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Dynamic Resources Configuration for Coevolutionary Scheduling of Scientific Workflows in Cloud Environment

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International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding (SOCO 2017, ICEUTE 2017, CISIS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 649))

Abstract

Modern composite scientific applications, also called scientific workflows, require large processing capacities. Cloud environments provide high performance and flexible infrastructure, which can be easily employed for workflows execution. Since cloud resources are paid in the most cases, there is a need to utilize these resources with maximal efficiency. In this paper we propose dynamic resources coevolutionary genetic algorithm, which extends previously developed coevolutionary genetic algorithm for dynamic cloud environment by changing computational capacities of execution nodes on runtime. This method along with using two types of chromosomes – mapping of tasks on resources and resources configuration – allows to greatly extend the search space of the algorithm. Experimental results demonstrate that developed algorithm is able to generate solutions better than other scheduling algorithms for a variety of scientific workflows.

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Acknowledgements

This research financially supported by Ministry of Education and Science of the Russian Federation, Agreement #14.587.21.0024 (18.11.2015). Unique Identification RFMEFI58715X0024.

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Authors and Affiliations

  1. ITMO University, Saint Petersburg, Russia

    Alexander A. Visheratin, Mikhail Melnik & Denis Nasonov

Authors
  1. Alexander A. Visheratin
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  2. Mikhail Melnik
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  3. Denis Nasonov
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Corresponding author

Correspondence to Alexander A. Visheratin .

Editor information

Editors and Affiliations

  1. University of Leon, Leon, Spain

    Hilde Pérez García

  2. University of Leon, Leon, Spain

    Javier Alfonso-Cendón

  3. University of Leon, Leon, Spain

    Lidia Sánchez González

  4. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Visheratin, A.A., Melnik, M., Nasonov, D. (2018). Dynamic Resources Configuration for Coevolutionary Scheduling of Scientific Workflows in Cloud Environment. In: Pérez García, H., Alfonso-Cendón, J., Sánchez González, L., Quintián, H., Corchado, E. (eds) International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding. SOCO ICEUTE CISIS 2017 2017 2017. Advances in Intelligent Systems and Computing, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-67180-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-67180-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67179-6

  • Online ISBN: 978-3-319-67180-2

  • eBook Packages: EngineeringEngineering (R0)

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