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European Conference on Parallel Processing

Euro-Par 2019: Euro-Par 2019: Parallel Processing Workshops pp 345–356Cite as

Adaptation of Workflow Application Scheduling Algorithm to Serverless Infrastructure

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 11997)

Abstract

Function-as-a-Service is a novel type of cloud service used for creating distributed applications and utilizing computing resources. Application developer supplies source code of cloud functions, which are small applications or application components, while the service provider is responsible for provisioning the infrastructure, scaling and exposing a REST style API. This environment seems to be adequate for running scientific workflows, which in recent years, have become an established paradigm for implementing and preserving complex scientific processes. In this paper, we present work done on adaptation of a scheduling algorithm to FaaS infrastructure. The result of this work is a static heuristic capable of planning workflow execution based on defined function pricing, deadline and budget. The SDBCS algorithm is designed to determine the quality of assignment of particular task to specific function configuration. Each task is analyzed for execution time and cost characteristics, while keeping track of parameters of complete workflow execution. The algorithm is validated through means of experiment with a set of synthetic workflows and a real life infrastructure case study performed on AWS Lambda. The results confirm the utility of the algorithm and lead us to propose areas of further study, which include more detailed analysis of infrastructure features affecting scheduling.

Keywords

  • Serverless
  • Cloud functions
  • Workflow scheduling
  • Infrastructure testing

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  • DOI: 10.1007/978-3-030-48340-1_27
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Notes

  1. 1.

    HyperFlow repository: https://github.com/hyperflow-wms/hyperflow.

  2. 2.

    https://github.com/PawelBanach/CloudFunctionOptimizer.

  3. 3.

    https://download.pegasus.isi.edu/misc/SyntheticWorkflows.tar.gz.

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Acknowledgements

This work was supported by the National Science Centre, Poland, grant 2016/21/B/ST6/01497.

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Authors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Maciej Pawlik, Pawel Banach & Maciej Malawski

Authors
  1. Maciej Pawlik
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  2. Pawel Banach
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  3. Maciej Malawski
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Corresponding author

Correspondence to Maciej Pawlik .

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Editors and Affiliations

  1. Gesellschaft für Wissenschaftliche Datenverarbeitung mbH, Göttingen, Germany

    Ulrich Schwardmann

  2. Gesellschaft für Wissenschaftliche Datenverarbeitung mbH, Göttingen, Germany

    Christian Boehme

  3. CiTIUS, Santiago de Compostela, Spain

    Dora B. Heras

  4. University of Rome "Tor Vergata", Rome, Italy

    Valeria Cardellini

  5. Inria Bordeaux Sud-Ouest, Talence, France

    Emmanuel Jeannot

  6. Engineering Sardegna, Cagliari, Italy

    Antonio Salis

  7. University of Turin, Torino, Italy

    Claudio Schifanella

  8. University College Dublin, Dublin, Ireland

    Ravi Reddy Manumachu

  9. DLR-AS, Göttingen, Germany

    Dieter Schwamborn

  10. University of Pisa, Pisa, Italy

    Laura Ricci

  11. Ajou University, Suwon, Korea (Republic of)

    Oh Sangyoon

  12. RRZE Friedrich-Alexander-Universität, Erlangen, Germany

    Thomas Gruber

  13. ICAR-CNR, Napoli, Italy

    Laura Antonelli

  14. Tennessee Technological University, Cookeville, TN, USA

    Stephen L. Scott

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Pawlik, M., Banach, P., Malawski, M. (2020). Adaptation of Workflow Application Scheduling Algorithm to Serverless Infrastructure. In: , et al. Euro-Par 2019: Parallel Processing Workshops. Euro-Par 2019. Lecture Notes in Computer Science(), vol 11997. Springer, Cham. https://doi.org/10.1007/978-3-030-48340-1_27

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  • DOI: https://doi.org/10.1007/978-3-030-48340-1_27

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