The increasing integration of renewable energy sources results in fluctuations in carbon intensity throughout the day. To mitigate their carbon footprint, datacenters can implement demand response (DR) by adjusting their load based on grid signals. However, this presents challenges for private datacenters with diverse workloads and services. One of the key challenges is efficiently and fairly allocating power curtailment across different workloads. In response to these challenges, we propose the Carbon Responder framework. The Carbon Responder framework aims to reduce the carbon footprint of heterogeneous workloads in datacenters by modulating their power usage. Unlike previous studies, Carbon Responder considers both online and batch workloads with different service level objectives and develops accurate performance models to achieve performance-aware power allocation. The framework supports three alternative policies: Efficient DR, Fair and Centralized DR, and Fair and Decentralized DR. We evaluate Carbon Responder polices using production workload traces from a private hyperscale datacenter. Our experimental results demonstrate that the efficient Carbon Responder policy reduces the carbon footprint by around 2x as much compared to baseline approaches adapted from existing methods. The fair Carbon Responder policies distribute the performance penalties and carbon reduction responsibility fairly among workloads.

翻译：可再生能源日益普及导致全天碳强度波动。为减少碳足迹，数据中心可根据电网信号调整负载实施需求响应(DR)。然而，这对承载多样化工作负载和服务的私有数据中心构成挑战，其中关键难题是如何在不同工作负载间高效公平地分配功率削减任务。针对这些挑战，我们提出碳响应者框架。该框架通过调节异构工作负载的功率使用量来降低数据中心碳足迹。与现有研究不同，碳响应者同时考虑具有不同服务等级目标的在线和批处理工作负载，并构建精确性能模型以实现性能感知的功率分配。该框架支持三种可选策略：高效需求响应、公平集中式需求响应和公平分布式需求响应。我们使用私有超大规模数据中心的生产工作负载轨迹对碳响应者策略进行评估。实验结果表明，与基于现有方法改进的基准方案相比，高效碳响应者策略可使碳足迹减少约两倍。公平碳响应者策略则在工作负载间公平分配性能损失和碳减排责任。