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Next generation of industrial wireless networking are expected to integrate the capabilities of time-sensitive networking (TSN), providing the deterministic communication for industrial applications within wireless domain. Fifth Generation (5G) system integrates with TSN as a logical bridge to the TSN domain, supporting the coexistence of different traffic classes, such as periodic traffic, sporadic traffic and mobile broadband traffic. However, to simultaneously satisfy the bounded latency requirements of time-critical TSN services and the bandwidth requirements of nontime-critical 5G services, it is required to accurately schedule the data flows and efficiently allocate resources. In this article, we investigate resource slicing of the Radio Access Network (RAN) in 5G-TSN integration and some of the relevant related aspects. Particularly, we first introduce the background of TSN, 5G-TSN integration and RAN slicing. Then, the implementation of deterministic communication are briefly reviewed. Next, a RAN slicing framework based on an Artificial Intelligence (AI)-engine deployed in the fog node is presented for enabling the transmission of the deterministic and nondeterministic traffic flows. Last, an AI-based resource scheduling method for the RAN of 5G-TSN integration is proposed and simulations are carried out to investigate the performance of the proposed method.
Guan et al. (Tue,) studied this question.