Preprint
Time-Sensitive Networking (TSN) for Industrial Automation: Current Advances and Future Directions
arXiv.org
Cornell University
07/16/2024
DOI: 10.48550/arxiv.2306.03691
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 ZhangGang WangChuanyu XueJiachen WangMark NixonSong Han
- Resource Type
- Preprint
- Publication Details
- arXiv.org
- DOI
- 10.48550/arxiv.2306.03691
- eISSN
- 2331-8422
- Publisher
- Cornell University; Ithaca, New York
- Language
- English
- Date posted
- 07/16/2024
- Academic Unit
- Computer Science
- Record Identifier
- 9984696694202771
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