Abstract
Industrial automation applications enforce strict requirements on the automation network, such as strict timing, upper bounded latency, low jitter, and essentially zero loss. Time sensitive networking (TSN) is an enabling technology for future automation networks. While most studies on TSN for industrial applications have focused on simple approaches to performance evaluation, we provide a comprehensive simulation based analysis for a typical industrial use case. We specify the network traffic produced by automation applications and associated TSN traffic classes. We model different network configurations such as priority queuing, time aware shaping, and credit based shaping to study how they meet the delay constraints of the different traffic classes. To evaluate the performance of our TSN based industrial network, we build and configured a network model and a set of application traffic models to generate realistic network traffic together with defined network design goals in OMNET ++. Our simulation results show that a TSN based network meets all application requirements.
| Original language | English |
|---|---|
| Title of host publication | 2022 IEEE 8th World Forum on Internet of Things, WF-IoT 2022 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781665491532 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | 8th IEEE World Forum on Internet of Things, WF-IoT 2022 - Hybrid, Yokohama, Japan Duration: 26 Oct 2022 → 11 Nov 2022 |
Publication series
| Name | 2022 IEEE 8th World Forum on Internet of Things, WF-IoT 2022 |
|---|
Conference
| Conference | 8th IEEE World Forum on Internet of Things, WF-IoT 2022 |
|---|---|
| Country/Territory | Japan |
| City | Hybrid, Yokohama |
| Period | 26/10/22 → 11/11/22 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- IIoT
- Industrial Networks
- OMNET++
- Resource management
- Time Sensitive Networking
Fingerprint
Dive into the research topics of 'TSN-based Industrial Network Performance Analysis'. Together they form a unique fingerprint.Prizes
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Best Paper Award at IEEE IoTime Workshop at IEEE WF-IoT
Seliem, M. (Recipient), Zahran, A. (Recipient) & Pesch, D. H. J. (Recipient), 11 Nov 2022
Prize
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