{"repo":"banksemi/mpquic-rl","free":true,"listed":false,"github":"https://github.com/banksemi/mpquic-rl","clone":"git clone https://github.com/banksemi/mpquic-rl.git","description":"Reinforcement Learning-based Multipath QUIC Scheduler for Multimedia Streaming","language":"Go","stars":23,"topics":["go","mpquic","quic","scheduler"],"license":null,"category":"workflow-automation","readme_excerpt":"Multipath QUIC RL Scheduler Reinforcement Learning Based Multipath QUIC Scheduler for Multimedia Streaming - Seunghwa Lee, and Joon Yoo. - Sensors 22.17 (2022): 6333. - https://doi.org/10.3390/s22176333 Summary This project implements a reinforcement learning-based scheduler to optimize the performance of Dynamic Adaptive Streaming over HTTP (DASH) in Multipath QUIC (MPQUIC). The testbed is constructed based on MAppLE. The main components of the MAppLE platform are as follows: - Caddy : A web server supporting QUIC - AStream : Python-based DASH performance measurement framework - quic-proxy : A proxy that processes HTTP requests from the Python DASH client based on quic-go - quic-go : MPQUIC integration in a QUIC-based fork Here, the quic-go implementing MPQUIC uses the quic-go from the Peekaboo Repository. Therefore, ECF, BLEST, and Peekaboo can be tested in a DASH environment. Finally, we added a reinforcement learning scheduler implementation that considers chunk information and the client's buffer status. References - MAppLE : https://github.com/vuva/MAppLE - AStream : https://github.com/pari685/AStream - Peekaboo : https://ieeexplore.ieee.org/document/9110610 Environment Setup We simplified the experimental environment configuration using Docker, allowing the test environment to be built regardless of the Linux kernel version. (It was tested on Ubuntu 18 in the original paper.) 1. Run Docker Compose You can build and run the containers using the command below. This proce","default_branch":null,"files":null,"tree":[],"storefront":"/r/banksemi","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/banksemi/mpquic-rl/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}