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Towards Failure Prediction in Scientific Workflows Using Stochastic Petri Nets and Dynamic Logic

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Quality of Information and Communications Technology (QUATIC 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1266))

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Abstract

Scientific workflows are models composed of activities, parameters, data, and dependencies, whose goal is to implement a complex computer simulation. Scientific workflows are commonly managed by Workflow Management Systems (WfMS). Several existing workflows demand many computing resources since they process a massive volume of data. This way, High-Performance Computing (HPC) environments allied to parallelization techniques have to be applied to support the execution of such workflows. Although HPC environments offer several advantages, failures are a reality rather than a possibility due to the high number of compute nodes involved in the execution. Thus, WfMS should be able to calculate the probability of a failure occurs in order to spare resources. In this paper, we propose the usage of \(\mathcal {DS}_3\), a dynamic logic tailored to reason about stochastic Petri nets, to verify and predict failures in scientific workflows.

This work was partially sponsored by CAPES, CNPq and FAPERJ.

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Notes

  1. 1.

    https://www.ipac.caltech.edu/2mass/releases/allsky/.

  2. 2.

    https://confluence.pegasus.isi.edu/display/pegasus/workflowgenerator.

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Authors and Affiliations

  1. Instituto de Computação, Universidade Federal Fluminense, Niterói, Brazil

    Bruno Lopes & Daniel de Oliveira

Authors
  1. Bruno Lopes
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  2. Daniel de Oliveira
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Corresponding author

Correspondence to Bruno Lopes .

Editor information

Editors and Affiliations

  1. Brunel University, London, UK

    Martin Shepperd

  2. Lisbon University Institute, Lisbon, Portugal

    Fernando Brito e Abreu

  3. University of Lisbon, Lisbon, Portugal

    Alberto Rodrigues da Silva

  4. University of Castilla-La Mancha, Talavera de la Reina, Spain

    Ricardo Pérez-Castillo

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Lopes, B., de Oliveira, D. (2020). Towards Failure Prediction in Scientific Workflows Using Stochastic Petri Nets and Dynamic Logic. In: Shepperd, M., Brito e Abreu, F., Rodrigues da Silva, A., Pérez-Castillo, R. (eds) Quality of Information and Communications Technology. QUATIC 2020. Communications in Computer and Information Science, vol 1266. Springer, Cham. https://doi.org/10.1007/978-3-030-58793-2_36

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  • DOI: https://doi.org/10.1007/978-3-030-58793-2_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58792-5

  • Online ISBN: 978-3-030-58793-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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