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Correction to: Severity: a QoS-aware approach to cloud application elasticity

The Original Article was published on 21 August 2021

Correction to: J Cloud Comp 10, 45 (2021)

https://doi.org/10.1186/s13677-021-00255-5

Following publication of the original article [1], the authors identified an error. This error has been corrected to express more accurately the work of Arkian et al. [2]. 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.

Incorrect

  • When the performance is better than expected, a single processing instance is removed, while when it is worse, a single processing instance is removed.

Correct:

  • When the performance is better than expected, multiple processing instances can be removed, while when it is worse, a single processing instance is added.

Notes

  1. 1.

    “Moreover, the scaling algorithms we define allow more than one instances to be added as necessary which reduces the number of reconfigurations.”

References

  1. 1.

    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

    Article  Google Scholar 

  2. 2.

    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

    Google Scholar 

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Correspondence to Andreas Tsagkaropoulos.

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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

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