The DOI matches its Crossref record.
Write off-loading: Practical power management for enterprise storage
Abstract
In enterprise data centers power usage is a problem impacting server density and the total cost of ownership. Storage uses a significant fraction of the power budget and there are no widely deployed power-saving solutions for enterprise storage systems. The traditional view is that enterprise workloads make spinning disks down ineffective because idle periods are too short. We analyzed block-level traces from 36 volumes in an enterprise data center for one week and concluded that significant idle periods exist, and that they can be further increased by modifying the read/write patterns using write off-loading . Write off-loading allows write requests on spun-down disks to be temporarily redirected to persistent storage elsewhere in the data center. The key challenge is doing this transparently and efficiently at the block level, without sacrificing consistency or failure resilience. We describe our write off-loading design and implementation that achieves these goals. We evaluate it by replaying portions of our traces on a rack-based testbed. Results show that just spinning disks down when idle saves 28--36% of energy, and write off-loading further increases the savings to 45--60%.
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
Optimizing energy consumption for data centers
Rong, H., Zhang, H., Xiao, S., Li, C., & Hu, C. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.12.283 · Cited by 398
Data retention in MLC NAND flash memory: Characterization, optimization, and recovery
Cai, Y., Luo, Y., Haratsch, E. F., Mai, K., & Mutlu, O. (2015) · 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA) · doi:10.1109/hpca.2015.7056062 · Cited by 274
Zhou, Z., Yang, S., Pu, L., & Yu, S. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2984332 · Cited by 77
Metadata
- Authors
- Narayanan, D., Donnelly, A., & Rowstron, A.
- Venue
- ACM Transactions on Storage
- Published
- 2008-11
- Volume
- 4
- Issue
- 3
- Pages
- 1-23
- ISSN
- 1553-3077 (ISSN-L)
- 1553-3093
- OpenAlex
- W2201220957
- Cited by
- 762
- References
- 0
- FWCI
- 53.22
- Type
- journal article
- Language
- en
- Open access
- closed
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: Write off-loading: Practical power management for enterprise storage. https://app.cochat.ai/papers/10.1145/1416944.1416949
- The paper
- Narayanan, D., Donnelly, A., & Rowstron, A. (2008). Write off-loading: Practical power management for enterprise storage. ACM Transactions on Storage. https://doi.org/10.1145/1416944.1416949
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.