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Towards Self-Manageable and Adaptive Industrial Cyber-Physical Systems with Knowledge-Driven Autonomic Service Management
University of Auckland, Shanghai Jiao Tong University.
University of Auckland, Penza State University, Department of Computer Science, University of Penza, Computer Science Department, Penza State University, Penza.
Rockwell Automation Advanced Technologies, Mayfield Heights, Holobloc Inc., Cleveland Heigths.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0002-9315-9920
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Number of Authors: 52017 (English)In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 13, no 2, p. 725-736, article id 7523919Article in journal (Refereed) Published
Abstract [en]

An increasingly important goal of industrial automation systems is to continuously optimize physical resource utilization such as materials. Distributed automation is seen as one enabling technology for achieving this goal, in which networking controller nodes collaborate in a peer to peer way to form a new paradigm, namely industrial cyber-physical systems (iCPS). In order to achieve rapid response to changes from both high level control systems and plant environment, the proposed self-manageable agent relies on the use of the Service-Oriented Architecture (SOA) that improves flexibility and interoperability. It is enhanced by the autonomic service management (ASM) to implement software modifications in a fully automatic manner, thus achieving self-manageable and adaptive industrial cyberphysical systems. The architecture design of the autonomic service manager is provided and integration with SOA based execution environment is illustrated. Preliminary tests on selfmanagement are completed using a case study of airport baggage handling system.

Place, publisher, year, edition, pages
IEEE, 2017. Vol. 13, no 2, p. 725-736, article id 7523919
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-9724DOI: 10.1109/TII.2016.2595401ISI: 000399961500032Scopus ID: 2-s2.0-85018170448Local ID: 864e5e02-ebcf-409b-98d6-c3c45690963aOAI: oai:DiVA.org:ltu-9724DiVA, id: diva2:982662
Note

Validerad; 2017; Nivå 2; 2017-04-25 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-09-14Bibliographically approved

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Vyatkin, Valeriy

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