TY - JOUR
T1 - A comprehensive survey on collaborative data-access enablers in the IIoT
AU - Sun, Danfeng
AU - Hu, Junjie
AU - Wu, Huifeng
AU - Wu, Jia
AU - Yang, Jian
AU - Sheng, Quan Z.
AU - Dustdar, Schahram
PY - 2024/2
Y1 - 2024/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85174703122&partnerID=8YFLogxK
U2 - 10.1145/3612918
DO - 10.1145/3612918
M3 - Article
AN - SCOPUS:85174703122
SN - 0360-0300
VL - 56
SP - 1
EP - 37
JO - ACM Computing Surveys
JF - ACM Computing Surveys
IS - 2
M1 - 50
ER -