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Partitioning Workflows for Decentralized Execution

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Cloud Computing and Services Science (CLOSER 2011)

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Abstract

Service-oriented workflows in the scientific domain are commonly modelled from a data flow perspective as directed acyclic graphs (DAGs); Web services represent the vertices and directed edges are formed by connecting a group of services together. When orchestrating service-oriented workflows, intermediate data are typically routed through a single centralised engine, which results in unnecessary data transfer, increasing the execution time of a workflow and causing the engine to become a performance bottleneck. This paper introduces an architecture for decentralized orchestration of service-oriented DAG-based workflows. A workflow is divided into a set of vertices, disseminated to a group of proxies and executed without centralised control over a peer-to-peer proxy network. Through a Web services implementation, we demonstrate that by reducing intermediate data transfer and by sharing the workload between distributed proxies, end-to-end workflows are sped up.

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Notes

  1. 1.

    http://webast.ast.obs-mip.fr/hyperz/.

  2. 2.

    http://ws.apache.org/xmlrpc/types.html.

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Authors and Affiliations

  1. School of Computer Science, University of St Andrews, St Andrews, Scotland, UK

    Adam Barker

Authors
  1. Adam Barker
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Correspondence to Adam Barker .

Editor information

Editors and Affiliations

  1. SUNY Empire State College, Hauppauge, 11788, New York, USA

    Ivan Ivanov

  2. , Centre for Telematics and Information Te, University of Twente, Enschede, 7500 AE, The Netherlands

    Marten van Sinderen

  3. Collaboration & Research on, Enterprise Systems &, Interdisciplinary Institute for, Sofia, Bulgaria

    Boris Shishkov

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Barker, A. (2012). Partitioning Workflows for Decentralized Execution. In: Ivanov, I., van Sinderen, M., Shishkov, B. (eds) Cloud Computing and Services Science. CLOSER 2011. Service Science: Research and Innovations in the Service Economy. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2326-3_7

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  • DOI: https://doi.org/10.1007/978-1-4614-2326-3_7

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-2325-6

  • Online ISBN: 978-1-4614-2326-3

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