-growing traffic and distributed network architecture. The congestion problem can be …

This article focuses on the machine learning (ML) technologies for Internet congestion
control. Specifically, it summarizes the main reasons why network operators should apply …

Learning-based Internet congestion control algorithms have attracted much attention due to
their potential performance improvement over traditional algorithms. However, such …

Decades of research on Internet congestion control (CC) have produced a plethora of
algorithms that optimize for different performance objectives. Applications face the challenge …

The advent of new network architectures has resulted in the rise of network applications with
different network performance requirements: live video streaming applications require low …

End-to-end congestion control has been extensively studied for over 30 years as one of the
most important mechanisms to ensure efficient and fair sharing of network resources among …

These days, taking the revolutionary approach of using clean-slate learning-based designs
to completely replace the classic congestion control schemes for the Internet is gaining …

Most congestion control algorithms (CCAs) are designed for specific network environments.
As such, there is no known algorithm that achieves uniformly good performance in all …

The Internet has existed since the 1970s as a means of data exchange between network
devices in small networks. In the early stage, there was a small number of devices, but today …

This paper presents a survey on the emerging approaches to the end-to-end congestion
control (EECC) in modern Internet. The actual mechanisms are inefficient in the operational …