We investigate incentives for reducing the carbon emissions of video streaming that depend on the energy consumption of segments in the end-to-end video delivery path, the carbon intensity, and the user type, i.e., quality-sensitive and green or environmentally conscious users. The incentives can be offered through a practical 2-tier subscription model with a discount and carbon rewards, which gives providers the flexibility to reduce the quality for up to a maximum percentage of videos within a time period, such as one month. The key features of our approach are i) it is preferable to offer subscriptions where the reduced-quality tier is set one resolution level below the resolution required for maximum user satisfaction; ii) when a video is streamed from a local data center, the maximum percentage of videos streamed at a lower quality depends solely on the carbon intensity and the average intensity cap, whereas the incentives also depend on the users' level of environmental consciousness; iii) when a video can be streamed from a local or a remote data center with different carbon intensities, the maximum percentage of videos streamed at lower quality and the incentives depend on the relative carbon intensity and energy consumption at the data centers, and the additional network energy costs from the remote data center.

翻译：我们研究了降低视频流媒体碳排放的激励机制，该机制取决于端到端视频传输路径中各分段的能耗、碳强度以及用户类型（即质量敏感型用户和绿色环保型用户）。通过一种实用的双层订阅模式（包含折扣和碳奖励）提供激励，使服务提供商能够灵活地在特定时间段（如一个月）内，将视频质量降低至不超过最大百分比。我们方法的关键特征包括：i) 更优的订阅方案是，将低质量层的分辨率设置为比用户满意度最大所需分辨率低一级；ii) 当视频从本地数据中心传输时，以低质量传输的视频最大百分比仅取决于碳强度与平均强度上限，而激励措施还取决于用户的环保意识水平；iii) 当视频可从碳强度不同的本地数据中心或远程数据中心传输时，以低质量传输的视频最大百分比和激励措施取决于数据中心的相对碳强度与能耗，以及远程数据中心带来的额外网络能耗。