Dissertation/Thesis Abstract

Enhancing the Internet of Things Architecture with Flow Semantics
by DeSerranno, Allen Ronald, D.B.A., University of South Florida, 2017, 152; 10636797
Abstract (Summary)

Internet of Things (‘IoT’) systems are complex, asynchronous solutions often comprised of various software and hardware components developed in isolation of each other. These components function with different degrees of reliability and performance over an inherently unreliable network, the Internet. Many IoT systems are developed within silos that do not provide the ability to communicate or be interoperable with other systems and platforms. Literature exists on how these systems should be designed, how they should interoperate, and how they could be improved, but practice does not always consult literature.

The work brings together a proposed reference architecture for the IoT and engineering practices for flow semantics found in existing literature with a commercial implementation of an IoT platform. It demonstrates that the proposed IoT reference architecture and flow-service-quality engineering practices when integrated together can produce a more robust system with increased functionality and interoperability. It shows how such practices can be implemented into a commercial solution, and explores the value provided to the system when implemented. This work contributes to the current understanding of how complex IoT systems can be developed to be more reliable and interoperable using reference architectures and flow semantics. The work highlights the value of integration of academic solutions with commercial implementations of complex systems.

Indexing (document details)
Advisor: Hevner, Alan, Mullarkey, Matthew
Commitee: Saunders, Carol S., de Vreede, Gert-Jan
School: University of South Florida
Department: Business
School Location: United States -- Florida
Source: DAI-A 79/03(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Business administration, Information Technology, Computer science
Keywords: IIoT, IoT, OPC UA, Ontology, Reference model, SCADA
Publication Number: 10636797
ISBN: 9780355463828
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