2026· IEEE Open Journal of the Communications Society· Vol 7, pp. 8714-8730· 0 citations· 34 references
Computer Science
TL;DR
Simulation results demonstrate that the proposed QoS-mapping-based no-wait latency-balanced joint scheduling (QMLB-JS) algorithm improves the end-to-end deterministic transmission capability of the integrated 5G-TSN network.
Abstract
Fifth-generation (5G) and time-sensitive networking (TSN) are widely recognized as the most promising technologies for future industrial networks. Quality of service (QoS) mapping and traffic scheduling mechanisms are critical to ensuring deterministic transmission in 5G-TSN integrated networks. However, the uncertainty of 5G air-interface delay significantly reduces the deterministic guarantee for traffic in 5G-TSN networks. A QoS mapping algorithm based on incremental mini-batch K-means++ stratified sampling (IMK-S3) is proposed to quickly and accurately determine the 5G QoS identifier (5QI) values of traffic flows, even under dynamic traffic variations. Based on this, combined with cross-layer scheduling optimization, a QoS-mapping-based no-wait latency-balanced joint scheduling (QMLB-JS) algorithm is proposed. QMLB-JS supports hold and forward buffer mechanism in DS-TT and NW-TT, and realizes accurate time-based gating management by orchestrating the time of time-triggered (TT) traffic injection into the network. Simulation results demonstrate that the proposed algorithm improves the end-to-end deterministic transmission capability of the integrated 5G-TSN network.
An improved strict-priority Deficit Round-Robin (SP-DRR) scheduling strategy is proposed and incorporates it into a unified moment generating function (MGF) analytical framework, referred to as SP-DRR-MGF, for probabilistic E2E delay analysis in 5G–TSN networks.
Xiaohuan Zhang, Jiancheng Qin, Yiqin Lu et al.· PeerJ Computer Science· 0 citations
The integration of Time-Sensitive Networking (TSN) and 5G is essential for deterministic industrial communication over mixed wired–wireless networks. In 3GPP TSN–5G integration, the 5G System (5GS) is modeled as a logical TSN bridge for Time-Aware Shaper (TAS) scheduling. However, Time Division Duplex (TDD) operation in 5GS introduces the transmission waiting time, and conventional bridge-delay-based scheduling must rely on conservative worst-case assumptions.In this paper, we analyze the periodic structure of TDD-induced waiting time and show that its worst-case value is determined by the TDD pattern, TSN flow period, and their phase offset. Based on this insight, we propose a phase-aware TAS scheduling method that derives a mapping between phase offsets and worst-case waiting times and incorporates it into E2E TAS scheduling. Simulations under multiple TSN flow periods and TDD patterns show that the proposed method consistently reduces worst-case waiting time compared with the conventional approach. Multiple flow evaluations also show that multiple TSN flows can be scheduled while satisfying E2E delay constraints under the evaluated configuration. This enables more flexible deployment of time-critical industrial IoT applications, including mobile robot control, motion control, and factory automation over mixed wired–wireless networks.
Keita Kuwayama, H. Kawata, Hironao Abe et al.· International Conference on...· 0 citations
The development of immersive video service and large-scale cluster computing technology further expand the potential application scope of time-sensitive networks (TSN). In the delivery network for these emerging services, Ultra-Service Flows (USFs), characterized by ultra-high bandwidth and deterministic latency, have become the most representative traffic type. Therefore, the route scheduling for hybrid deployment of Regular-Service Flows (RSFs) and USF has become an unavoidable issue within a deterministic domain. However, existing research has not thoroughly investigated routing issues for the hybrid deployment of USF and RSF since the significant differences between them. To resolve this issue, a multi-objective optimization model is designed in this paper, in which three key factors are comprehensively considered: the path blocking degree of USF, the available bandwidth rate, and the end-to-end latency of RSF. Subsequently, we propose a cooperative framework where a Transformer-DRL agent, enforced by validity-constraint masking, generates high-quality initial populations to “warm start” NSGA-II. This hybrid design replaces random initialization, effectively resolving the evolutionary “cold start” issue in large-scale topologies while ensuring routing feasibility. The simulation results demonstrate that the algorithm proposed here in significantly improves performance and generalization capabilities, improving the RSF’s overall latency, the USF’s path-blocking degree, and the available bandwidth rate by 10.526%, 14.102%, and 14.286%, respectively.
Mengjie Guo, Qiang Wu, Ran Wang et al.· IEEE Transactions on Network...· 0 citations
A unified routing and scheduling framework that jointly optimizes TT communication while systematically improving AVB performance is presented, which significantly improves AVB schedulability and delay bounds while maintaining TT feasibility with low computational overhead.
Meng Wang, Yiqin Lu, Haihan Wang et al.· ACM Transactions on Embedded...· 0 citations
B-CUBE is proposed, a novel burst-aware 5G-TSN architecture that equips each industrial node with co-deployed TSN and 5G system bridges to enable wired, wireless, and dual-mode transmission, and designs a set of e-cient cross-domain mixed-flow scheduling algorithms.
Yi Xue, Jie Jia, Hao-Yang Mao et al.· Science China Information Sc...· 0 citations
Network slicing is an enabling technology of fifth-generation (5G) mobile networks that enables several autonomous logical networks to exist on a common physical infrastructure. One key issue of the paradigm is the admission control mechanism which slice requests are accepted to achieve the best performance of the system and still ensure quality-of-service (QoS) guarantees. In this paper, the authors provide a comparative study of the current methods of admission control and introduce a new approach, Priority-Aware Deep Q-Network with Dynamic Threshold Adaptation (PA-DQN-DTA). Our method (as opposed to the traditional methods which tie admission control to resource allocation) addresses intelligent admission decisions only. The suggested scheme uses inter-slice and intra-slice priorities via a mathematically defined admission probability functional. The outcomes of simulation in four assessment scenarios show that parameter calibration is of the essence: the balanced configuration reaches acceptance ratios of 11.812.9, and QoE in all scenarios is above 98.8%. Besides, this paper presents an in-depth analysis of parameter tuning and describes the space of tradeoffs between the acceptance ratio, the QoE preservation, and the resource usage. Concrete recommendations are made and implications to the realistic 5G deployment are discussed.
A. S. Mahore, C. N. Deshmukh· International Conference Com...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
