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Scalable business process execution in the cloud


Sven Euting, Christian Janiesch, Stefan Tai and Ingo Weber

University of Karlsruhe




Business processes orchestrate service requests in a structured fashion. Process knowledge, however, has rarely been used to predict and decide about cloud infrastructure resource usage. In this paper, we present an approach for BPM-aware cloud computing that builds on process knowledge to improve the timeliness and quality of resource scaling decisions. We introduce an IaaS resource controller based on fuzzy theory that monitors process execution and is used to predict and control resource requirements for subsequent process tasks. In a laboratory experiment, we evaluate the controller design against a commercially available state-of-the-art auto scaler. Based on the results, we discuss improvements and limitations, and suggest directions for further research.

BibTeX Entry

    author           = {Euting, Sven and Janiesch, Christian and Tai, Stefan and Weber, Ingo},
    month            = mar,
    year             = {2014},
    keywords         = {cloud computing; business process management; fuzzy control; elasticity},
    address          = {Boston, MA, USA},
    title            = {Scalable Business Process Execution in the Cloud},
    pages            = {175--184},
    booktitle        = {IEEEInternational Conference on Cloud Computing}


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