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PRESS: PRedictive Elastic ReSource Scaling for cloud systems
Abstract
Cloud systems require elastic resource allocation to minimize resource provisioning costs while meeting service level objectives (SLOs). In this paper, we present a novel PRedictive Elastic reSource Scaling (PRESS) scheme for cloud systems. PRESS unobtrusively extracts fine-grained dynamic patterns in application resource demands and adjust their resource allocations automatically. Our approach leverages light-weight signal processing and statistical learning algorithms to achieve online predictions of dynamic application resource requirements. We have implemented the PRESS system on Xen and tested it using RUBiS and an application load trace from Google. Our experiments show that we can achieve good resource prediction accuracy with less than 5% over-estimation error and near zero under-estimation error, and elastic resource scaling can both significantly reduce resource waste and SLO violations.
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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
Autopilot: workload autoscaling at Google
Rzadca, K., Findeisen, P., Swiderski, J., Zych, P., Broniek, P., Kusmierek, J., Nowak, P., Strack, B., Witusowski, P., Hand, S., et al. (2020) · Proceedings of the Fifteenth European Conference on Computer Systems · doi:10.1145/3342195.3387524 · Cited by 303
Self-citationKSwSVR: A New Load Forecasting Method for Efficient Resources Provisioning in Cloud
Hu, R., Jiang, J., Liu, G., & Wang, L. (2013) · 2013 IEEE International Conference on Services Computing · doi:10.1109/scc.2013.67 · Cited by 22
PoWER: prediction of workload for energy efficient relocation of virtual machines
Qazi, K., Li, Y., & Sohn, A. (2013) · Proceedings of the 4th annual Symposium on Cloud Computing · doi:10.1145/2523616.2525938 · Cited by 6
Metadata
- Authors
- Gong, Z., Gu, X., & Wilkes, J.
- Venue
- 2010 International Conference on Network and Service Management
- Publisher
- IEEE
- Published
- 2010-10
- Pages
- 9-16
- OpenAlex
- W2106098710
- Cited by
- 544
- References
- 0
- FWCI
- 17.77
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: PRESS: PRedictive Elastic ReSource Scaling for cloud systems. https://app.cochat.ai/papers/10.1109/cnsm.2010.5691343
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- Gong, Z., Gu, X., & Wilkes, J. (2010). PRESS: PRedictive Elastic ReSource Scaling for cloud systems. 2010 International Conference on Network and Service Management. https://doi.org/10.1109/cnsm.2010.5691343
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
