Published February 20, 2026
| Version v1
Software
Open
X4-Match: Sustainable Prediction-based Video Encoding Scheduling Framework
Authors/Creators
Description
This framework provides a sustainable, energy-efficient scheduling method that integrates ML–based prediction with game-theoretic heuristics to optimize video encoding workloads across cloud and edge instances.
BibTex:
@inproceedings{afzal2026x4,
title={X4-MATCH: Sustainable Prediction-based Distribution of Video Encoding on Cloud and Edge},
author={Afzal, Samira and Mehran, Narges and Freeman, Andrew C. and Hoi, Manuel and Lachini, Armin and Timmerer, Christian and Prodan, Radu},
booktitle={40th IEEE International Parallel \& Distributed Processing Symposium, May 2026},
year={2026}
}
Files
X4-MATCH.zip
Files
(159.9 MB)
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Additional details
Funding
- Baylor University
- The Freeman Multimedia Lab
- Land Salzburg
- EXDIGIT (Excellence in Digital Sciences and Interdisciplinary Technologies) 20204-WISS/263/6-6022
- Christian Doppler Research Association
- Adaptive Streaming over HTTP and Emerging Networked Multimedia Services (ATHENA)
- Austrian Research Promotion Agency
- AIM AT Stiftungsprofessur für Edge AI 909989
Software
- Programming language
- Python , Jupyter Notebook