FlexTAS: Flexible Gating Control for Enhanced Time-Sensitive Networking Deployment

Time-sensitive networking (TSN), essential in industrial networks for its promise of reliable and deterministic data transmission, faces deployment challenges due to the limitations of existing time-aware shaper (TAS)-based scheduling algorithms. Specifically, the size of the generated gate control lists (GCLs) is usually too large to be deployed in actual devices. To bridge the gap between theory and practice, we propose FlexTAS, a flexible and practical solution for TSN. The key insight behind FlexTAS is that relaxing gating does not introduce uncertainty, as long as nonoverlap reserved time slots are guaranteed. FlexTAS is comprised of two main components: first, a novel gating model deviates from the conventional TAS model by incorporating selective relaxation of gating at certain nodes; and second, a deep reinforcement learning-based engine to rapidly generate valid schedules. We build a real testbed and validate the effectiveness of our proposed solution. Our evaluation demonstrates that FlexTAS effectively controls the number of gate entries within the GCL capacity of devices, while simultaneously meeting the Quality of Service(QoS) requirements of time-triggered streams. It significantly reduces the number of GCL entries by 60% to 80%, and facilitates deployment in heterogeneous networks, thus offering a practical solution for TSN.