Abstract
This research presents an architecture-agnostic energy model for sustainable computing, integrating the Software Carbon Intensity (SCI) score to estimate energy usage and assess the environmental impact of software operations. It focuses on creating a reliable energy estimation model and developing a workload management strategy for edge devices, optimizing task distribution without sacrificing performance. The study also adapts Kubernetes for energy-aware orchestration, enhancing sustainability in managed systems. Overall, this scalable framework promotes energy-efficient computing while aligning technological progress with sustainability goals, advancing environmentally responsible practices in computing.
| Original language | English |
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| Publication status | Published - 18 Mar 2024 |
| Event | The Alan Turing Institute, UK-AI ECR Connect 2024 - Queen Elizabeth II Centre, London, United Kingdom Duration: 18 Mar 2024 → … |
Conference
| Conference | The Alan Turing Institute, UK-AI ECR Connect 2024 |
|---|---|
| Country/Territory | United Kingdom |
| City | London |
| Period | 18/03/24 → … |
| Other | Ahead of AI UK 2024, The Alan Turing Institute has organised Early Career Researchers Connect (ECR Connect), an event specifically designed to offer early career researchers in the UK valuable networking and career-development opportunities. |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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