Inference and propagation of performance constraints from abstract to concrete business workflows
Antonio García-Domínguez*, University of Cádiz; Inmaculada Medina-Bulo, University of Cádiz; Mariano Marcos-Bárcena, University of Cádiz
Abstract: Currently, manufacturing organizations of all sizes need to collaborate with others in order to meet their goals. However, achieving an adequate level of communication between their people and their information systems is difficult. Organizations are urged to formalize their processes and implement their information systems flexibly. These tasks can be achieved using workflows and service-oriented architectures, respectively. Abstract business-level workflows can be refined into executable workflows which compose services from the established service-oriented architecture, integrating disparate systems. However, it is hard to ensure that the target performance of the business process is achieved from the concrete software components. In this work, we present two algorithms which infer performance constraints for tasks in a workflow from its global and local restrictions. These tasks can be then further decomposed into nested subgraphs automatically. By repeatedly decomposing the tasks and inferring their constraints, target key performance indicator values can propagate from abstract business processes down to concrete activities.

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Improving applicability of workflow modelling
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