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CloudScale: elastic resource scaling for multi-tenant cloud systems
Abstract
Elastic resource scaling lets cloud systems meet application service level objectives (SLOs) with minimum resource provisioning costs. In this paper, we present CloudScale, a system that automates fine-grained elastic resource scaling for multi-tenant cloud computing infrastructures. CloudScale employs online resource demand prediction and prediction error handling to achieve adaptive resource allocation without assuming any prior knowledge about the applications running inside the cloud. CloudScale can resolve scaling conflicts between applications using migration, and integrates dynamic CPU voltage/frequency scaling to achieve energy savings with minimal effect on application SLOs. We have implemented CloudScale on top of Xen and conducted extensive experiments using a set of CPU and memory intensive applications (RUBiS, Hadoop, IBM System S). The results show that CloudScale can achieve significantly higher SLO conformance than other alternatives with low resource and energy cost. CloudScale is non-intrusive and light-weight, and imposes negligible overhead (< 2% CPU in Domain 0) to the virtualized computing cluster.
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Cited by
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Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R. H., Morrow, M. J., & Polakos, P. A. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2771153 · Cited by 1,022
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
A Survey of Virtual Machine Management in Edge Computing
Tao, Z., Xia, Q., Hao, Z., Li, C., Ma, L., Yi, S., & Li, Q. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2927919 · Cited by 114
Marahatta, A., Pirbhulal, S., Zhang, F., Parizi, R. M., Choo, K.-K. R., & Liu, Z. (2021) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2019.2918226 · Cited by 88
RAD: Detecting Performance Anomalies in Cloud-based Web Services
Mukherjee, J., Baluta, A., Litoiu, M., & Krishnamurthy, D. (2020) · 2020 IEEE 13th International Conference on Cloud Computing (CLOUD) · doi:10.1109/cloud49709.2020.00073 · Cited by 5
Metadata
- Authors
- Shen, Z., Subbiah, S., Gu, X., & Wilkes, J.
- Venue
- Proceedings of the 2nd ACM Symposium on Cloud Computing
- Publisher
- ACM
- Published
- 2011-10-26
- Pages
- 1-14
- OpenAlex
- W2143408306
- Cited by
- 592
- References
- 0
- FWCI
- 34.61
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Shen, Z., Subbiah, S., Gu, X., & Wilkes, J. (2011). CloudScale: elastic resource scaling for multi-tenant cloud systems. Proceedings of the 2nd ACM Symposium on Cloud Computing. https://doi.org/10.1145/2038916.2038921
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