journal article
Sep 15, 2023
A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT
Abstract
The scope of the Industrial Internet of Things (IIoT) has stretched beyond manufacturing to include energy, healthcare, transportation, and all that tomorrow’s smart cities will entail. The realm of IIoT includes smart sensors, actuators, programmable logic controllers, distributed control systems (DCS), embedded devices, supervisory control, and data acquisition systems—all produced by manufacturers for different purposes and with different data structures and formats; designed according to different standards and made to follow different protocols. In this sea of incompatibility, how can we flexibly acquire these heterogeneous data, and how can we uniformly structure them to suit thousands of different applications? In this article, we survey the four pillars of information science that enable collaborative data access in an IIoT—standardization, data acquisition, data fusion, and scalable architecture—to provide an up-to-date audit of current research in the field. Here, standardization in IIoT relies on standards and technologies to make things communicative; data acquisition attempts to transparently collect data through plug-and-play architectures, reconfigurable schemes, or hardware expansion; data fusion refers to the techniques and strategies for overcoming heterogeneity in data formats and sources; and scalable architecture provides basic techniques to support heterogeneous requirements. The article also concludes with an overview of the frontier researches and emerging technologies for supporting or challenging data access from the aspects of 5G, machine learning, blockchain, and semantic web.
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Cited By
35
Enhancing federated unlearning using catastrophic forgetting in heterogeneous Industrial Internet of Things
Computer Communications
Zhenguo Ma, Zixuan He · 2026
Metrics
35
Citations
270
References
Details
- Published
- Sep 15, 2023
- Vol/Issue
- 56(2)
- Pages
- 1-37
- License
- View
Authors
Funding
National Natural Science Foundation of China
Award: U21A20484
National Key R&D Program of China
Award: 2022YFB3304600
Science and Technology Program of Zhejiang Province
Award: 2022C01016
Cite This Article
Danfeng Sun, Junjie Hu, Huifeng Wu, et al. (2023). A Comprehensive Survey on Collaborative Data-access Enablers in the IIoT. ACM Computing Surveys, 56(2), 1-37. https://doi.org/10.1145/3612918
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