Latency- and Jitter-Aware Traffic Scheduling for Hybrid Services in 5G-TSN Integrated Systems

In this paper, we investigate the hybrid traffic scheduling problem in 5G-TSN integrated systems, to achieve the endogenous deterministic communication for 5G. A novel strategy namely time-slot orchestration is proposed, and a latencyand jitter-aware traffic scheduling problem with the objective of maximizing the resource utilization is further formulated. To the best of our knowledge, it is the first time for such a problem being studied in the context of 5G-TSN integration. To solve this complex combinatorial optimization problem, a low-complexity heuristic scheduling algorithm is elaborately designed and extensively evaluated. Experimental results show that, compared with the optimal method derived from the genetic algorithm (GA) and the method based on the classical earliest deadline first (EDF) scheduling, the proposed method can efficiently enhance the endogenous deterministic communication capability of 5G by orders of magnitude, especially under high loads.

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Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1109/vtc2025-spring65109.2025.11174737
Primary Topic
Software-Defined Networks and 5G
Type
article
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Latency- and Jitter-Aware Traffic Scheduling for Hybrid Services in 5G-TSN Integrated Systems

Zening Liu, Yongming Huang, Feiyang Wang, Hongxin Lin et al.
Software-Defined Networks and 5G
article

Latency- and Jitter-Aware Traffic Scheduling for Hybrid Services in 5G-TSN Integrated Systems

Zening Liu, Yongming Huang, Feiyang Wang, Hongxin Lin, Cheng Zhang, Nian Xiong
article en

Abstract

In this paper, we investigate the hybrid traffic scheduling problem in 5G-TSN integrated systems, to achieve the endogenous deterministic communication for 5G. A novel strategy namely time-slot orchestration is proposed, and a latencyand jitter-aware traffic scheduling problem with the objective of maximizing the resource utilization is further formulated. To the best of our knowledge, it is the first time for such a problem being studied in the context of 5G-TSN integration. To solve this complex combinatorial optimization problem, a low-complexity heuristic scheduling algorithm is elaborately designed and extensively evaluated. Experimental results show that, compared with the optimal method derived from the genetic algorithm (GA) and the method based on the classical earliest deadline first (EDF) scheduling, the proposed method can efficiently enhance the endogenous deterministic communication capability of 5G by orders of magnitude, especially under high loads.

Purple Mountain Laboratories (CN), Southeast University (CN)
Openalex Percentile: Top 69%
Software-Defined Networks and 5G
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