通过具有碳感知奖励的双层订阅模式激励绿色视频流媒体
Incentivising green video streaming through a 2-tier subscription model with carbon-aware rewards
AI总结：
本文提出一种双层订阅模型，通过折扣和碳奖励减少视频流媒体的碳排放，核心方法是根据用户类型和碳强度调整视频质量，主要贡献是提供灵活的减质策略以降低环境影响。
摘要：
我们研究了通过具有折扣和碳奖励的实用双层订阅模型来减少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片段的能耗、碳强度和用户类型（即对质量敏感或环保意识强的用户）。该模型使提供商能够灵活地将质量降低至最多一定百分比的视频内容，例如一个月内。我们的方法的关键特征包括：i）在最大用户满意度所需的分辨率下一级设置减质层更优；ii）当视频从本地数据中心流媒体时，最大百分比的视频以较低质量流媒体仅取决于碳强度和平均强度上限，而激励也取决于用户的环保意识水平；iii）当视频可以从本地或远程数据中心以不同碳强度流媒体时，最大百分比的视频以较低质量流媒体及激励取决于相对碳强度和数据中心的能耗，以及远程数据中心的额外网络能耗成本。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
