The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
A survey on techniques for improving the energy efficiency of large-scale distributed systems
Abstract
The great amounts of energy consumed by large-scale computing and network systems, such as data centers and supercomputers, have been a major source of concern in a society increasingly reliant on information technology. Trying to tackle this issue, the research community and industry have proposed myriad techniques to curb the energy consumed by IT systems. This article surveys techniques and solutions that aim to improve the energy efficiency of computing and network resources. It discusses methods to evaluate and model the energy consumed by these resources, and describes techniques that operate at a distributed system level, trying to improve aspects such as resource allocation, scheduling, and network traffic management. This work aims to review the state of the art on energy efficiency and to foster research on schemes to make network and computing resources more efficient.
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Cites
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Data Center Energy Consumption Modeling: A Survey
Dayarathna, M., Wen, Y., & Fan, R. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2481183 · Cited by 1,165
Edge-Oriented Computing Paradigms: A Survey on Architecture Design and System Management
Li, C., Xue, Y., Wang, J., Zhang, W., & Li, T. (2019) · ACM Computing Surveys · doi:10.1145/3154815 · Cited by 180
Czarnul, P., Proficz, J., & Krzywaniak, A. (2019) · Scientific Programming · doi:10.1155/2019/8348791 · Cited by 57
Distributed resource scheduling in edge computing: Problems, solutions, and opportunities
Sahni, Y., Cao, J., Yang, L., & Wang, S. (2022) · Computer Networks · doi:10.1016/j.comnet.2022.109430 · Cited by 38
Quantifying the impact of shutdown techniques for energy‐efficient data centers
Raïs, I., Orgerie, A., Quinson, M., & Lefèvre, L. (2018) · Concurrency and Computation: Practice and Experience · doi:10.1002/cpe.4471 · Cited by 23
Self-citation
Metadata
- Authors
- Orgerie, A.-C., Assuncao, M. D. D., & Lefevre, L.
- Venue
- ACM Computing Surveys
- Published
- 2014-03
- Volume
- 46
- Issue
- 4
- Pages
- 1-31
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W1988593113
- Cited by
- 340
- References
- 66
- FWCI
- 74.65
- Type
- journal article
- Language
- en
- Open access
- closed
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- Orgerie, A.-C., Assuncao, M. D. D., & Lefevre, L. (2014). A survey on techniques for improving the energy efficiency of large-scale distributed systems. ACM Computing Surveys. https://doi.org/10.1145/2532637
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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.
