Pantheon of Congestion Control
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Updated
Sep 2, 2020 - Python
Pantheon of Congestion Control
A platform to test reinforcement learning policies in the datacenter setting.
An attempt of our team to tackle the problem of traffic congestion using deep learning and IoT
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
Ideal Flow Network (IFN) is a Python module and library to compute network efficiency to analyze transportation network, communication networks and data science..
Emulator for Testing Congestion Control Algorithms in a Dumbbell Network
Framework for testing Active Queue Management (AQM) and congestion control implementations
Computer Networks Assignments
P_MUL: A Reliable Multicast Transfer Protocol
Implementation of the paper "LFQ: Online Learning of Per-Flow Queuing Policies Using Deep Reinforcement Learning", Contact: Maximilian Bachl
Implementation of Refined Adaptive RED (RARED) algorithm in ns-3-dev
Reinforcement Learning environment for Congestion Control with ContainerNet
A Deadline-Aware, Incentive-Compatible and Proportionally-Fair Mechanism for EV Charging in Distribution Grids
Chat application over TCP with file transfer over fast reliable UDP
DRL in Network Congestion Control. Completion of the A3C implementation of Indigo based on the original Indigo codes. Tested on Pantheon.
Low Extra Delay Background Transport (LEDBAT) implementation in Python3
🚦TCP Simulation, Computer Networks course, University of Tehran
Chat Box - Client-Server
Using IFN to simulate the trafiic Conditions in VIT Vellore
Implementation of Refined Adaptive RED (RARED) algorithm in ns-3.25
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