3 research outputs found

    Computing the Parallelism Degree of Timed BPMN Processes

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    International audienceA business process is a combination of structured and related activities that aim at fulfilling a specific organizational goal for a customer or market. An important measure when developing a business process is the degree of parallelism, namely, the maximum number of tasks that are executable in parallel at any given time in a process. This measure determines the peak demand on tasks and thus can provide valuable insight on the problem of resource allocation in business processes. This paper considers timed business processes modeled in BPMN, a workflow-based graphical notation for processes, where execution times can be associated to several BPMN constructs such as tasks and flows. An encoding of timed business processes into Maude's rewriting logic system is presented, enabling the automatic computation of timed degrees of parallelism for business processes. The approach is illustrated with a simple yet realistic case study in which the degree of parallelism is used to improve the business process design with the ultimate goal of optimizing resources and, therefore, with the potential for reducing operating costs

    Quantifying the Parallelism in BPMN Processes using Model Checking

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    International audienceA business process is a set of structured, related activities that aims at fulfilling a specific organizational goal for a customer or market. An important metric when developing a business process is its degree of parallelism, i.e., the maximum number of tasks that are executable in parallel in that process. The degree of parallelism determines the peak demand on tasks, providing a valuable guide for the problem of resource allocation in business processes. In this paper, we investigate how to automatically measure the degree of parallelism for business processes, described using the BPMN standard notation. We first present a formal model for BPMN processes in terms of Labelled Transition Systems, which are obtained through process algebra encodings. We then propose an approach for automatically computing the degree of parallelism by using model checking techniques and dichotomic search. We implemented a tool for automating this check and we applied it successfully to more than one hundred BPMN processes

    Acquisition of Multi-Band Signals via Compressed Sensing

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