Understanding the Operational Carbon Footprint of Storage Reliability and Management

With daily data generation of Zettabytes and exponential growth, our study finds that power needed for data reliability and management is an increasing fraction of storage system power. Thus storage management is an important contributor to data center (DC) energy use and carbon footprint. We study the University of Chicago's high energy physics storage system (UChicago HEP) background tasks for reliability and management. We build a model for their activity and power costs, and next explore their opportunities for temporal shifting to reduce operational carbon footprint. We apply our model to varied DC scale: a large HEP facility, large cloud, and global set of large cloud DCs, we find that these storage tasks consume 2.1--4.9% of DC power and 12.8--27.2% of DC storage annually. Translating power use to carbon emissions depends on location and time, so carbon footprint varies. But we show that storage management power can account for as much as the annual electricity consumption of 755,000 US homes. Studying four power grids with varied carbon intensity, we show that aligning background tasks with low-carbon periods can achieve emission reductions of up to 82.8%. Greater reductions (up to 96.9%) are possible, as grids decarbonize further.

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Publication Details

Journal
ACM SIGEnergy Energy Informatics Review
Published
2024-12-01
DOI
https://doi.org/10.1145/3727200.3727227
Citations
4
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.81
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article

Understanding the Operational Carbon Footprint of Storage Reliability and Management

Andrew A. Chien, Varsha Rao
4 citations
ACM SIGEnergy Energy Informatics Review
Advanced Battery Technologies Research
0.81
article

Understanding the Operational Carbon Footprint of Storage Reliability and Management

Andrew A. Chien, Varsha Rao
article en
4 citations

Abstract

With daily data generation of Zettabytes and exponential growth, our study finds that power needed for data reliability and management is an increasing fraction of storage system power. Thus storage management is an important contributor to data center (DC) energy use and carbon footprint. We study the University of Chicago's high energy physics storage system (UChicago HEP) background tasks for reliability and management. We build a model for their activity and power costs, and next explore their opportunities for temporal shifting to reduce operational carbon footprint. We apply our model to varied DC scale: a large HEP facility, large cloud, and global set of large cloud DCs, we find that these storage tasks consume 2.1--4.9% of DC power and 12.8--27.2% of DC storage annually. Translating power use to carbon emissions depends on location and time, so carbon footprint varies. But we show that storage management power can account for as much as the annual electricity consumption of 755,000 US homes. Studying four power grids with varied carbon intensity, we show that aligning background tasks with low-carbon periods can achieve emission reductions of up to 82.8%. Greater reductions (up to 96.9%) are possible, as grids decarbonize further.

ACM SIGEnergy Energy Informatics ReviewVol. 4(5)
Argonne National Laboratory (US), University of Chicago (US)
Openalex Percentile: Top 27%
Advanced Battery Technologies Research
0.81
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