This repository contains the HAS testbed for MEDUSA, a novel distributed ABR technique for VoD applications, selecting the appropriate codec for each user and video segment (on a per-segment basis in the outmost case), refining the selection of the ABR algorithms by exploiting key metrics, such as the perceived segment quality and size. The experimental results show that our proposed method can increase the QoE score of up to 42% according to the ITU-T P.1203 model (mode 0). Additionally, MEDUSA can reduce the transmitted data volume by up to more than 40% achieving a QoE similar to the techniques compared, reducing the burden on streaming service providers for delivery costs.
- Python
- itu-t-p1203 module
- itu-t-p1203-codec-extension module
- Clone this repository
- Run the testbed with CAdViSE
- Wait for the streaming session to be completed
- Check the ITU-T P.1203 compliant JSON files containing the QoE score of the streaming session for each selected client
If you use this source code in your research, please cite
- Include the link to this repository
- Cite the following publication
Lorenzi, D., Tashtarian, F., Timmerer, C., and, Hellwagner, H., "MEDUSA: A Dynamic Codec Switching Approach in HTTP Adaptive Streaming", In ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2024.
@article{lorenzi2024medusa,
title={MEDUSA: A Dynamic Codec Switching Approach in HTTP Adaptive Streaming},
author={Lorenzi, Daniele and Tashtarian, Farzad and Hellwagner, Hermann and Timmerer, Christian},
journal={ACM Transactions on Multimedia Computing, Communications and Applications},
volume={20},
number={10},
pages={1--23},
year={2024},
publisher={ACM New York, NY}
}