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Exploring Cloud Elasticity in Scientific Applications

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Cloud Computing

Part of the book series: Computer Communications and Networks ((CCN))

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Abstract

Cloud computing has become an alternative to enable distributed computational resources to execute HPC-driven scientific applications. Among the cloud features, we highlight elasticity as one of the most pertinent for this kind of demand, particularly because this facility is in charge of on-the-fly modifying resource configurations to support the application behavior at each execution moment. In this way, elasticity can be used to find the most appropriate set of resources for running scientific applications whose requirements like number of processes or workloads cannot be determined in advance. This chapter aims at describing an elasticity taxonomy, in addition to the applicability of this feature on scientific applications. Moreover, we present two alternatives to explore cloud elasticity: one based on a novel set of programming directives (API) that are inserted in the application code to enable resource reorganization and another that offers elasticity at middleware level, without imposing any modifications in the user’s application code. Finally, a discussion about good practices and open issues is presented to inform existing and novel researchers and users about the state of the art in cloud elasticity and scientific applications.

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Notes

  1. 1.

    http://www.pbsworks.com

  2. 2.

    https://oar.imag.fr

  3. 3.

    http://gridscheduler.sourceforge.net

  4. 4.

    https://aws.amazon.com/ec2/instance-types/

  5. 5.

    https://wiki.gogrid.com/index.php/Cloud_Servers

  6. 6.

    https://www.rackspace.com/cloud/servers

  7. 7.

    https://www.profitbricks.com/

  8. 8.

    http://www.cloudsigma.com/

  9. 9.

    https://aws.amazon.com/emr/

  10. 10.

    https://aws.amazon.com/swf/

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Acknowledgements

This work was partially supported by the following Brazilian Agencies: FAPERGS, CAPES, and CNPq (grants 457501/2014-6 and 305531/2015-8).

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Authors and Affiliations

  1. Computer Science Department, Western Parana State University (Unioeste), Cascavel-PR, Brazil

    Guilherme Galante

  2. Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos (Unisinos), São Leopoldo-RS, Brazil

    Rodrigo da Rosa Righi

Authors
  1. Guilherme Galante
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  2. Rodrigo da Rosa Righi
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Correspondence to Guilherme Galante .

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Editors and Affiliations

  1. University of Derby, Derby, Derbyshire, United Kingdom

    Nick Antonopoulos

  2. University of Surrey, Guildford, Surrey, United Kingdom

    Lee Gillam

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Galante, G., da Rosa Righi, R. (2017). Exploring Cloud Elasticity in Scientific Applications. In: Antonopoulos, N., Gillam, L. (eds) Cloud Computing. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-54645-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-54645-2_4

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