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Modeling Classes of Body Sensor Networks

dc.contributor.authorCarwehl, Marc
dc.contributor.authorReisig, Wolfgang
dc.contributor.editorMichael, Judith
dc.contributor.editorWeske, Mathias
dc.date.accessioned2024-02-19T11:27:58Z
dc.date.available2024-02-19T11:27:58Z
dc.date.issued2024
dc.description.abstractComputer-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.en
dc.identifier.doi10.18420/modellierung2024_008
dc.identifier.isbn978-3-88579-742-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/43632
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofModellierung 2024
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-348
dc.subjectPetri nets
dc.subjectHeraklit
dc.subjectBody Sensor Network
dc.titleModeling Classes of Body Sensor Networksen
dc.typeText/Conference Paper
gi.citation.endPage82
gi.citation.publisherPlaceBonn
gi.citation.startPage65
gi.conference.date12.-15. March 2024
gi.conference.locationPotsdam, Germany
gi.conference.sessiontitleSystems Design

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