The DOI matches its Crossref record.
Report to Congress on Server and Data Center Energy Efficiency: Public Law 109-431
Open accessAbstract
This report was prepared in response to the request from Congress stated in Public Law 109-431 (H.R. 5646),"An Act to Study and Promote the Use of Energy Efficient Computer Servers in the United States." This report assesses current trends in energy use and energy costs of data centers and servers in the U.S. (especially Federal government facilities) and outlines existing and emerging opportunities for improved energy efficiency. It also makes recommendations for pursuing these energy-efficiency opportunities broadly across the country through the use of information and incentive-based programs.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The role of artificial intelligence in achieving the Sustainable Development Goals
Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020) · Nature Communications · doi:10.1038/s41467-019-14108-y · Cited by 3,294
A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems
Beloglazov, A., Buyya, R., Lee, Y. C., & Zomaya, A. (2011) · Advances in Computers · doi:10.1016/b978-0-12-385512-1.00003-7 · Cited by 777
Energy Efficient Resource Management in Virtualized Cloud Data Centers
Beloglazov, A., & Buyya, R. (2010) · 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing · doi:10.1109/ccgrid.2010.46 · Cited by 760
Habibi Khalaj, A., & Halgamuge, S. K. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.08.037 · Cited by 707
Energy Efficient Allocation of Virtual Machines in Cloud Data Centers
Beloglazov, A., & Buyya, R. (2010) · 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing · doi:10.1109/ccgrid.2010.45 · Cited by 422
Metadata
- Authors
- Alliance to Save Energy, & Ernest Orlando Lawrence Berkeley National Laboratory, B.
- Published
- 2007-08-02
- OpenAlex
- W2166716750
- Cited by
- 589
- References
- 0
- Type
- report
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Report to Congress on Server and Data Center Energy Efficiency: Public Law 109-431. https://app.cochat.ai/papers/10.2172/929723
- The paper
- Alliance to Save Energy, & Ernest Orlando Lawrence Berkeley National Laboratory, B. (2007). Report to Congress on Server and Data Center Energy Efficiency: Public Law 109-431. https://doi.org/10.2172/929723
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.