Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems

David Hästbacka; Jari Halme; Laurentiu Barna; Henrikki Hoikka; Henri Pettinen; Martin Larranaga; Mikael Bjorkbom; Heikki Mesia; Antti Jaatinen; Marko Elo

doi:10.1109/TII.2021.3071509

Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems

David Hästbacka, Jari Halme, Laurentiu Barna, Henrikki Hoikka, Henri Pettinen, Martin Larranaga, Mikael Bjorkbom, Heikki Mesia, Antti Jaatinen, Marko Elo

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Abstract

Industrial cyber-physical systems rely increasingly on data from IoT devices and other systems as continuously emerging use cases implement new intelligent features. Edge computing can be seen as an extension of the cloud in close physical proximity, in which some of the typical cloud computing loads are beneficial to run. This paper studies data analytics application development for integration of industrial IoT data and composition of application services executed on edge and cloud. A solution is designed to support heterogeneous hardware and run-time platforms, and focuses on the service layer that enables flexible orchestration of data flows and dynamic service compositions. The unified model and system architecture implemented, using the open Arrowhead Framework model, is verified through two representative industrial use cases.

Original language	English
Pages (from-to)	498-508
Number of pages	11
Journal	IEEE Transactions on Industrial Informatics
Volume	18
Issue number	1
Early online date	Apr 2021
DOIs	https://doi.org/10.1109/TII.2021.3071509
Publication status	Published - 2022
Publication type	A1 Journal article-refereed

Keywords

Arrowhead Framework
Cloud computing
Computer architecture
Condition monitoring
Cyber-physical systems
Edge computing
Interoperability
Monitoring
Production
Production monitoring
System architecture

Publication forum classification

Publication forum level 3

ASJC Scopus subject areas

Control and Systems Engineering
Information Systems
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TII.2021.3071509Licence: CC BY

Dynamic Edge and Cloud Service IntegrationFinal published version, 1.59 MBLicence: CC BY

https://urn.fi/URN:NBN:fi:tuni-202110267828Licence: CC BY

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Hästbacka, D., Halme, J., Barna, L., Hoikka, H., Pettinen, H., Larranaga, M., Bjorkbom, M., Mesia, H., Jaatinen, A., & Elo, M. (2022). Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems. IEEE Transactions on Industrial Informatics, 18(1), 498-508. https://doi.org/10.1109/TII.2021.3071509

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title = "Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems",

abstract = "Industrial cyber-physical systems rely increasingly on data from IoT devices and other systems as continuously emerging use cases implement new intelligent features. Edge computing can be seen as an extension of the cloud in close physical proximity, in which some of the typical cloud computing loads are beneficial to run. This paper studies data analytics application development for integration of industrial IoT data and composition of application services executed on edge and cloud. A solution is designed to support heterogeneous hardware and run-time platforms, and focuses on the service layer that enables flexible orchestration of data flows and dynamic service compositions. The unified model and system architecture implemented, using the open Arrowhead Framework model, is verified through two representative industrial use cases.",

keywords = "Arrowhead Framework, Cloud computing, Computer architecture, Condition monitoring, Cyber-physical systems, Edge computing, Interoperability, Monitoring, Production, Production monitoring, System architecture",

author = "David H{\"a}stbacka and Jari Halme and Laurentiu Barna and Henrikki Hoikka and Henri Pettinen and Martin Larranaga and Mikael Bjorkbom and Heikki Mesia and Antti Jaatinen and Marko Elo",

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Hästbacka, D, Halme, J, Barna, L, Hoikka, H, Pettinen, H, Larranaga, M, Bjorkbom, M, Mesia, H, Jaatinen, A & Elo, M 2022, 'Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems', IEEE Transactions on Industrial Informatics, vol. 18, no. 1, pp. 498-508. https://doi.org/10.1109/TII.2021.3071509

TY - JOUR

T1 - Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems

AU - Hästbacka, David

AU - Halme, Jari

AU - Barna, Laurentiu

AU - Hoikka, Henrikki

AU - Pettinen, Henri

AU - Larranaga, Martin

AU - Bjorkbom, Mikael

AU - Mesia, Heikki

AU - Jaatinen, Antti

AU - Elo, Marko

N1 - Publisher Copyright: CCBY

PY - 2022

Y1 - 2022

N2 - Industrial cyber-physical systems rely increasingly on data from IoT devices and other systems as continuously emerging use cases implement new intelligent features. Edge computing can be seen as an extension of the cloud in close physical proximity, in which some of the typical cloud computing loads are beneficial to run. This paper studies data analytics application development for integration of industrial IoT data and composition of application services executed on edge and cloud. A solution is designed to support heterogeneous hardware and run-time platforms, and focuses on the service layer that enables flexible orchestration of data flows and dynamic service compositions. The unified model and system architecture implemented, using the open Arrowhead Framework model, is verified through two representative industrial use cases.

AB - Industrial cyber-physical systems rely increasingly on data from IoT devices and other systems as continuously emerging use cases implement new intelligent features. Edge computing can be seen as an extension of the cloud in close physical proximity, in which some of the typical cloud computing loads are beneficial to run. This paper studies data analytics application development for integration of industrial IoT data and composition of application services executed on edge and cloud. A solution is designed to support heterogeneous hardware and run-time platforms, and focuses on the service layer that enables flexible orchestration of data flows and dynamic service compositions. The unified model and system architecture implemented, using the open Arrowhead Framework model, is verified through two representative industrial use cases.

KW - Arrowhead Framework

KW - Cloud computing

KW - Computer architecture

KW - Condition monitoring

KW - Cyber-physical systems

KW - Edge computing

KW - Interoperability

KW - Monitoring

KW - Production

KW - Production monitoring

KW - System architecture

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DO - 10.1109/TII.2021.3071509

M3 - Article

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SN - 1551-3203

VL - 18

SP - 498

EP - 508

JO - IEEE Transactions on Industrial Informatics

JF - IEEE Transactions on Industrial Informatics

IS - 1

ER -

Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems

Abstract

Keywords

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ASJC Scopus subject areas

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