Title: Towards Memory-Efficient Traffic Policing in Time-Sensitive Networking

Abstract: Time-Sensitive Networking (TSN) is an emerging real-time Ethernet technology that provides deterministic communication for time-critical traffic. At its core, TSN relies on Time-Aware Shaper (TAS) for pre-allocating frames in specific time intervals and Per-Stream Filtering and Policing (PSFP) for mitigating the fatal disturbance of unavoidable frame drift. However, as first identified in this work, PSFP incurs heavy memory consumption during policing, hindering normal switching functionalities.
This work proposes a lightweight policing design called FooDog, which could facilitate sub-microsecond jitter with ultra-low memory consumption. FooDog employs a period-wise and stream-wise structure to realize the memory-efficient PSFP without loss of determinism. Results using commercial FPGAs in typical aerospace scenarios show that FooDog could keep end-to-end time-sensitive traffic jitter <150 nanoseconds in the presence of abnormal traffic, comparable to typical TSN performance without anomalies. Meanwhile, it consumes merely hundreds of kilobits of memory, reducing >90% of on-chip memory overheads than unoptimized PSFP design.