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AVB-Aware Optimized Routing and Scheduling of Time-Triggered Traffic in Time-Sensitive Networks

Jul 2026 · ACM Transactions on Embedded Computing Systems · Vol 25, pp. 1 - 30 · 0 citations · 34 references

TL;DR

A unified routing and scheduling framework that jointly optimizes TT communication while systematically improving AVB performance is presented, which significantly improves AVB schedulability and delay bounds while maintaining TT feasibility with low computational overhead.

Abstract

Time-Sensitive Networking (TSN) supports mixed-criticality communication by integrating Time-Triggered (TT) and Audio Video Bridging (AVB) traffic within a unified network infrastructure. While TT flows benefit from deterministic scheduling through the Time-Aware Shaper (TAS), their presence can increase the worst-case delay (WCD) experienced by AVB traffic. However, many existing AVB-aware TT scheduling approaches incur high computational costs and lack a theoretical foundation for analyzing the impact of TT routing on AVB performance. To address these limitations, this article presents a unified routing and scheduling framework that jointly optimizes TT communication while systematically improving AVB performance. At the core of our method is a network calculus-based analysis that derives a theoretical lower bound on AVB WCD under TT interference. This bound is consistently leveraged in both the routing and scheduling stages: first, to define a flow-level metric called Impact on WCD (IoW) that guides AVB-aware routing decisions; and second, to introduce an AVB-Aware Idle Constraint that regulates TT offsets to shape residual bandwidth for AVB traffic. Extensive experiments across diverse topologies and traffic patterns demonstrate that the proposed framework significantly improves AVB schedulability and delay bounds while maintaining TT feasibility with low computational overhead. These results confirm the practicality and effectiveness of a tightly integrated approach to TSN configuration for mixed-criticality systems.

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