Path Optimization and Scheduling Design for Industrial Time-Triggered Ethernet

In the context of Industry 4.0, real-time and reliable communication has become essential for industrial control, automotive electronics, and aerospace applications, which demand high determinism and low-delay data transmission. Recently, Time-triggered Ethernet (TTE) has emerged as a promising solution to satisfy these stringent requirements. However, existing methods fail to guarantee schedulability in large-scale TTE networks, and traditional path planning relies on the shortest path principle without accounting for link load, potentially causing congestion. This paper first establishes a periodic-oriented time-triggered constraint model and proposes a constraint reduction strategy to expand the solvable scale of the TTE networks. Our study further analyzes the impact of time slot discretization on network delay and proposes a non-fixed time slot allocation strategy, which effectively improves the utilization of time slot resources and reduces the solution complexity. Then a path optimization strategy based on the Army Ant Search Optimizer is proposed to balance link load and re-plan the transmission paths for each traffic. Furthermore, this paper introduces an incremental scheduling strategy, incorporating priority-aware into the scheduling process to ensure preferential treatment for critical traffic. Finally, an improved network calculus method is employed to derive the worst-case delay upper bounds for RC traffic on each link. The methods this paper propose are validated in different network scenarios, including industrial, in-vehicle, and Airbus A380 topologies. It is compared against other state-of-the-art algorithms, such as shortest path, particle swarm optimization and simulated annealing algorithms. Evaluation results indicate that our methods can effectively reduce network delay, lower the worst-case delay of RC traffic, and improve the uniformity of delay across these scenarios.