Dynamical Orchestration and Configuration Services in Industrial IoT Systems: An Autonomic Approach
The Industrial Internet of Things (IIoT) enables the integration of physical devices such as sensors and actuators into the virtual world of automation application systems via different communication protocols. Interoperability among the “things” appears to be one of the bigges...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Open Journal of the Industrial Electronics Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9706288/ |
| _version_ | 1797974800228941824 |
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| author | An Ngoc Lam Oystein Haugen Jerker Delsing |
| author_facet | An Ngoc Lam Oystein Haugen Jerker Delsing |
| author_sort | An Ngoc Lam |
| collection | DOAJ |
| description | The Industrial Internet of Things (IIoT) enables the integration of physical devices such as sensors and actuators into the virtual world of automation application systems via different communication protocols. Interoperability among the “things” appears to be one of the biggest conceptual and technological challenges in developing the IIoT framework. Typically, collaboration at the field device level is very limited. Instead, the decision-making process is usually propagated to higher levels with substantial computational resources. This centralized architecture has been widely deployed based on global cloud infrastructure. However, sending data over the cloud for analysis may bring about privacy and security threats. Besides, network latency could be another factor that reduces adaptability. In this article, we propose a decentralized approach that applies the concepts of local automation cloud. By using semantic technologies to achieve autonomicity, the approach enables real-time monitoring of the control systems within one local cloud and automates orchestration and configuration locally through adaptation based on semantic policies. The approach is deployed and tested on a chemical production use case in which business-level policies have been used for dynamical planning for suppliers and automatic detection of malfunctioning sensors with subsequent adaptation to continuing supply planning and production as smooth as possible. |
| first_indexed | 2024-04-11T04:25:28Z |
| format | Article |
| id | doaj.art-eb06bbb6a1504c308e7da5f2f4db5382 |
| institution | Directory Open Access Journal |
| issn | 2644-1284 |
| language | English |
| last_indexed | 2024-04-11T04:25:28Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Industrial Electronics Society |
| spelling | doaj.art-eb06bbb6a1504c308e7da5f2f4db53822022-12-30T00:00:34ZengIEEEIEEE Open Journal of the Industrial Electronics Society2644-12842022-01-01312814510.1109/OJIES.2022.31490939706288Dynamical Orchestration and Configuration Services in Industrial IoT Systems: An Autonomic ApproachAn Ngoc Lam0https://orcid.org/0000-0003-4929-054XOystein Haugen1https://orcid.org/0000-0002-0567-769XJerker Delsing2https://orcid.org/0000-0002-4133-3317Faculty of Computer Science, Engineering and Economics, Østfold University College, Halden, NorwayFaculty of Computer Science, Engineering and Economics, Østfold University College, Halden, NorwayDepartment of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, SwedenThe Industrial Internet of Things (IIoT) enables the integration of physical devices such as sensors and actuators into the virtual world of automation application systems via different communication protocols. Interoperability among the “things” appears to be one of the biggest conceptual and technological challenges in developing the IIoT framework. Typically, collaboration at the field device level is very limited. Instead, the decision-making process is usually propagated to higher levels with substantial computational resources. This centralized architecture has been widely deployed based on global cloud infrastructure. However, sending data over the cloud for analysis may bring about privacy and security threats. Besides, network latency could be another factor that reduces adaptability. In this article, we propose a decentralized approach that applies the concepts of local automation cloud. By using semantic technologies to achieve autonomicity, the approach enables real-time monitoring of the control systems within one local cloud and automates orchestration and configuration locally through adaptation based on semantic policies. The approach is deployed and tested on a chemical production use case in which business-level policies have been used for dynamical planning for suppliers and automatic detection of malfunctioning sensors with subsequent adaptation to continuing supply planning and production as smooth as possible.https://ieeexplore.ieee.org/document/9706288/Arrowhead frameworkautonomic computingindustrial IoTself-adaptationsemantic interoperabilitysemantic web |
| spellingShingle | An Ngoc Lam Oystein Haugen Jerker Delsing Dynamical Orchestration and Configuration Services in Industrial IoT Systems: An Autonomic Approach IEEE Open Journal of the Industrial Electronics Society Arrowhead framework autonomic computing industrial IoT self-adaptation semantic interoperability semantic web |
| title | Dynamical Orchestration and Configuration Services in Industrial IoT Systems: An Autonomic Approach |
| title_full | Dynamical Orchestration and Configuration Services in Industrial IoT Systems: An Autonomic Approach |
| title_fullStr | Dynamical Orchestration and Configuration Services in Industrial IoT Systems: An Autonomic Approach |
| title_full_unstemmed | Dynamical Orchestration and Configuration Services in Industrial IoT Systems: An Autonomic Approach |
| title_short | Dynamical Orchestration and Configuration Services in Industrial IoT Systems: An Autonomic Approach |
| title_sort | dynamical orchestration and configuration services in industrial iot systems an autonomic approach |
| topic | Arrowhead framework autonomic computing industrial IoT self-adaptation semantic interoperability semantic web |
| url | https://ieeexplore.ieee.org/document/9706288/ |
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