The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Survey of Techniques and Architectures for Designing Energy-Efficient Data Centers
Abstract
Cloud computing has emerged as the leading paradigm for information technology businesses. Cloud computing provides a platform to manage and deliver computing services around the world over the Internet. Cloud services have helped businesses utilize computing services on demand with no upfront investments. The cloud computing paradigm has sustained its growth, which has led to increase in size and number of data centers. Data centers with thousands of computing devices are deployed as back end to provide cloud services. Computing devices are deployed redundantly in data centers to ensure 24/7 availability. However, many studies have pointed out that data centers consume large amount of electricity, thus calling for energy-efficiency measures. In this survey, we discuss research issues related to conflicting requirements of maximizing quality of services (QoSs) (availability, reliability, etc.) delivered by the cloud services while minimizing energy consumption of the data center resources. In this paper, we present the concept of inception of data center energy-efficiency controller that can consolidate data center resources with minimal effect on QoS requirements. We discuss software- and hardware-based techniques and architectures for data center resources such as server, memory, and network devices that can be manipulated by the data center controller to achieve energy efficiency.
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Citations
Cites
(2010) · doi:10.5555/1855711.1855728 · Cited by 970
Cited by
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
Energy efficiency in cloud computing data centers: a survey on software technologies
Katal, A., Dahiya, S., & Choudhury, T. (2023) · Cluster Computing · doi:10.1007/s10586-022-03713-0 · Cited by 516
“In addition, the authors in [13] highlighted research difficulties connected to the competing needs of enhancing the quality of services (QoSs) supplied by cloud services while lowering energy consumption of data centre resources.”
BackgroundGreen Internet of Things for Smart World
Zhu, C., Leung, V. C. M., Shu, L., & Ngai, E. C.-H. (2015) · IEEE Access · doi:10.1109/access.2015.2497312 · Cited by 494
Green IoT for Eco-Friendly and Sustainable Smart Cities: Future Directions and Opportunities
Almalki, F. A., Alsamhi, S. H., Sahal, R., Hassan, J., Hawbani, A., Rajput, N. S., Saif, A., Morgan, J., & Breslin, J. (2023) · Mobile Networks and Applications · doi:10.1007/s11036-021-01790-w · Cited by 376
Biobjective Task Scheduling for Distributed Green Data Centers
Yuan, H., Bi, J., Zhou, M., Liu, Q., & Ammari, A. C. (2021) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2019.2958979 · Cited by 138
Metadata
- Authors
- Shuja, J., Bilal, K., Madani, S. A., Othman, M., Ranjan, R., Balaji, P., & Khan, S. U.
- Venue
- IEEE Systems Journal
- Published
- 2016-06
- Volume
- 10
- Issue
- 2
- Pages
- 507-519
- ISSN
- 1932-8184 (ISSN-L)
- 1937-9234
- 2373-7816
- OpenAlex
- W2315342500
- Cited by
- 218
- References
- 1
- FWCI
- 49.93
- Type
- journal article
- Language
- en
- Open access
- closed
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- Shuja, J., Bilal, K., Madani, S. A., Othman, M., Ranjan, R., Balaji, P., & Khan, S. U. (2016). Survey of Techniques and Architectures for Designing Energy-Efficient Data Centers. IEEE Systems Journal. https://doi.org/10.1109/jsyst.2014.2315823
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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.