Ecovisor: A Virtual Energy System for Carbon-Efficient Applications
Abel Souza, Noman Bashir, Jorge Murillo, Walid A. Hanafy, Qianlin Liang, David Irwin, Prashant J. Shenoy
Abstract
Cloud platforms' rapid growth is raising significant concerns about their carbon emissions. To reduce carbon emissions, future cloud platforms will need to increase their reliance on renewable energy sources, such as solar and wind, which have zero emissions but are highly unreliable. Unfortunately, today's energy systems effectively mask this unreliability in hardware, which prevents applications from optimizing their carbon-efficiency, or work done per kilogram of carbon emitted. To address the problem, we design an "ecovisor", which virtualizes the energy system and exposes software-defined control of it to applications. An ecovisor enables each application to handle clean energy's unreliability in software based on its own specific requirements. We implement a small-scale ecovisor prototype that virtualizes a physical energy system to enable software-based application-level i) visibility into variable grid carbon-intensity and local renewable generation and ii) control of server power usage and battery charging and discharging. We evaluate the ecovisor approach by showing how multiple applications can concurrently exercise their virtual energy system in different ways to better optimize carbon-efficiency based on their specific requirements compared to general system-wide policies.
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Cited by top-tier papers8
- On the Limitations of Carbon-Aware Temporal and Spatial Workload Shifting in the CloudThanathorn Sukprasert, Abel Souza, Noman Bashir, David Irwin et al.EuroSys 2024 · 73 citations
- Designing Cloud Servers for Lower CarbonJaylen Wang, Daniel S. Berger, Fiodar Kazhamiaka, Celine Irvene et al.ISCA 2024 · 49 citations
- Going Green for Less Green: Optimizing the Cost of Reducing Cloud Carbon EmissionsWalid A. Hanafy, Qianlin Liang, Noman Bashir, Abel Souza et al.ASPLOS 2024 · 43 citations
- GREEN: Carbon-efficient Resource Scheduling for Machine Learning ClustersKaiqiang Xu, Decang Sun, Han Tian, Junxue Zhang et al.NSDI 2025 · 23 citations
- WaterWise: Co-optimizing Carbon- and Water-Footprint Toward Environmentally Sustainable Cloud ComputingYankai Jiang, Rohan Basu Roy, Raghavendra Kanakagiri, Devesh TiwariPPoPP 2025 · 17 citations
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- Data Center Power Oversubscription with a Medium Voltage Power Plane and Priority-Aware CappingVarun Sakalkar, Vasileios Kontorinis, David Landhuis, Shaohong Li et al.ASPLOS 2020 · 56 citations
- Thunderbolt: Throughput-Optimized, Quality-of-Service-Aware Power Capping at ScaleShaohong Li, Xi Wang, Xiao Zhang, Vasileios Kontorinis et al.OSDI 2020 · 42 citations
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