TL;DR
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.
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.
The nascTime framework on OMNeT++/Simu5G is used to evaluate how many TSN endpoints a single 5G NR cell can bridge before per-flow QoS degrades, showing that sub-3 ms TSN deadlines may require radio-configuration changes such as configured grants or higher numerology.
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.
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.
Time-Sensitive Networking (TSN) provides guaranteed traffic delivery, making it essential for industrial automation, multimedia, automotive systems, and other areas. Although TSN is well-established in wired networks, wireless systems face extra challenges such as delays, interference, and unstable links. Extending TSN to wireless (WTSN) thus adds complexity, particularly in managing traffic. This paper proposes a data-driven solution leveraging Digital Twin (DT) modeling to enhance WTSN management. We focus on mitigating the residual service time (RST) problem introduced by non-TSN traffic generators, which increases link latency. Implemented in a real Wi-Fi TSN-based environment, our implementation demonstrates that delay prediction through WTSN-DT reduces application link latency by up to 96% at the 90th percentile in a real Wi-Fi TSN setting, relative to fixed time slot allocation.
: Mobile edge services require deterministic communication across Time-Sensitive Networking (TSN) and 5G access, where the standardized integration architecture exposes the 5G System (5GS) to the TSN controller as a logical bridge. We study dynamic admission of time-triggered (TT) flows using reported 5GS bridge delay and TSN-to-5GS Quality of Service (QoS) mapping in route selection and Gate Control List (GCL) scheduling. Arrivals and departures can split available transmission time into noncontiguous windows. Online insertion preserves admitted schedules but may reduce subsequent schedulability, whereas full recomputation can restore schedulability but changes many routes and GCL entries, complicating coordinated activation. Coupling routing and GCL scheduling under timing, bridge-delay, QoS-mapping, and a bound on changes to admitted schedules yields an NP-hard problem. To address it, we propose a two-timescale scheduling mechanism. The fast timescale uses current 5GS bridge information to place arrivals without modifying admitted flows. Fragmented windows, repeated insertion failures, or changes in reported 5GS state invoke the slower timescale, which sequentially reschedules a bounded subset of admitted flows and commits only feasible improvements. At 0.95 offered load across A380, CEV, and Ring6, admission improves by 14.8–18.5 percentage points over online-only scheduling and remains within 1.7–2.2 points of full recomputation, while per-event runtime falls by over one order of magnitude with limited GCL changes.
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