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Cited by 11IoT and Edge/Fog ComputingDigital Transformation in IndustryIndustrial Automation and Control Systems

The DOI matches its Crossref record; 28 of the 29 references it cites were found in a registry or an index, and 1 are not checked yet.

Validation of High-Availability Model for Edge Devices and IIoT

Open access
Peniak, Peter, Bubeníková, Emília, Kanáliková, Alžbeta·2023·Sensors
DOI 10.3390/s23104871PMC PMC10223726
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Abstract

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.

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Crossref · 10.3390/s23104871

Cites

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Figures

Figure 1 The traditional approach (a), Edge-based (b), and Edge with High-Availability approach (c).
Figure 1 The traditional approach (a), Edge-based (b), and Edge with High-Availability approach (c).CC BY · PubMed Central
Figure 2 The concept of traditional IIoT integration (a) and generic Edge based approach (b).
Figure 2 The concept of traditional IIoT integration (a) and generic Edge based approach (b).CC BY · PubMed Central
Figure 3 The generic Edge model.
Figure 3 The generic Edge model.CC BY · PubMed Central
Figure 4 The availability of sensors values x’i within publishing time tp by Edge basic model.
Figure 4 The availability of sensors values x’i within publishing time tp by Edge basic model.CC BY · PubMed Central
Figure 5 The concept of basic Edge model (a) with off-line Edge2 (b).
Figure 5 The concept of basic Edge model (a) with off-line Edge2 (b).CC BY · PubMed Central
Figure 6 The Edge recovery model.
Figure 6 The Edge recovery model.CC BY · PubMed Central
Figure 7 The basic Edge model with off-line Edge2.
Figure 7 The basic Edge model with off-line Edge2.CC BY · PubMed Central
Figure 8 The concept of extended Edge model with mirroring by Edge2 in case the right activity (a), in case of Edge failure (b).
Figure 8 The concept of extended Edge model with mirroring by Edge2 in case the right activity (a), in case of Edge failure (b).CC BY · PubMed Central
Figure 9 The extended Edge device da model with mirroring.
Figure 9 The extended Edge device da model with mirroring.CC BY · PubMed Central
Figure 10 The concept of extended Edge duplexing in case the right activity (a), in case of Edge failure (b).
Figure 10 The concept of extended Edge duplexing in case the right activity (a), in case of Edge failure (b).CC BY · PubMed Central
Figure 11 The extended Edge device model with duplexing.
Figure 11 The extended Edge device model with duplexing.CC BY · PubMed Central
Figure 12 Experimental workplace for validation of high-availability Edge model with default configuration (a) and in case of Edge failure (b).
Figure 12 Experimental workplace for validation of high-availability Edge model with default configuration (a) and in case of Edge failure (b).CC BY · PubMed Central
Figure 13 Node-RED flows for experimental validation of high-availability Edge models.
Figure 13 Node-RED flows for experimental validation of high-availability Edge models.CC BY · PubMed Central
Figure 14 OPC Ua Expert connected to Edge1 OPC UA server with sensor values from Figure 13.
Figure 14 OPC Ua Expert connected to Edge1 OPC UA server with sensor values from Figure 13.CC BY · PubMed Central
Figure 15 Node-RED console during initialization of Edge flows.
Figure 15 Node-RED console during initialization of Edge flows.CC BY · PubMed Central
Figure 16 Edge Variant 2 -High-availability/Fail-over with HeartBeat flow.
Figure 16 Edge Variant 2 -High-availability/Fail-over with HeartBeat flow.CC BY · PubMed Central
Figure 17 Edge basic model and simulation of Edge1 failure—phase 1: Detection of failure.
Figure 17 Edge basic model and simulation of Edge1 failure—phase 1: Detection of failure.CC BY · PubMed Central
Figure 18 Edge basic model and simulation of Edge1 failure—phase 2: Application malfunction.
Figure 18 Edge basic model and simulation of Edge1 failure—phase 2: Application malfunction.CC BY · PubMed Central
Figure 19 Edge basic model and simulation of Edge1 failure—phase 3: Edge restart.
Figure 19 Edge basic model and simulation of Edge1 failure—phase 3: Edge restart.CC BY · PubMed Central
Figure 20 Edge basic model and simulation of Edge1 failure—phase 4: Edge recovery.
Figure 20 Edge basic model and simulation of Edge1 failure—phase 4: Edge recovery.CC BY · PubMed Central
Figure 21 Generated and processed data by application during Edge failure and recovery.
Figure 21 Generated and processed data by application during Edge failure and recovery.CC BY · PubMed Central
Figure 22 Edge enhanced model—Variant 2: Mirroring—Failure detection.
Figure 22 Edge enhanced model—Variant 2: Mirroring—Failure detection.CC BY · PubMed Central
Figure 23 Fail-over process initiated by Edge2—Variant 2.
Figure 23 Fail-over process initiated by Edge2—Variant 2.CC BY · PubMed Central
Figure 24 IIoT sensor model for Node-RED—Variant 3 and Edge duplexing.
Figure 24 IIoT sensor model for Node-RED—Variant 3 and Edge duplexing.CC BY · PubMed Central

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Citations

Cites

Show all 28 references

Research works printed but not linked: 2

  1. Mahmud, R., Kotagiri, R., and Buyya, R. (2018). Internet of Everything. Internet of Things, Springer.
  2. Harjula, E., Artemenko, A., and Forsström, S. (2020). Wireless Networks and Industrial IoT, Springer.

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Metadata

Authors
Peniak, P., Bubeníková, E., & Kanáliková, A.
Affiliations
University of Žilina (SK)
Corresponding author
Kanáliková, Alžbeta
ORCID
Venue
Sensors
Publisher
MDPI AG
Published
2023-05-18
Volume
23
Issue
10
Pages
4871
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s23104871
PMC
PMC10223726
OpenAlex
W4377138651
Cited by
11
References
28
Citations by year
2026: 4 · 2025: 2 · 2024: 2 · 2023: 3
FWCI
1.22
Type
journal article
Language
en
Open access
Licence
Locations
  • Sensors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Cultural and Educational Grant Agency MŠVVaŠ SR (008ŽU-4/2021)
  • University of Žilina (008ŽU-4/2021)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
  • Physical Sciences › Engineering › Control and Systems Engineering › Industrial Automation and Control Systems
Keywords
edge computing, high availability, Industrial Internet of Things, redundancy, mirroring, duplexing, fault recovery, OPC UA, MQTT, Node-RED, sensor synchronization, fog computing, manufacturing process control

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CoChat. (2026). Citation check: Validation of High-Availability Model for Edge Devices and IIoT. https://app.cochat.ai/papers/10.3390/s23104871
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Peniak, P., Bubeníková, E., & Kanáliková, A. (2023). Validation of High-Availability Model for Edge Devices and IIoT. Sensors. https://doi.org/10.3390/s23104871