B-UFS: Uniform Resource Metric-Based Periodic Flow Scheduling in 5G-TSN Integrated Network

In modern intelligent factories, numerous applications require deterministic end-to-end latency for flow transmission. The 5G-TSN integrated network is aiming to meet the flow transmission requirements of time-critical applications. However, the heterogeneity between 5G and TSN, along with the non-deterministic nature of 5G, pose challenges in guaran-teeing bounded end-to-end latency. Therefore, an efficient flow scheduling algorithm becomes more crucial for deterministic communication in the 5G-TSN network. The majority of existing research focuses solely on allocating resources for either 5G or TSN, neglecting the investigation of joint resource allocation for both. This paper investigates the periodic flow scheduling problem, focusing on guaranteeing deterministic communication and the joint allocation of heterogeneous resources. We propose a novel heuristic algorithm that considers the urgency of flows, and quantifies heterogeneous resources uniformly to achieve a spatiotemporal load balancing across heterogeneous networks. Evaluation results demonstrate that our algorithm can achieve deterministic end-to-end latency for periodic flows and significantly enhance the schedulability of periodic flow sets.