Paper Contents
Abstract
Adaptive video streaming is of majorsignificance in this new digital era for transportation of high-quality multimedia data on time-varying networks. In this paper, wesuggest a lightweight meta-RL framework to enhance the generalization and online adaptation skills for bitrate choice on the basis of Reptile. The model can instruct a universal initialization on a broadvariety of network situations, and adapts rapidly in-stream to maximize video quality and decrease stalling, In comparison to classical ABR and, the suggested method can perform a faster adaptation at lower meta-critic and complexity systems and thus is suited for contemporary, scalable video streaming platforms.
Copyright
Copyright © 2025 C Prakash Naik. This is an open access article distributed under the Creative Commons Attribution License.
