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Cloud Adoption by Fine-Grained Resource Adaptation: Price Determination of Diagonally Scalable IaaS

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Advances in Service-Oriented and Cloud Computing (ESOCC 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 567))

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Abstract

Cloud computing is a suitable solution for addressing the uncertainty of resource demand by allowing dynamic resource adjustment. However, most IaaS cloud providers offer their services with a limited granularity at rather slow scaling speeds and flat pricing schemes. Diagonal scaling techniques can offer a more adaptive and fine-grained service with a likewise granular pricing model. Before offering such an adaptive service, cloud providers need a comparison between horizontal and diagonal scaling models to estimate how resource prices can be increased while still staying competitive. In this paper we examine the resource reduction potential of diagonal scaling in comparison to conventional horizontal approaches. Given an empirical load pattern of a web application provider we find a CPU allocation reduction potential of 8.05 % compared to the conventional service. Given a more fine-grained pricing model, we find an additional revenue potential for diagonal scaling of 9.01 % when following a competitor based pricing regime.

This work has been developed in the project CLoUd Services Scalability (CLUSS) that is partly funded by the German ministry of education and research (ref. num.: 01IS13013A-D).

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Notes

  1. 1.

    http://aws.amazon.com/autoscaling, last visit 23.06.2015.

  2. 2.

    http://rackspace.com/cloud/auto-scale, last visit 23.06.2015.

  3. 3.

    http://aws.amazon.com/ec2/pricing/, last visit 23.06.2015.

  4. 4.

    http://rackspace.com/cloud/servers/, last visit 23.06.2015.

  5. 5.

    http://gloveler.de/, last visit 23.06.2015.

  6. 6.

    http://cpubenchmark.net/compare.php?cmp[]=834&cmp[]=896&cmp[]=1220, last visit 23.06.2015.

  7. 7.

    http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/example-templates-autoscaling.html, last visit 23.06.2015.

  8. 8.

    http://aws.amazon.com/ec2/instance-types/, last visit 23.06.2015.

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Authors and Affiliations

  1. FZI Research Center for Information Technology, Haid-und-Neu-Straße 10–14, 76131, Karlsruhe, Germany

    Kevin Laubis, Viliam Simko & Alexander Schuller

Authors
  1. Kevin Laubis
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  2. Viliam Simko
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  3. Alexander Schuller
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Correspondence to Kevin Laubis .

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Editors and Affiliations

  1. DICIEAMA, University of Messina, Messina, Italy

    Antonio Celesti

  2. Software Evolution and Architecture Lab, University of Zürich Software Evolution and Architecture Lab, Zürich, Switzerland

    Philipp Leitner

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Laubis, K., Simko, V., Schuller, A. (2016). Cloud Adoption by Fine-Grained Resource Adaptation: Price Determination of Diagonally Scalable IaaS. In: Celesti, A., Leitner, P. (eds) Advances in Service-Oriented and Cloud Computing. ESOCC 2015. Communications in Computer and Information Science, vol 567. Springer, Cham. https://doi.org/10.1007/978-3-319-33313-7_19

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  • DOI: https://doi.org/10.1007/978-3-319-33313-7_19

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  • Publisher Name: Springer, Cham

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