Research Article

Simulating Taverna workflows using stochastic process algebras

  1. Vasa Curcin1,*,
  2. Paolo Missier2,
  3. David De Roure3

Article first published online: 2 JUN 2011

DOI: 10.1002/cpe.1757

Issue

Concurrency and Computation: Practice and Experience

Concurrency and Computation: Practice and Experience

Special Issue: Special Issue Fourth International Workshop On Workflow Management (ICWM2009)

Volume 23, Issue 16, pages 1920–1935, November 2011

Additional Information

How to Cite

Curcin, V., Missier, P. and De Roure, D. (2011), Simulating Taverna workflows using stochastic process algebras. Concurrency Computat.: Pract. Exper., 23: 1920–1935. doi: 10.1002/cpe.1757

Author Information

  1. 1

    Department of Computing, Imperial College, London, U.K.

  2. 2

    School of Computing Science, Newcastle University, Newcastle, U.K.

  3. 3

    Oxford e-Research Centre, University of Oxford, Oxford, U.K.

*Department of Computing, Imperial College, London, U.K.

Publication History

  1. Issue published online: 3 OCT 2011
  2. Article first published online: 2 JUN 2011
  3. Manuscript Accepted: 21 FEB 2011
  4. Manuscript Received: 22 NOV 2010

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Keywords:

  • scientific workflows;
  • process modelling;
  • stochastic modelling;
  • Taverna;
  • workflows

Abstract

Scientific workflows provide powerful middleware for scientific computing in that they represent a central abstraction in the research task by simultaneously acting as an editable action plan, collaboration tool, and executable entity. Taverna workflows, in particular, have been widely accepted in the bioinformatics community, due to their flexible integration with web service analytical tools that are the essential tools of any bioinformatician. However, the semantics of Taverna have so far only been qualified in terms of the functional composition and data processing. While correct, and useful for reasoning about functional and trace equivalences, this aspect does not help with modelling the throughput and utilization of individual services in the workflow. In this paper we present a stochastic process model for Taverna, and use it to perform execution simulations in Microsoft's SPIM tool. The model also opens up the possibilities for further static analyses that are explored. Copyright © 2011 John Wiley & Sons, Ltd.

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