Journal article
Time-Sensitive Networking (TSN) for Industrial Automation: Current Advances and Future Directions
ACM computing surveys, Vol.57(2), 30
10/10/2024
DOI: 10.1145/3695248
Appears in UI Libraries Support Open Access
Abstract
With 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.
Details
- Title: Subtitle
- Time-Sensitive Networking (TSN) for Industrial Automation: Current Advances and Future Directions
- Creators
- Tianyu Zhang - University of IowaGang WangChuanyu Xue - University of ConnecticutJiachen Wang - University of ConnecticutMark Nixon - Emerson (Sweden)Song Han - University of Connecticut
- Resource Type
- Journal article
- Publication Details
- ACM computing surveys, Vol.57(2), 30
- DOI
- 10.1145/3695248
- ISSN
- 0360-0300
- eISSN
- 1557-7341
- Publisher
- Association for Computing Machinery; NEW YORK
- Grant note
- National Science Foundation: CNS-1932480, CNS-2008463, CCF-2028875, CNS-1925706 NASA STRI Resilient Extraterrestrial Habitats Institute (RETHi): 80NSSC19K1076
The work is supported in part by the National Science Foundation Grant CNS-1932480, CNS-2008463, CCF-2028875, CNS-1925706, and the NASA STRI Resilient Extraterrestrial Habitats Institute (RETHi) under grant number 80NSSC19K1076.
- Language
- English
- Electronic publication date
- 09/09/2024
- Date published
- 10/10/2024
- Academic Unit
- Computer Science
- Record Identifier
- 9984702834902771
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