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Adaptive Scaling Up/Down for Elastic Clouds

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Intelligent Distributed Computing X (IDC 2016)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 678))

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Abstract

An approach for adapting distributed applications in response to changes in user requirements and resource availability is presented. The notion of elasticity enables capabilities and resources to be dynamically provisioned and released. However, existing applications do not inherently support elastic capabilities and resources. To solve this problem, we propose two novel functions: dynamic deployment of components and dividing and merging components. The former enables components to relocate themselves at new servers when provisioning the servers and at remaining servers when deprovisioning servers, while the latter enables the states of components to be divided, passed to other components, and merged with other components in accordance with user-defined functions. We constructed a middleware system for Java-based general-purpose software components with the two functions because they are useful to adapt applications to elasticity in cloud computing. The proposed system is useful because it enables applications be operated with elastic capabilities and resources in cloud computing.

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Author information

Authors and Affiliations

  1. National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Japan

    Ichiro Satoh

Authors
  1. Ichiro Satoh
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Correspondence to Ichiro Satoh .

Editor information

Editors and Affiliations

  1. Fac. of Automatics, Comp. & Electronics, University of Craiova Fac. of Automatics, Comp. & Electronics, Craiova, Romania

    Costin Badica

  2. Sorbonne Universités, Sorbonne Universités, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 4 place Jussieu 75005 Paris France, Paris, France

    Amal El Fallah Seghrouchni

  3. Faculty of EEMCS, Delft University of Technology Faculty of EEMCS, Delft, Zuid-Holland, The Netherlands

    Aurélie Beynier

  4. Sorbonne Universités, Sorbonne Universités, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 4 place Jussieu 75005 Paris France, Paris, France

    David Camacho

  5. Sorbonne Universités, Sorbonne Universités, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606, 4 place Jussieu 75005 Paris France, Paris, France

    Cédric Herpson

  6. Computer Science Department, Universidad Autonoma de Madrid Organization, C. Francisco Tomas y Valiente, , Madrid, Spain

    Koen Hindriks

  7. Universidade do Minho, Campus of Gualtar,4710 - 057 Braga, Portugal, Braga, Portugal

    Paulo Novais

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Satoh, I. (2017). Adaptive Scaling Up/Down for Elastic Clouds. In: Badica, C., et al. Intelligent Distributed Computing X. IDC 2016. Studies in Computational Intelligence, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-48829-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-48829-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48828-8

  • Online ISBN: 978-3-319-48829-5

  • eBook Packages: EngineeringEngineering (R0)

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