Carbon-Efficient Internet Video Streaming

Carbon-efficient computing has drawn significant attention recently aiming to achieve environmental sustainability. Several computation intensive applications, such as deep learning, have been studied in the community for carbon optimizations. However, video streaming, one of the most popular and resource-consuming Internet applications, is under-explored for carbon efficiency. In this paper, we for the first time investigate the carbon efficiency of video streaming systems with the goal of reducing carbon emissions caused by hosting the video streaming service. We develop a dynamic workload migration mechanism utilizing real-time carbon intensity data to select the hosting data center. Furthermore, to minimize the impact on the end-user experience, we consider the migration frequency to maintain service stability when making the migration decisions. The evaluation results indicate significant carbon reductions and acceptable stream switching overhead.