There has been a significant societal push towards sustainable practices, including in computing. Modern interactive workloads such as geo-distributed web-services exhibit various spatiotemporal and performance flexibility, enabling the possibility to adapt the location, time, and intensity of processing to align with the availability of renewable and low-carbon energy. An example is a web application hosted across multiple cloud regions, each with varying carbon intensity based on their local electricity mix. Distributed load-balancing enables the exploitation of low-carbon energy through load migration across regions, reducing web applications carbon footprint. In this paper, we present CASPER, a carbon-aware scheduling and provisioning system that primarily minimizes the carbon footprint of distributed web services while also respecting their Service Level Objectives (SLO). We formulate CASPER as an multi-objective optimization problem that considers both the variable carbon intensity and latency constraints of the network. Our evaluation reveals the significant potential of CASPER in achieving substantial reductions in carbon emissions. Compared to baseline methods, CASPER demonstrates improvements of up to 70% with no latency performance degradation.

翻译：社会正在大力推动可持续发展实践，包括计算领域。现代交互式工作负载（如地理分布式网络服务）具有多种时空和性能灵活性，使得调整处理的位置、时间和强度以匹配可再生能源和低碳能源的可用性成为可能。例如，跨多个云区域托管的Web应用程序，每个区域因当地电力结构不同而具有差异化的碳强度。通过跨区域负载迁移实现分布式负载均衡，可开发利用低碳能源，从而减少Web应用的碳足迹。本文提出CASPER——一种碳感知调度与资源供给系统，其在最小化分布式Web服务碳足迹的同时，尊重其服务等级目标（SLO）。我们将CASPER建模为多目标优化问题，同时考虑可变碳强度与网络延迟约束。评估结果表明，CASPER在显著降低碳排放方面具有巨大潜力。与基线方法相比，CASPER在无延迟性能下降的情况下实现了高达70%的改进。