基于sdn的编解码器视频传输

Obinna Izima, R. Fréin, Ali Malik
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引用次数: 0

摘要

为了保证视频流在软件定义网络上的传输质量,需要有效的预测器和自适应路由框架。我们展示了一个代理,它使用定制的编解码器感知学习模型以可扩展的方式预测交付指标的视频质量。我们还演示了该代理与用于集中控制的软件定义网络的自适应框架的集成,该框架根据学习代理重新配置网络操作路径,确保在拥塞期间保持良好的视频传输质量。演示场景突出了框架的可行性、可伸缩性和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Codec-Aware Video Delivery Over SDNs
To guarantee quality of delivery for video streaming over software defined networks, efficient predictors and adaptive routing frameworks are required. We demonstrate an agent that predicts video quality of delivery metrics in a scalable way using a bespoke codec-aware learning model. We also demonstrate the integration of this agent with an adaptive framework for centrally controlled software-defined networks that re-configures network operational paths in response to the learning agent, ensuring that good quality of delivery of video is maintained during periods of congestion. The demo scenario highlights the feasibility, scalability and accuracy of the framework.
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