Skip to main content
Springer Nature Link
Log in

Eulero: A Tool for Quantitative Modeling and Evaluation of Complex Workflows

  • Conference paper
  • First Online:
Quantitative Evaluation of Systems (QEST 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13479))

Included in the following conference series:

Abstract

We present Eulero, a novel Java library enabling modeling of complex workflows and evaluation of their end-to-end response time Probability Density Function (PDF). Workflows consist of activities with general (i.e., non-exponential) duration with bounded support, composed through sequence, choice/merge, and split/join blocks, with unbalanced split and join constructs that break the structure of well-formed nesting. Eulero supports specification of workflows through structure trees, a hierarchical representation enabling the workflow decomposition into sub-workflows that can be efficiently analyzed in isolation. Eulero implements composition of the analysis results of these sub-workflows to provide a stochastically ordered approximation of the response time PDF of the overall workflow. The library supports random generation of workflow models controlling the main factors of computational complexity. Eulero exploits the SIRIO Library of the ORIS tool to represent monovariate PDFs and to model and analyze sub-workflows, and it is designed to facilitate usability, maintainability, and extensibility.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Data Availability Statement

An artifact of the Eulero library is available at https://doi.org/10.5281/zenodo.6841108. The artifact consists of the jar archive of the library, two Java classes containing the code snippets provided with the paper, a suite of models randomly generated through the procedure described in Sect. 5.2, a script to generate and evaluate a new suite of models, and a script to replicate the generation and the evaluation of a suite of models.

References

  1. Alur, R., Dill, D.L.: A theory of timed automata. Theoret. Comput. Sci. 126(2), 183–235 (1994)

    Article  MathSciNet  Google Scholar 

  2. Amparore, E.G., Balbo, G., Beccuti, M., Donatelli, S., Franceschinis, G.: 30 years of GreatSPN. Principles of performance and reliability modeling and evaluation, pp. 227–254 (2016)

    Google Scholar 

  3. Carnevali, L., Paolieri, M., Reali, R., Vicario, E.: Compositional safe approximation of response time distribution of complex workflows. In: Abate, A., Marin, A. (eds.) QEST 2021. LNCS, vol. 12846, pp. 83–104. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-85172-9_5

    Chapter  MATH  Google Scholar 

  4. Carnevali, L., Reali, R., Vicario, E.: Compositional evaluation of stochastic workflows for response time analysis of composite web services. In: Proceedings of the ACM/SPEC International Conference on Performance Engineering, pp. 177–188 (2021)

    Google Scholar 

  5. Ciardo, G., Jones, R.L., Miner, A.S., Siminiceanu, R.: Logical and stochastic modeling with SMART. In: Kemper, P., Sanders, W.H. (eds.) TOOLS 2003. LNCS, vol. 2794, pp. 78–97. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-540-45232-4_6

    Chapter  Google Scholar 

  6. Curbera, F., Goland, Y., Klein, J., Leymann, F., Roller, D., Thatte, S., Weerawarana, S.: Business process execution language for web services (2002)

    Google Scholar 

  7. Dehnert, C., Junges, S., Katoen, J.-P., Volk, M.: A Storm is coming: a modern probabilistic model checker. In: Majumdar, R., Kunčak, V. (eds.) CAV 2017. LNCS, vol. 10427, pp. 592–600. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63390-9_31

    Chapter  Google Scholar 

  8. van Der Aalst, W.M., Ter Hofstede, A.H., Kiepuszewski, B., Barros, A.P.: Workflow patterns. Dist. Paral. Datab. 14(1), 5–51 (2003)

    Article  Google Scholar 

  9. Dick, R.P., Rhodes, D.L., Wolf, W.: TGFF: task graphs for free. In: Proceedings of the Sixth International Workshop on Hardware/Software Codesign. (CODES/CASHE 1998), pp. 97–101. IEEE (1998)

    Google Scholar 

  10. Foundation, A.S.: Apache airflow

    Google Scholar 

  11. Gamma, E., Helm, R., Johnson, R., Vlissides, J.M.: Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional, 1 edn. (1994)

    Google Scholar 

  12. German, R., Lindemann, C.: Analysis of stochastic Petri nets by the method of supplementary variables. Perform. Eval. 20(1–3), 317–335 (1994)

    Article  MathSciNet  Google Scholar 

  13. Horváth, A., Paolieri, M., Ridi, L., Vicario, E.: Transient analysis of non-Markovian models using stochastic state classes. Perform. Eval. 69(7–8), 315–335 (2012)

