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International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing

ARMS-CC 2015: Adaptive Resource Management and Scheduling for Cloud Computing pp 60–77Cite as

User-Guided Provisioning in Federated Clouds for Distributed Calculations

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9438))

Abstract

Cloud Computing promises to be more flexible, usable, available and simple than Grid, covering also much more computational needs than the ones required to carry out distributed calculations. However, the diversity of cloud providers, the lack of standardised APIs and brokering tools prevent the massive portability of legacy applications to cloud environments. In this work a new framework to effectively schedule distributed calculations in cloud federations is presented. The system takes account of the experience in large and collaborative grid federations to provide several basic features that differentiates it from other approaches, such as the decentralisation, middleware independence, dynamic brokering, on-demand provisioning of specific virtual images, compatibility with legacy applications, efficient accomplishment of short tasks, etc. In this sense, the mechanisms that allow users to consolidate their own resource provisioning in cloud federations are the focus of this work. To demonstrate the suitability of the new approach, a common application to model radiation beams has been scheduled into the EGI FedCloud.

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Notes

  1. 1.

    http://aws.amazon.com.

  2. 2.

    http://cloudinit.readthedocs.org.

  3. 3.

    https://www.egi.eu/infrastructure/cloud/.

  4. 4.

    http://sixsq.com/products/slipstream.html.

  5. 5.

    http://www.compatibleone.org.

  6. 6.

    https://appdb.egi.eu/store/vo/image/de355bfb-5781-5b0c-9ccd-9bd3d0d2be06.

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Acknowledgements

This work was supported by the COST Action BETTY (IC 1201) and partially funded by the Spanish Ministry of Economy and Competitiveness project CODEC (TIN2013-46009-P).

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Authors and Affiliations

  1. Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain

    A. J. Rubio-Montero & R. Mayo-García

  2. Dep. de Arquitectura de Computadores y Automática, Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain

    E. Huedo

Authors
  1. A. J. Rubio-Montero
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  2. E. Huedo
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  3. R. Mayo-García
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Corresponding author

Correspondence to A. J. Rubio-Montero .

Editor information

Editors and Affiliations

  1. University Politehnica of Bucharest, Bucharest, Romania

    Florin Pop

  2. Université Pierre et Marie CURIE, Paris, France

    Maria Potop-Butucaru

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Rubio-Montero, A.J., Huedo, E., Mayo-García, R. (2015). User-Guided Provisioning in Federated Clouds for Distributed Calculations. In: Pop, F., Potop-Butucaru, M. (eds) Adaptive Resource Management and Scheduling for Cloud Computing. ARMS-CC 2015. Lecture Notes in Computer Science(), vol 9438. Springer, Cham. https://doi.org/10.1007/978-3-319-28448-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-28448-4_5

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-28448-4

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