Mixed-Criticality Flow Scheduling with Low Delay and Limited Bandwidth in TSN
2026-05-11 • Networking and Internet Architecture
Networking and Internet Architecture
AI summaryⓘ
The authors focus on improving a network protocol called Time-Sensitive Networking (TSN), which is used in systems needing precise timing like cars and factories. They noticed that as more data flows compete for the same time slots, delays can increase. To fix this, they created MCFS-2L, which smartly combines and separates data frames based on priority to fit better in the schedule. Their method helps send more critical and non-critical data with less bandwidth used, making the network more efficient.
Time-Sensitive NetworkingTSNframe aggregationmixed-criticalityflow schedulingbandwidth utilizationdeterministic transmissiondynamic reassemblytime windows
Authors
Wenyan Yan, Sijing Duan, Dongsheng Wei
Abstract
Time-Sensitive Networking (TSN) is a promising Ethernet protocol with time determinism, widely used in time-critical systems such as industrial automation, automotive networks, and avionics. By allocating dedicated time windows for time-sensitive flows, TSN enables deterministic transmission; however, as network traffic grows, multiple flows may contend for the same window, causing large delays. Frame aggregation can mitigate this by combining multiple small frames into a larger one, thereby reducing the number of frames and required time windows, but existing approaches typically handle only single-priority traffic and cannot fully utilize pre-allocated time windows. To address this limitation, we propose MCFS-2L, a mixed-criticality flow scheduling scheme with low delay and limited bandwidth usage. MCFS-2L first aggregates critical and non-critical frames with the same source and destination nodes and harmonic periods into a single frame, and then applies a dynamic reassembly and scheduling method that selectively disaggregates non-critical frames from unschedulable aggregated frames. Experimental results show that MCFS-2L increases the acceptance ratio of critical and non-critical flows by up to 4.78% and 8.58%, respectively, while reducing bandwidth utilization by up to 11.88%.