Utilizing Large Language Models (LLMs) to Design Adaptive Bitrate (ABR) Algorithms
Overview
Large Language models (LLMs) are powerful in generating high-quality text and code. They can craft specific functions and even develop innovative networking algorithms. However, there are challenges in directly generating high-quality algorithms for a given target scenario.
Practical Solutions
Researchers have introduced LLM-ABR, the first system that uses LLMs to design adaptive bitrate (ABR) algorithms tailored for diverse network characteristics. This system outperforms traditional complex methods and has been evaluated across different network settings, consistently providing better results.
Key Advantages
– LLM-ABR autonomously designs adaptive bitrate algorithms for diverse network environments.
– The system improves video Quality of Experience (QoE) and outperforms default ABR algorithms across various network scenarios.
Value for Business
This research presents practical applications of LLMs in developing ABR algorithms tailored for diverse network environments. It highlights the potential for significant performance improvements and sets the stage for future advancements in ABR algorithms.
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