EDBT 2026 Demo / reviewers in the wild / expert
Eric R. Masanet
dblp:122/1773
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Energy-efficient computing · 87% Cloud and datacenter computing · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy-efficient computing
datacenter energy consumption |
0.1 | 1 | 2011 | Estimating the Energy Use and Efficiency Potential of U.S. Data Centers · Proc. IEEE 2011 |
Energy-efficient computing
datacenter energy efficiency |
0.1 | 1 | 2011 | Estimating the Energy Use and Efficiency Potential of U.S. Data Centers · Proc. IEEE 2011 |
Cloud and datacenter computing
datacenter infrastructure |
0.0 | 1 | 2011 | Estimating the Energy Use and Efficiency Potential of U.S. Data Centers · Proc. IEEE 2011 |
Methods — techniques the papers use, named apart from their topics
bottom-up modeling · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Estimating the Energy Use and Efficiency Potential of U.S. Data CentersabstractData centers are a significant and growing component of electricity demand in the United States. This paper presents a bottom-up model that can be used to estimate total data center electricity demand within a region as well as the potential electricity savings associated with energy efficiency improvements. The model is applied to estimate 2008 U.S. data center electricity demand and the technical potential for electricity savings associated with major measures for IT devices and infrastructure equipment. Results suggest that 2008 demand was approximately 69 billion kilowatt hours (1.8% of 2008 total U.S. electricity sales) and that it may be technically feasible to reduce this demand by up to 80% (to 13 billion kilowatt hours) through aggressive pursuit of energy efficiency measures. Measure-level savings estimates are provided, which shed light on the relative importance of different measures at the national level. Measures applied to servers are found to have the greatest contribution to potential savings. Eric R. Masanet, Richard Brown 0002, Arman Shehabi, Jonathan G. Koomey, Bruce Nordman |
Proc. IEEE | 1 |