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Heuristic Anticipation Scheduling for Efficient and Fair Resources Allocation in Grid VOs

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Creativity in Intelligent Technologies and Data Science (CIT&DS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 754))

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Abstract

In this work, a job-flow scheduling approach for Grid virtual organizations (VOs) is proposed and studied. Users’ and resource providers’ preferences, VOs internal policies, resources geographical distribution along with local private utilization impose specific requirements for efficient scheduling according to different, usually contradictive, criteria. With increasing resources utilization level the available resources set and corresponding decision space are reduced. In order to improve overall scheduling efficiency, we propose an anticipation scheduling heuristic. It includes a predetermined (anticipated) pattern solution definition and a special replication procedure for efficient and feasible resources allocation. A proposed anticipation algorithm is compared against conservative backfilling variations using such criteria as average jobs’ response time (start and finish times) as well as users’ and VO economic criteria (execution time and cost).

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Acknowledgments

This work was partially supported by the Council on Grants of the President of the Russian Federation for State Support of Young Scientists and Leading Scientific Schools (grants YPhD-2297.2017.9 and SS-6577.2016.9), RFBR (grants 15-07-02259 and 15-07-03401) and by the Ministry on Education and Science of the Russian Federation (project no. 2.9606.2017/8.9).

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Authors and Affiliations

  1. National Research University “MPEI”, ul. Krasnokazarmennaya, 14, Moscow, 111250, Russia

    Victor Toporkov & Dmitry Yemelyanov

Authors
  1. Victor Toporkov
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  2. Dmitry Yemelyanov
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Correspondence to Dmitry Yemelyanov .

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Editors and Affiliations

  1. Volgograd State Technical University, Volgograd, Russia

    Alla Kravets

  2. Volgograd State Technical University, Volgograd, Russia

    Maxim Shcherbakov

  3. Volgograd State Technical University, Volgograd, Russia

    Marina Kultsova

  4. University of Patras, Patras, Greece

    Peter Groumpos

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Toporkov, V., Yemelyanov, D. (2017). Heuristic Anticipation Scheduling for Efficient and Fair Resources Allocation in Grid VOs. In: Kravets, A., Shcherbakov, M., Kultsova, M., Groumpos, P. (eds) Creativity in Intelligent Technologies and Data Science. CIT&DS 2017. Communications in Computer and Information Science, vol 754. Springer, Cham. https://doi.org/10.1007/978-3-319-65551-2_43

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  • DOI: https://doi.org/10.1007/978-3-319-65551-2_43

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-65551-2

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