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Applying semantics into Service-oriented IoT Framework
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab. Faculty of Computer Sciences, Østfold University College, Halden, Norway.ORCID iD: 0000-0003-4929-054X
Faculty of Computer Sciences, Østfold University College, Halden, Norway.
2019 (English)In: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE, 2019, p. 206-213Conference paper, Published paper (Other academic)
Abstract [en]

Introducing semantics into the Internet of Things (IoT) has been attracting increasing attention from researchers and industrial practitioners. Semantic technologies have been used to enable interoperability as well as deal with the heterogeneity, massive scale, and dynamic nature of IoT resources. With the emergence of Industry 4.0, semantic technologies arise as a potential approach toward information modeling and dynamic reconfiguration of highly complex automation systems with high diversity of domains, protocols, tools or hardware platforms. Applying semantics into existing IoT frameworks requires a thorough understanding of the framework architectures as well as careful considerations of different semantic technologies. To support this process, we survey the literature on the contributions and usage of semantics in IoT. We find that semantics are mainly used to handle interoperable systems and heterogeneous standards. In this paper, we also propose procedures for applying semantics into IoT frameworks. Further, we present our idea of using semantics to enable dynamical orchestration of services within the Arrowhead Framework - an IoT framework that supports the development of industrial automation systems.

Place, publisher, year, edition, pages
IEEE, 2019. p. 206-213
Series
IEEE International Conference on Industrial Informatics (INDIN), ISSN 1935-4576, E-ISSN 2378-363X
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Industrial Electronics
Identifiers
URN: urn:nbn:se:ltu:diva-79450DOI: 10.1109/INDIN41052.2019.8972295ISI: 000529510400029Scopus ID: 2-s2.0-85079034951OAI: oai:DiVA.org:ltu-79450DiVA, id: diva2:1439488
Conference
2019 IEEE 17th International Conference on Industrial Informatics (INDIN), 22-25 July, 2019, Helsinki-Espoo, Finland
Note

ISBN för värdpublikation: 978-1-7281-2927-3, 978-1-7281-2928-0

Available from: 2020-06-12 Created: 2020-06-12 Last updated: 2022-10-31Bibliographically approved
In thesis
1. Dynamic Adaptation in Industrial IoT Systems
Open this publication in new window or tab >>Dynamic Adaptation in Industrial IoT Systems
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The evolution of the current technological landscape has opened an emergent paradigm that enables interoperability between the digital and physical world, leading to a new generation of industrial systems. This new digitalization era marks the beginning of the fourth industrial revolution, usually referred to as "Industry 4.0". By employing recent technologies and concepts such as Industrial Internet of Things (IIoT), Cyber-physical Systems (CPS), Cloud-based technologies, , Service-oriented Architecture (SoA), and Artificial Intelligence (AI), the Industry 4.0 approach aims to address the dynamic evolution of contemporary requirements as well as improve the sustainability and efficiency in industrial production. 

While this new industrial paradigm facilitates the integration and collaboration among industrial components, it also introduces greater complexity to the industrial systems, thereby potentially increasing costs related to system development and maintenance. Specifically, significant engineering effort is dedicated to addressing the heterogeneity, interoperability and scalability of those integrated components. As a result, in order to mitigate those challenges, the self-adaptive solution appears as a potential approach to automate the management and supervision of the systems. Self-adaptation allows the system to adapt in the face of changes in its operating environment and in the system itself without human intervention.

This thesis outlines the progress made towards self-adaptation in industrial production. It proposes an architectural design that enables dynamic adaptation for IIoT systems. Particularly, in order to facilitate the integration of heterogeneous and numerous physical components, the proposed approach shifts from tightly-coupled automation systems to loosely-coupled flexible information and communication infrastructure by employing service-oriented and decentralized technologies. Furthermore, the concept of Autonomic Computing (AC) is exploited to address the interoperability among the systems with the goal to enable autonomous decision-making based on real-time information from the integrated components.   

To illustrate the potential of this design, an Autonomic Adaptation System is proposed to provide dynamic adaptation as a service in order to assist IIoT systems to re-orchestrate the communication among them or re-configure their internal functionality. The prototype of the system has been implemented and tested with a simulated industrial use case.

Place, publisher, year, edition, pages
Luleå University of Technology, 2021
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords
Autonomic Computing, Industrial IoT, Self-adaptation, Semantic Interoperability, System of Systems
National Category
Computer Systems
Research subject
Cyber-Physical Systems
Identifiers
urn:nbn:se:ltu:diva-88637 (URN)978-91-8048-003-1 (ISBN)978-91-8048-004-8 (ISBN)
Public defence
2022-02-22, A1545, 10:00 (English)
Opponent
Supervisors
Funder
EU, Horizon 2020, 826452EU, Horizon 2020, 737459
Available from: 2022-01-03 Created: 2022-01-03 Last updated: 2022-10-31Bibliographically approved

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Lam, An Ngoc

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