Exploiting Dependency-Aware Priority Adjustment for Mixed-Criticality TSN Flow Scheduling

TL;DR

This paper introduces a dependency-aware priority adjustment method for mixed-criticality TSN flow scheduling, reducing queuing delays and improving schedulability by dynamically adjusting priorities based on flow dependencies.

Contribution

It proposes a novel priority adjustment scheme that considers flow dependencies and link conditions, significantly improving schedulability over existing static priority methods.

Findings

Schedulability improved by 20.57% over state-of-the-art methods.

Dependency-aware algorithms effectively reduce queuing delays.

Dynamic priority adjustment enhances real-time transmission guarantees.

Abstract

Time-Sensitive Networking (TSN) serves as a one-size-fits-all solution for mixed-criticality communication, in which flow scheduling is vital to guarantee real-time transmissions. Traditional approaches statically assign priorities to flows based on their associated applications, resulting in significant queuing delays. In this paper, we observe that assigning different priorities to a flow leads to varying delays due to different shaping mechanisms applied to different flow types. Leveraging this insight, we introduce a new scheduling method in mixed-criticality TSN that incorporates a priority adjustment scheme among diverse flow types to mitigate queuing delays and enhance schedulability. Specifically, we propose dependency-aware priority adjustment algorithms tailored to different link-overlapping conditions. Experiments in various settings validate the effectiveness of the proposed method, which enhances the schedulability by 20.57% compared with the SOTA method.