The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
A Survey on Cloud Computing Elasticity
Abstract
Elasticity is a key feature in the cloud computing context, and perhaps what distinguishes this computing paradigm of the other ones, such as cluster and grid computing. Considering the importance of elasticity in cloud computing context, the objective of this paper is to present a comprehensive study about the elasticity mechanisms available today. Initially, we propose a classification for elasticity mechanisms, based on the main features found in the analysed commercial and academic solutions. In a second moment, diverse related works are reviewed in order to define the state of the art of elasticity in clouds. We also discuss some of the challenges and open issues associated with the use of elasticity features in cloud computing.
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
Cites
The NIST definition of cloud computing
Mell, P. M., & Grance, T. (2011) · doi:10.6028/nist.sp.800-145 · Cited by 11,795
Cloud Computing: Issues and Challenges
Dillon, T., Wu, C., & Chang, E. (2010) · 2010 24th IEEE International Conference on Advanced Information Networking and Applications · doi:10.1109/aina.2010.187 · Cited by 1,369
CloudScale: elastic resource scaling for multi-tenant cloud systems
Shen, Z., Subbiah, S., Gu, X., & Wilkes, J. (2011) · Proceedings of the 2nd ACM Symposium on Cloud Computing · doi:10.1145/2038916.2038921 · Cited by 592
Efficient Autoscaling in the Cloud Using Predictive Models for Workload Forecasting
Roy, N., Dubey, A., & Gokhale, A. (2011) · 2011 IEEE 4th International Conference on Cloud Computing · doi:10.1109/cloud.2011.42 · Cited by 591
PRESS: PRedictive Elastic ReSource Scaling for cloud systems
Gong, Z., Gu, X., & Wilkes, J. (2010) · 2010 International Conference on Network and Service Management · doi:10.1109/cnsm.2010.5691343 · Cited by 544
A Performance Study on the VM Startup Time in the Cloud
Mao, M., & Humphrey, M. (2012) · 2012 IEEE Fifth International Conference on Cloud Computing · doi:10.1109/cloud.2012.103 · Cited by 526
Zhang, X., Kunjithapatham, A., Jeong, S., & Gibbs, S. (2011) · Mobile Networks and Applications · doi:10.1007/s11036-011-0305-7 · Cited by 257
A Cost-Aware Elasticity Provisioning System for the Cloud
Sharma, U. K., Shenoy, P. J., Sahu, S., et al. (2011) · International Conference on Distributed Computing Systems · doi:10.1109/icdcs.2011.59 · Cited by 252
Badger, L., Grance, T., Patt-Corner, R., & Voas, J. (2012) · Cited by 205
DejaVu: accelerating resource allocation in virtualized environments
Vasić, N., Novaković, D., Miučin, S., Kostić, D., & Bianchini, R. (2012) · Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems · doi:10.1145/2150976.2151021 · Cited by 174
Cited by
Elasticity in Cloud Computing: State of the Art and Research Challenges
Al-Dhuraibi, Y., Paraiso, F., Djarallah, N., & Merle, P. (2018) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2017.2711009 · Cited by 409
Metadata
- Authors
- Galante, G., & de Bona, L. C. E.
- Venue
- 2012 IEEE Fifth International Conference on Utility and Cloud Computing
- Publisher
- IEEE
- Published
- 2012-11
- Pages
- 263-270
- OpenAlex
- W2014721449
- Cited by
- 270
- References
- 13
- FWCI
- 18.19
- Type
- conference paper
- 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: A Survey on Cloud Computing Elasticity. https://app.cochat.ai/papers/10.1109/ucc.2012.30
- The paper
- Galante, G., & de Bona, L. C. E. (2012). A Survey on Cloud Computing Elasticity. 2012 IEEE Fifth International Conference on Utility and Cloud Computing. https://doi.org/10.1109/ucc.2012.30
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.