The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
An diverse approach on virtual machines administration and power control in multi-level implicit servers
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In the citing paper
“Apart from this, Prabhakaran et al. [25] introduced VM resource calibration. They created a system to reduce the energy usage of virtual servers by utilising controlled feedback architecture as well as power monitoring services.”
From Energy efficiency in cloud computing data centers: a survey on software technologies (2023) · cites this paper as [25]
Citations
Cites
On Global Electricity Usage of Communication Technology: Trends to 2030
Andrae, A., & Edler, T. (2015) · Challenges · doi:10.3390/challe6010117 · Cited by 1,334
VirtualPower: coordinated power management in virtualized enterprise systems
Nathuji, R., & Schwan, K. (2007) · Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles · doi:10.1145/1294261.1294287 · Cited by 606
Performance guarantees for Web server end-systems: a control-theoretical approach
Abdelzaher, T. F., Shin, K. G., & Bhatti, N. (2002) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/71.980028 · Cited by 594
Adaptive control of virtualized resources in utility computing environments
Padala, P., Shin, K. G., Zhu, X., et al. (2007) · doi:10.1145/1272996.1273026 · Cited by 581
Ensemble-level Power Management for Dense Blade Servers
Ranganathan, P., Leech, P., Irwin, D., & Chase, J. (2006) · ACM SIGARCH Computer Architecture News · doi:10.1145/1150019.1136492 · Cited by 357
Dynamic Voltage Scaling in Multitier Web Servers with End-to-End Delay Control
Horváth, T., Abdelzaher, T., Skadron, K., et al. (2007) · IEEE Transactions on Computers · doi:10.1109/tc.2007.1003 · Cited by 275
Cluster-level feedback power control for performance optimization
Wang, X., & Chen, M. (2008) · Proceedings - International Symposium on High-Performance Computer Architecture/Proceedings · doi:10.1109/hpca.2008.4658631 · Cited by 222
Survey of Techniques and Architectures for Designing Energy-Efficient Data Centers
Shuja, J., Bilal, K., Madani, S. A., Othman, M., Ranjan, R., Balaji, P., & Khan, S. U. (2016) · IEEE Systems Journal · doi:10.1109/jsyst.2014.2315823 · Cited by 218
Diao, Y., Gandhi, N., Hellerstein, J. L., et al. (2003) · doi:10.1109/noms.2002.1015566 · Cited by 212
Sustainable Cloud Data Centers: A survey of enabling techniques and technologies
Shuja, J., Gani, A., Shamshirband, S., Ahmad, R. W., & Bilal, K. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.04.034 · Cited by 172
Cited by
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
“[25] introduced VM resource calibration.”
Metadata
- Authors
- Prabhakaran, G., & Selvakumar, S.
- Affiliations
- Anna University, Chennai (IN)
- Corresponding author
- Prabhakaran, G.
- Venue
- Journal of Ambient Intelligence and Humanized Computing
- Published
- 2021-03-09
- ISSN
- 1868-5137 (ISSN-L)
- 1868-5145
- OpenAlex
- W3134766117
- Cited by
- 4
- References
- 32
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 2
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- www.springer.com/tdm (vor)
- Locations
- Journal of Ambient Intelligence and Humanized Computing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Keywords
- power capping, container-based virtualization, power estimation, electricity metering, data center energy efficiency
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.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An diverse approach on virtual machines administration and power control in multi-level implicit servers. https://app.cochat.ai/papers/10.1007/s12652-021-03013-2
- The paper
- Prabhakaran, G., & Selvakumar, S. (2021). An diverse approach on virtual machines administration and power control in multi-level implicit servers. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-021-03013-2
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.
