There are 12 repositories under congestion-control topic.
Congestion control algorithms evaluation on ns3
BBR' - An Implementation of Bottleneck Bandwidth and Round-trip Time Congestion Control for ns-3
Python package provides powerful tools for creating and managing Ideal Flow Networks (IFN). An Ideal Flow Network is a strongly connected network where the flows are balanced.
Implementation of the paper "LFQ: Online Learning of Per-Flow Queuing Policies Using Deep Reinforcement Learning", Contact: Maximilian Bachl
Framework for high-performance streaming over message-passing systems. High-performance WAN protocols over UDP datagrams. Implemented in golang.
deprecated. move to https://github.com/q191201771/lalext
📜 [NeurIPS 2022] "Symbolic Distillation for Learned TCP Congestion Control", S P Sharan, Wenqing Zheng, Kuo-Feng Hsu, Jiarong Xing, Ang Chen, Zhangyang Wang
Linux Kernel Module TCP/IP pacing (rate based) congestion control for Linux video streaming/data servers or workstations. It can work better, than BBR from Google. You may use it instead of default Cubic for Linux data servers (and both it makes data uploading faster for Linux Workstations too, so feel faster Internet for your Linux Workstation). Compatible with Kernels 4.x+ or 3.x.
🪗 Dynamic congestion-based concurrency limits for controlling backpressure
Framework for testing Active Queue Management (AQM) and congestion control implementations
Reliable file transfer using unreliable User Datagram protocol
A Deadline-Aware, Incentive-Compatible and Proportionally-Fair Mechanism for EV Charging in Distribution Grids
Reliable Transport Protocol (TCP) implementation using unreliable delivery mechanism.
Cocoa is a qdisc which maximizes throughput for each flow while keeping the buffer minimal. Contact: Maximilian Bachl.
Reinforcement Learning environment for Congestion Control with ContainerNet
TCP simplified implementation with congestion control and congestion avoidance.
DRL in Network Congestion Control. Completion of the A3C implementation of Indigo based on the original Indigo codes. Tested on Pantheon.
Code written for Networks Lab in the 5th Semester
BUET CSE L3T2 Computer Networks Project
An attempt of our team to tackle the problem of traffic congestion using deep learning and IoT
Emulator for Testing Congestion Control Algorithms in a Dumbbell Network
We aimed to implement our own socket layer and reliable transport layer. So we implemented a reliable transfer service on the top of UDP/IP protocol. In other words, you need to implement a service that guarantees the arrival of datagrams in the correct order on top of the UDP/IP protocol, along with congestion control.
This project includes the implementation on TCP congestion control algorithm Elastic, and a new CCA Elmod on NS3.
Analyzed a Wireshark/TCPdump trace to characterize the TCP flows in the trace and also figured out the HTTP Versions, congestion window sizes and packet losses
Congestion control middleware components for ASPNET Core.
Includes NS-2 simulations for benchmarking between several congestion control algorithms such as DCTCP, Timely, Vegas and new ones.