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Service-oriented data acquisition and management for industrial cyber-physical systems
Shanghai Jiao Tong University.
Shanghai Jiao Tong University.
Shenyang Institute of Automation, China Academy of Science.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University.ORCID iD: 0000-0002-9315-9920
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2017 (English)In: Proceedings: 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 759-764, article id 8104867Conference paper, Published paper (Refereed)
Abstract [en]

 With rapid improvement in information and communication technologies, industrial automation systems are under the revolution. Legacy industrial automation systems lack flexibility and interoperability due to multi-layered architecture. From industrial cyber-physical system point of view, a new system architecture is needed to allow vertical and horizontal integration between all devices and systems from enterprise level to sensor level. In this paper, a RESTful service-oriented architecture is proposed for industrial controllers. By adopting RESTful services over HTTP methods, better efficiency for data acquisition from sensors, actuators, and controllers is achieved. In addition, service-oriented device management for industrial controllers is also implemented along with data acquisition. The reference architecture experiments on a car manufacturing demonstration line

Place, publisher, year, edition, pages
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 759-764, article id 8104867
Series
IEEE International Conference on Industrial Informatics INDIN, ISSN 1935-4576
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-67626DOI: 10.1109/INDIN.2017.8104867ISI: 000427453200114Scopus ID: 2-s2.0-85041218084ISBN: 978-1-5386-0837-1 (electronic)OAI: oai:DiVA.org:ltu-67626DiVA, id: diva2:1182443
Conference
15th IEEE International Conference on Industrial Informatics, INDIN 2017, University of Applied Science Emden/LeerEmden, Germany, 24-26 July 2017
Available from: 2018-02-13 Created: 2018-02-13 Last updated: 2019-08-14Bibliographically approved

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Vyatkin, Valeriy

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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Output format
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