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Validation of High-Availability Model for Edge Devices and IIoT
Competitiveness in industry requires smooth, efficient, and high-quality operation. For some industrial applications or process control and monitoring applications, it is necessary to achieve high availability and reliability because, for example, the failure of availability in industrial production...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223726/ https://www.ncbi.nlm.nih.gov/pubmed/37430789 http://dx.doi.org/10.3390/s23104871 |
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author | Peniak, Peter Bubeníková, Emília Kanáliková, Alžbeta |
author_facet | Peniak, Peter Bubeníková, Emília Kanáliková, Alžbeta |
author_sort | Peniak, Peter |
collection | PubMed |
description | Competitiveness in industry requires smooth, efficient, and high-quality operation. For some industrial applications or process control and monitoring applications, it is necessary to achieve high availability and reliability because, for example, the failure of availability in industrial production can have serious consequences for the operation and profitability of the company, as well as for the safety of employees and the surrounding environment. At present, many new technologies that use data obtained from various sensors for evaluation or decision-making require the minimization of data processing latency to meet the needs of real-time applications. Cloud/Fog and Edge computing technologies have been proposed to overcome latency issues and to increase computing power. However, industrial applications also require the high availability and reliability of devices and systems. The potential malfunction of Edge devices can cause a failure of applications, and the unavailability of Edge computing results can have a significant impact on manufacturing processes. Therefore, our article deals with the creation and validation of an enhanced Edge device model, which in contrast to the current solutions, is aimed not only at the integration of various sensors within manufacturing solutions, but also brings the required redundancy to enable the high availability of Edge devices. In the model, we use Edge computing, which performs the recording of sensed data from various types of sensors, synchronizes them, and makes them available for decision making by applications in the Cloud. We focus on creating a suitable Edge device model that works with the redundancy, by using either mirroring or duplexing via a secondary Edge device. This enables high Edge device availability and rapid system recovery in the event of a failure of the primary Edge device. The created model of high availability is based on the mirroring and duplexing of the Edge devices, which support two protocols: OPC UA and MQTT. The models were implemented in the Node-Red software, tested, and subsequently validated and compared to confirm the required recovery time and 100% redundancy of the Edge device. In the contrast to the currently available Edge solutions, our proposed extended model based on Edge mirroring is able to address most of the critical cases, where fast recovery is required, and no adjustments are needed for critical applications. The maturity level of Edge high availability can be further extended by applying Edge duplexing for process control. |
format | Online Article Text |
id | pubmed-10223726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102237262023-05-28 Validation of High-Availability Model for Edge Devices and IIoT Peniak, Peter Bubeníková, Emília Kanáliková, Alžbeta Sensors (Basel) Article Competitiveness in industry requires smooth, efficient, and high-quality operation. For some industrial applications or process control and monitoring applications, it is necessary to achieve high availability and reliability because, for example, the failure of availability in industrial production can have serious consequences for the operation and profitability of the company, as well as for the safety of employees and the surrounding environment. At present, many new technologies that use data obtained from various sensors for evaluation or decision-making require the minimization of data processing latency to meet the needs of real-time applications. Cloud/Fog and Edge computing technologies have been proposed to overcome latency issues and to increase computing power. However, industrial applications also require the high availability and reliability of devices and systems. The potential malfunction of Edge devices can cause a failure of applications, and the unavailability of Edge computing results can have a significant impact on manufacturing processes. Therefore, our article deals with the creation and validation of an enhanced Edge device model, which in contrast to the current solutions, is aimed not only at the integration of various sensors within manufacturing solutions, but also brings the required redundancy to enable the high availability of Edge devices. In the model, we use Edge computing, which performs the recording of sensed data from various types of sensors, synchronizes them, and makes them available for decision making by applications in the Cloud. We focus on creating a suitable Edge device model that works with the redundancy, by using either mirroring or duplexing via a secondary Edge device. This enables high Edge device availability and rapid system recovery in the event of a failure of the primary Edge device. The created model of high availability is based on the mirroring and duplexing of the Edge devices, which support two protocols: OPC UA and MQTT. The models were implemented in the Node-Red software, tested, and subsequently validated and compared to confirm the required recovery time and 100% redundancy of the Edge device. In the contrast to the currently available Edge solutions, our proposed extended model based on Edge mirroring is able to address most of the critical cases, where fast recovery is required, and no adjustments are needed for critical applications. The maturity level of Edge high availability can be further extended by applying Edge duplexing for process control. MDPI 2023-05-18 /pmc/articles/PMC10223726/ /pubmed/37430789 http://dx.doi.org/10.3390/s23104871 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Peniak, Peter Bubeníková, Emília Kanáliková, Alžbeta Validation of High-Availability Model for Edge Devices and IIoT |
title | Validation of High-Availability Model for Edge Devices and IIoT |
title_full | Validation of High-Availability Model for Edge Devices and IIoT |
title_fullStr | Validation of High-Availability Model for Edge Devices and IIoT |
title_full_unstemmed | Validation of High-Availability Model for Edge Devices and IIoT |
title_short | Validation of High-Availability Model for Edge Devices and IIoT |
title_sort | validation of high-availability model for edge devices and iiot |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10223726/ https://www.ncbi.nlm.nih.gov/pubmed/37430789 http://dx.doi.org/10.3390/s23104871 |
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