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Designing and simulating large networks, based on the Time-Sensitive Networking (TSN) standards, require complex and demanding configuration at the design and pre-simulation phases. The existing configuration and simulation frameworks support only the manual configuration of TSN networks. This hampers the applicability of these frameworks to large-sized TSN networks, especially in complex industrial embedded system applications. This paper proposes a modular framework to automate offline scheduling in TSN networks to facilitate the design time and pre-simulation automated network configurations as well as interpretation of the simulations. To demonstrate and evaluate the applicability of the proposed framework, a large TSN network is automatically configured and its performance is evaluated by measuring end-to-end delays of time-critical flows in a state-of-the-art simulation framework, namely NeSTiNg.

The IEEE Time-Sensitive Networking (TSN) standards' amendment 802.1Qbv provides real-time guarantees for Scheduled Traffic (ST) streams by the Time Aware Shaper (TAS) mechanism. In this paper, we develop offline schedule optimization objective functions to configure the TAS for ST streams, which can be effective to achieve a high Quality of Service (QoS) of lower priority Best-Effort (BE) traffic. This becomes useful if real-time streams from legacy protocols are configured to be carried by the BE class or if the BE class is used for value-added (but non-critical) services. We present three alternative objective functions, namely Maximization, Sparse and Evenly Sparse, followed by a set of constraints on ST streams. Based on simulated stream traces in OMNeT++/INET TSN NeSTiNg simulator, we compare our proposed schemes with a most commonly applied objective function in terms of overall maximum end-to-end delay and deadline misses of BE streams. The results confirm that changing the schedule synthesis objective to our proposed schemes ensures timely delivery and lower end-to-end delays in BE streams.

This paper presents a schedulability analysis for the Best-Effort (BE) traffic class within Time-Sensitive Networking (TSN) networks. The presented analysis considers several features in the TSN standards, including the Credit-Based Shaper (CBS), the Time-Aware Shaper (TAS), and the frame preemption. Although the BE class in TSN is primarily used for the traffic with no strict timing requirements, some industrial applications prefer to utilize this class for the non-hard real-time traffic instead of classes that use the CBS. The reason mainly lies in the fact that the complexity of TSN configuration becomes significantly high when the time-triggered traffic via the TAS and other classes via the CBS are used altogether. We demonstrate the applicability of the presented analysis on a vehicular application use case. We show that a network designer can get information on the schedulability of the BE traffic, based on which the network configuration can be further refined with respect to the application requirements. 

In this paper, we identify that the existing end-to-end data propagation delay analysis for distributed embedded systems can calculate pessimistic (over-estimated) analysis results when the nodes are synchronized. This is particularly the case of the Scheduled Traffic (ST) class in Time-sensitive Networking (TSN), which is scheduled offline according to the IEEE 802.1Qbv standard and the nodes are synchronized according to the IEEE 802.1AS standard. We present a comprehensive system model for distributed embedded systems that incorporates all of the above mentioned aspect as well as all traffic classes in TSN. We extend the analysis to support both synchronization and non-synchronization among the ECUs as well as offline schedules on the networks. The extended analysis can now be used to analyze all traffic classes in TSN when the nodes are synchronized without introducing any pessimism in the analysis results. We evaluate the proposed model and the extended analysis on a vehicular industrial use case.

In this paper, we present an end-to-end timing model to capture timing information from software architectures of distributed embedded systems that use network communication based on the Time-Sensitive Networking (TSN) standards. Such a model is required as an input to perform end-to-end timing analysis of these systems. Furthermore, we present a methodology that aims at automated extraction of instances of the end-to-end timing model from component-based software architectures of the systems and the TSN network configurations. As a proof of concept, we implement the proposed end-to-end timing model and the extraction methodology in the Rubus Component Model (RCM) and its tool chain Rubus-ICE that are used in the vehicle industry. We demonstrate the usability of the proposed model and methodology by modeling a vehicular industrial use case and performing its timing analysis.