CASPER: Carbon-Aware Scheduling and Provisioning for Distributed Web Services

Abstract

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.

References in corpus (3)

• Sustainable AI: Environmental Implications, Challenges and Opportunities
• Let's Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud
• Adapting Datacenter Capacity for Greener Datacenters and Grid

Cited by in corpus (6)

• On the Limitations of Carbon-Aware Temporal and Spatial Workload Shifting in the Cloud
• LACS: Learning-Augmented Algorithms for Carbon-Aware Resource Scaling with Uncertain Demand
• Carbon-Aware Quality Adaptation for Energy-Intensive Services
• EnsembleCI: Ensemble Learning for Carbon Intensity Forecasting
• A Decentralized Microservice Scheduling Approach Using Service Mesh in Cloud-Edge Systems
• EcoKube: Simulating Carbon-Aware Scheduling Policies in Heterogeneous Edge-Cloud Environments