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Correction to: Severity: a QoS-aware approach to cloud application elasticity
Journal of Cloud Computing volume 10, Article number: 50 (2021)
Correction to: J Cloud Comp 10, 45 (2021)
Following publication of the original article , the authors identified an error. This error has been corrected to express more accurately the work of Arkian et al. . This change should also make the last lines of the fourth paragraph of the Section on Rule-based and control-theoretic adaptation approaches more understandable.Footnote 1
The erroneous and corrected text are published in this correction article. The original article has been updated.
When the performance is better than expected, a single processing instance is removed, while when it is worse, a single processing instance is removed.
When the performance is better than expected, multiple processing instances can be removed, while when it is worse, a single processing instance is added.
“Moreover, the scaling algorithms we define allow more than one instances to be added as necessary which reduces the number of reconfigurations.”
Tsagkaropoulos A, Verginadis Y, Papageorgiou N, Paraskevopoulos F, Apostolou D, Mentzas G (2021) Severity: a QoS-aware approach to cloud application elasticity. J Cloud Comp 10(1):45. https://doi.org/10.1186/s13677-021-00255-5
Arkian H et al (2021) Model-based Stream Processing Auto-scaling in Geo-Distributed Environments. In: ICCCN 2021-30th International Conference on Computer Communications and Network
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Tsagkaropoulos, A., Verginadis, Y., Papageorgiou, N. et al. Correction to: Severity: a QoS-aware approach to cloud application elasticity. J Cloud Comp 10, 50 (2021). https://doi.org/10.1186/s13677-021-00266-2