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Time-Sensitive Networking (TSN) for Industrial Automation: Current Advances and Future DirectionsWith the introduction of Cyber-Physical Systems (CPS) and Internet of Things (IoT) technologies, the automation industry is undergoing significant changes, particularly in improving production efficiency and reducing maintenance costs. Industrial automation applications often need to transmit time- and safety-critical data to closely monitor and control industrial processes. Several Ethernet-based fieldbus solutions, such as PROFINET IRT, EtherNet/IP, and EtherCAT, are widely used to ensure real-time communications in industrial automation systems. These solutions, however, commonly incorporate additional mechanisms to provide latency guarantees, making their interoperability a grand challenge. The IEEE 802.1 Time-Sensitive Networking (TSN) task group was formed to enhance and optimize IEEE 802.1 network standards, particularly for Ethernet-based networks. These solutions can be evolved and adapted for cross-industry scenarios, such as large-scale distributed industrial plants requiring multiple industrial entities to work collaboratively. This paper provides a comprehensive review of current advances in TSN standards for industrial automation. It presents the state-of-the-art IEEE TSN standards and discusses the opportunities and challenges of integrating TSN into the automation industry. Some promising research directions are also highlighted for applying TSN technologies to industrial automation applications.
Document ID
20250002365
Acquisition Source
2230 Support
Document Type
Reprint (Version printed in journal)
Authors
Tianyu Zhang
(University of Iowa Iowa City, United States)
Gang Wang
(Emerson Automation Solutions)
Chuanyu Xue
(University of Connecticut Storrs, Connecticut, United States)
Jiachen Wang
(University of Connecticut Storrs, Connecticut, United States)
Mark S Nixon
(Emerson Automation Solutions)
Song Han
(University of Connecticut Storrs, Connecticut, United States)
Date Acquired
March 5, 2025
Publication Date
October 10, 2024
Publication Information
Publication: ACM Computing Surveys
Publisher: Association for Computing Machinery
Volume: 57
Issue: 2
Issue Publication Date: February 1, 2025
ISSN: 0360-0300
e-ISSN: 1557-7341
Subject Category
Computer Systems
Funding Number(s)
CONTRACT_GRANT: 80NSSC19K1076
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
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