End-to-end delay performance analysis of the 5G-TSN network using network calculus
The emerging Ultra-Reliable and Low-Latency Communication (URLLC) of the Fifth Generation Communication Network (5G) makes the integration of Time-Sensitive Networking (TSN) and 5G communication access possible. Unfortunately, there is a lack of a theoretical study for analyzing the end-to-end (E2E) delay upper bound of different characteristic traffic in the integrated 5G-TSN scenario. Furthermore, current scheduling solutions are not able to meet the scheduling demands of different hybrid traffic in the integrated 5G-TSN network. To address these issues, this article proposes an improved strict-priority Deficit Round-Robin (SP-DRR) scheduling strategy 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. In this framework, the TSN wired segment is characterized through Time-Aware Shaper (TAS)/Credit-Based Shaper (CBS)-related service curves, the 5G wireless segment is modeled using Jake’s fading-based MGF service characterization with Meijer G-functions, and the 5G core segment is represented by the proposed SP-DRR scheduling strategy. These heterogeneous service components are mapped into a common ($\sigma_{s},\rho_{s}$)-bounded form and concatenated within the stochastic network calculus framework to derive the final E2E delay-violation bound. The results demonstrate that the proposed SP-DRR-MGF analysis matches the simulation results well under different operating conditions. Under the considered parameter settings and quasi-stationary fading assumption, the results indicate that the wireless segment becomes the dominant bottleneck once the wired-side service rate exceeds a certain threshold. The wireless resource scheduling strategy is the key to the E2E service guarantee in the 5G-TSN scenarios. Moreover, related parameters such as weight, quantum, and the number of allocated resource blocks (RBs) should be appropriately allocated to improve E2E delay according to a match requirement of delay upper bound and reliability. These observations provide stronger evidence that the proposed theoretical framework can serve not only as an effective approximation tool for realistic 5G-TSN networks, but also as a useful sensitivity-analysis and design-guidance tool for parameter tuning in practical deployments.