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COMPOSITIONAL MODELS FOR THE INTERNET OF THINGS

Published online by Cambridge University Press:  19 June 2023

Spencer Briener ,
Jooik Jung ,
Eswaran Subrahmanian  and
Ram Sriram
Spencer Briener
Affiliation:
National Insititute of Standards and Technology;
Jooik Jung
Affiliation:
National Insititute of Standards and Technology;
Eswaran Subrahmanian*
Affiliation:
National Insititute of Standards and Technology; Carnegie Mellon University
Ram Sriram
Affiliation:
National Insititute of Standards and Technology;
*
Subrahmanian, Eswaran, Carnegie Mellon University, United States of America, es3e@andrew.cmu.edu

Abstract

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The modularity of components has enhanced the ability to create IoT systems by composing them from off the shelf. However, the breadth of technological choices and capabilities of component devices has made designing these systems harder to select, compose, implement and test, especially for dynamic systems. In this paper, we adopt formal tools from category theory (CT), a branch of mathematics whose central tenet is compositionality, to generate models for IoT systems. More specifically, we introduce a port-graph operad to represent the architectural designs of IoT systems. We use presheaf categories to construct generic IoT schemas to support modularity. Given this information, we briefly describe its relationship to control strategies of dynamical systems that model the interaction of components. Our approach balances genericity and specificity, providing interlinked schematic representations of system architecture and component representation.

Keywords

Internet of ThingsSystems Engineering (SE)Design methodsProduct modelling / models
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1037 - 1046
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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