    Article  Google Scholar 

  14. Jensen, E.D., Locke, C.D., Tokuda, H.: A time-driven scheduling model for real-time operating systems. In: RTSS, vol. 85, pp. 112–122 (1985)

    Google Scholar 

  15. Katoen, J.P., Zapreev, I.S., Hahn, E.M., Hermanns, H., Jansen, D.N.: The ins and outs of the probabilistic model checker MRMC. Perform. Eval. 68(2), 90–104 (2011)

    Article  Google Scholar 

  16. de Kok, T.G., Fransoo, J.C.: Planning supply chain operations: definition and comparison of planning concepts. Handbooks Oper. Res. Manage. Sci. 11, 597–675 (2003)

    Article  Google Scholar 

  17. Kulkarni, V.G.: Modeling and Analysis of Stochastic Systems. Chapman and Hall/CRC, Boca Raton (2016)

    Google Scholar 

  18. Kwiatkowska, M., Norman, G., Parker, D.: PRISM: probabilistic symbolic model checker. In: Field, T., Harrison, P.G., Bradley, J., Harder, U. (eds.) TOOLS 2002. LNCS, vol. 2324, pp. 200–204. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-46029-2_13

    Chapter  Google Scholar 

  19. Paolieri, M., Biagi, M., Carnevali, L., Vicario, E.: The ORIS tool: quantitative evaluation of non-Markovian systems. IEEE Trans. Softw. Eng. 47(6), 1211–1225 (2019)

    Article  Google Scholar 

  20. Rahman, J., Lama, P.: Predicting the end-to-end tail latency of containerized microservices in the cloud. In: 2019 IEEE International Conference on Cloud Engineering (IC2E), pp. 200–210. IEEE (2019)

    Google Scholar 

  21. Russell, N., Ter Hofstede, A.H., Van Der Aalst, W.M., Mulyar, N.: Workflow control-flow patterns: a revised view. BPM Center Report BPM-06-22, BPMcenter. org, pp. 06–22 (2006)

    Google Scholar 

  22. SA, S.T.: Luigi

    Google Scholar 

  23. Trivedi, K.S., Sahner, R.: SHARPE at the age of twenty two. ACM SIGMETRICS Perform. Eval. Rev. 36(4), 52–57 (2009)

    Article  Google Scholar 

  24. Van Eyk, E., Iosup, A., Abad, C.L., Grohmann, J., Eismann, S.: A SPEC RG cloud group’s vision on the performance challenges of FaaS cloud architectures. In: Companion of the 2018 ACM/SPEC International Conference on Performance Engineering, pp. 21–24 (2018)

    Google Scholar 

  25. Vicario, E.: Static analysis and dynamic steering of time-dependent systems. IEEE Trans. Softw. Eng. 27(8), 728–748 (2001)

    Article  Google Scholar 

  26. Vicario, E., Sassoli, L., Carnevali, L.: Using stochastic state classes in quantitative evaluation of dense-time reactive systems. IEEE Trans. Softw. Eng. 35(5), 703–719 (2009)

    Article  Google Scholar 

  27. Zheng, Z., Trivedi, K.S., Qiu, K., Xia, R.: Semi-Markov models of composite web services for their performance, reliability and bottlenecks. IEEE Trans. Serv. Comput. 10(3), 448–460 (2015)

    Article  Google Scholar 

  28. Zimmermann, A.: Modelling and performance evaluation with TimeNET 4.4. In: Bertrand, N., Bortolussi, L. (eds.) QEST 2017. LNCS, vol. 10503, pp. 300–303. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-66335-7_19

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Engineering, University of Florence, Florence, Italy

    Laura Carnevali, Riccardo Reali & Enrico Vicario

Authors
  1. Laura Carnevali
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Riccardo Reali
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Enrico Vicario
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Riccardo Reali .

Editor information

Editors and Affiliations

  1. RWTH Aachen University, Aachen, Germany

    Erika Ábrahám

  2. University of Southern California, Los Angeles, CA, USA

    Marco Paolieri

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Carnevali, L., Reali, R., Vicario, E. (2022). Eulero: A Tool for Quantitative Modeling and Evaluation of Complex Workflows. In: Ábrahám, E., Paolieri, M. (eds) Quantitative Evaluation of Systems. QEST 2022. Lecture Notes in Computer Science, vol 13479. Springer, Cham. https://doi.org/10.1007/978-3-031-16336-4_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-16336-4_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16335-7

  • Online ISBN: 978-3-031-16336-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics