Traffic Shaping Mechanism Based on Time Slot-Aware Cyclic Queuing and Forwarding in Time-Sensitive Networking

CAI Yueping; REN Zhiwen

doi:10.11999/JEIT220530

Volume 45 Issue 6

Jun. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(6): 1999-2006

ZHANG Tianqi, QUAN Shengrong, QIANG Xingzi, JIANG Xiaolei. Time-frequency Analysis Method Based on Multi-scale Chirplet Sparse Decomposition and Wigner-Ville Transform[J]. Journal of Electronics & Information Technology, 2017, 39(6): 1333-1339. doi: 10.11999/JEIT160750

Citation:

CAI Yueping, REN Zhiwen. Traffic Shaping Mechanism Based on Time Slot-Aware Cyclic Queuing and Forwarding in Time-Sensitive Networking[J]. Journal of Electronics & Information Technology, 2023, 45(6): 1999-2006. doi: 10.11999/JEIT220530

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Traffic Shaping Mechanism Based on Time Slot-Aware Cyclic Queuing and Forwarding in Time-Sensitive Networking

doi: 10.11999/JEIT220530

CAI Yueping^,,
REN Zhiwen

School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400030, China

Funds: The National Key Research and Development Program of China (2020YFB1710900)

Received Date: 2022-04-27
Rev Recd Date: 2022-10-25

Available Online: 2022-11-18

Publish Date: 2023-06-10

Abstract

Abstract

Time sensitive network is one of the core technologies of future smart factories. There are multiple business flows with different requirements in smart factories. To ensure the performance of critical traffic flows and improve network bandwidth utilization, a Time Slot-Aware Cyclic Queuing and Forwarding (TSA-CQF) mechanism is proposed. TSA-CQF improves bandwidth utilization by inserting low-priority traffic into the remaining available time slots of the CQF queues. TSA-CQF mechanism includes slot-aware insertion of low-priority traffic and global traffic planning for low-priority traffic. The first part of TSA-CQF is to insert low-priority traffic into the remaining time slots of the CQF queues. The global traffic planning is modeled as a multi-conditional objective optimization problem, and it is solved by the simulated annealing algorithm to accept as many flows as possible to increase the bandwidth utilization. Simulation results show that TSA-CQF improves the bandwidth utilization by 11.29% on average compared with the traditional CQF mechanism under mixed traffic conditions.
- Industrial internet,
- Time-Sensitive Network (TSN),
- Traffic shaping,
- Bandwidth utilization

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References(18)

References

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