P348 - Modellierung 2024

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Konferenzbeitrag
Modeling Classes of Body Sensor Networks
(Modellierung 2024, 2024) Carwehl, Marc; Reisig, Wolfgang
Computer-embedded systems frequently manifest in diverse variants, featuring slight differences in interfaces and functionalities, yet fundamentally grounded in a shared functional kernel. To address this variability, we propose to employ a schematic model of the functional kernel, from which concrete system instances are derived. This modeling methodology leverages well-established principles from predicate logic and Petri nets, augmented with the dynamic extensions provided by the \textsc{Heraklit} infrastructure. As a practical case study, we explore the realm of Body Sensor Networks (BSNs), a domain increasingly pivotal in the realm of medical diagnosis. Our work showcases the versatility and adaptability of our modeling framework in the context of BSNs, offering insights into its potential applications in the broader landscape of embedded systems and beyond.