What is it about?
The framework reduces water consumption, carbon emissions, and energy cost without compromising performance in geo-distributed datacenter scheduling. SHIELD achieves multi-objective optimal through the proposed hybrid search approach. The work explores the spatiotemporal patterns of energy water intensity factor, carbon intensity, and energy pricing.
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This page is a summary of: SHIELD: Sustainable Hybrid Evolutionary Learning Framework for Carbon, Wastewater, and Energy-Aware Data Center Management, October 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3634769.3634810.
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