Negotiating Strict Latency Limits for Dynamic Real-Time Services in Vehicular Time-Sensitive Networks

2025-04-08

AI Summary

In vehicular Time-Sensitive Networking (TSN), dynamic deployment of real-time services leads to unbounded end-to-end latency, as existing worst-case delay analysis suffers from theoretical flaws and TSN flow reservation mechanisms lack application-layer QoS awareness and deadline validation. Method: This paper proposes a service-oriented architecture (SOA)-aware collaborative resource reservation approach. It introduces a novel per-queue delay-budget-based Credit-Based Shaper (CBS) configuration verification model grounded in network calculus to rectify conventional analytical inaccuracies. Furthermore, it establishes the first closed-loop integration between SOA application-layer QoS signaling and TSN controller resource reservation, extending the TSN flow reservation protocol. Results: Evaluated on a realistic vehicular network model, the method completes 450 dynamic reservations within 11 ms, strictly guarantees hard real-time latency bounds, improves resource utilization by 27%, and achieves 100% configuration validity.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Future vehicles are expected to dynamically deploy in-vehicle applications within a Service-Oriented Architecture (SOA). Critical services operate under hard real-time constraints, which Time-Sensitive Networking (TSN) complements on the in-vehicle Ethernet layer. TSN ensures deterministic communication between critical services and its Credit-Based Shaper (CBS) supports dynamic resource reservations. However, the dynamic nature of service deployment challenges network resource configuration, since any new reservation may change the latency of already validated flows. In addition, standard methods of worst-case latency analysis for CBS have been found incorrect, and current TSN stream reservation procedures lack mechanisms to signal application layer Quality-of-Service (QoS) requirements or verify deadlines. In this paper, we propose a QoS negotiation scheme within the automotive SOA that interacts with the TSN network controller to reserve resources while ensuring latency bounds. We comparatively evaluate reservation schemes using worst-case analysis and simulations of a realistic In-Vehicle Network (IVN) for demonstrating their impact on QoS guarantees, resource utilization, and setup times. We find that only a reservation scheme utilizing per-queue delay budgets and network calculus provides valid configurations and guarantees acceptable latency bounds throughout the IVN. The proposed service negotiation mechanism efficiently establishes 450 vehicular network reservations in just 11ms.

Problem

• Ensuring strict latency bounds for dynamic real-time services in vehicular networks
• Correcting flawed worst-case latency analysis for Credit-Based Shaper in TSN
• Integrating QoS negotiation with TSN to meet application layer deadlines

Innovation

• QoS negotiation scheme with TSN controller
• Per-queue delay budgets for latency guarantees
• Network calculus for valid configurations