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The IEEE Time-Sensitive Networking (TSN) standards offer a promising solution to deal with the challenge of supporting high-bandwidth, low-latency, and predictable communication in distributed embedded systems. Although TSN provides a gate mechanism to support the low-jitter transmission of high-priority time-triggered traffic, it also brings complexity to the network design as the configuration of such mechanism together with support for low-priority transmission is non-trivial. Moreover, the combination of the gate mechanism and the Credit-based Shaper (CBS) mechanism in TSN deals with many configuration parameters, hence finding the most suitable configuration is complex. To avoid this complexity, the Best-effort (BE) class is sometimes used as an alternative channel to the classes that undergo the CBS mechanism, through which the real-time traffic without strict deadlines is transmitted with a minimum level of Quality of Service (QoS). On the other hand, the end stations that operate based on the legacy communication standards might not support the TSN's traffic shaping mechanisms, hence the designers need to assign the legacy traffic to use the BE class in a TSN network. To the extent of our knowledge, there is no implicit mechanism to support the QoS of BE in a TSN network. Hence, utilizing BE as an alternative to other classes must be guaranteed in terms of meeting the timing requirements, i.e., response times and end-to-end delays. Therefore, the work in this thesis aims at developing techniques and solutions to support the QoS of the lower-priority classes in TSN. In this regard, this work improves the scheduling solutions of high-priority time-triggered traffic to reduce the latency of BE traffic and develops techniques to verify the timing properties of BE traffic considering the impact of all other traffic classes in TSN. Furthermore, the work in this thesis extends the existing end-to-end data-propagation delay analysis for distributed real-time systems based on TSN networks. Finally, the applicability of the proposed techniques is verified and demonstrated by automotive application use cases.

The set of IEEE Time-Sensitive Networking (TSN) standards is an emerging candidate for backbone communication in modern applications of real-time distributed embedded systems. TSN provides various traffic shaping mechanisms that aim at managing the timing requirements of traffic. Emerging applications of these systems, particularly in the automotive domain, often run complex distributed software that requires low-latency and high-bandwidth communication across multiple onboard electronic control units. Using TSN in these systems introduces multiple challenges. Specifically, the developers of these systems face a lack of development techniques and tools, as TSN standards only offer general recommendations for the use of its features and mechanisms. There is an urgent need for development techniques, tools, and methods to assist the developers in effectively leveraging the features outlined in TSN standards. In this thesis, we identify and address several challenges encountered in the development of TSN-based distributed embedded systems, particularly focusing on the stages of system and software modeling, network configuration, and timing analysis. The overall goal of this thesis is to support the development of these systems in the aforementioned stages while considering the Quality of Service (QoS) requirements of all traffic classes in TSN. We present techniques to facilitate the system and software modeling of TSN-based distributed embedded systems. These techniques enable performing timing analysis in the early stages of system and software development. In the stage of network configuration, we propose techniques for managing the configuration complexity and supporting the automatic configuration of mechanisms in TSN. The proposed configuration techniques consider achieving acceptable QoS in various traffic classes. In the stage of timing analysis, we address the challenges of incorporating various TSN traffic classes and mechanisms by extending the existing timing analyses. The results indicate that the proposed techniques effectively facilitate the system and software modeling, network configuration, and timing analysis of TSN-based distributed embedded systems.

IEEE Time-Sensitive Networking (TSN) är en framväxande kommunikationsteknik för moderna tillämpningar inom distribuerade inbyggda realtidssystem. TSN definerar olika mekanismer för trafikomformning som syftar till att ge flexibilitet i hur fördröjningar och bandbredd fördelas mellan olika användare. Nya tillämpningar av distribuerade inbyggda system i realtid har ofta mycket komplex distribuerad programvara som kräver kommunikation med låg latens och hög bandbredd över flera enheter (ECU I automotiv system). Att anpassa sig till TSN för att utveckla sådana system innebär många utmaningar. Dessutom finns det en brist på stödtekniker för utvecklare eftersom TSN-standarder endast ger generaliserade rekommendationer för tillämpningen av dess mekanismer. Därför finns det ett behov av tekniker och metoder för att stödja utvecklare att använda tillgängliga funktioner i TSN-standarderna. I den här avhandlingen angriper vi några av utmaningarna i utvecklingsstadierna av TSN-baserade distribuerade inbyggda system som är modellering, konfiguration av nätverk och tidsanalys. Målet med avhandlingen är att stödja utvecklingen av TSN-baserade distribuerade inbyggda system i dessastadier, samtidigt som man tar hänsyn till Quality of Service (QoS) krav inom alla trafikklasser i TSN. Vi tillhandahåller tekniker för att underlätta system- och mjukvarumodellering av TSN-baserade distribuerade inbyggda system som ger ett verktyg för utvecklare att designa sina system i tidiga stadier av systemutveckling. Inom konfiguration av nätverk föreslår vi tekniker för att hantera komplexiteten och den automatiska konfigurationen av TSN-formningsmekanismer. Under tiden tar vi hänsyn till att nå en acceptabel QoS i olika trafikklasser. Inom tidsanalysen tar vi itu med utmaningarna med att införliva olika TSN-trafikklasser och mekanismer genom att utöka de befintliga tidsanalysmetoderna. Genom de tre bidragna tillvägagångssätten underlättar våra resultat processen att utveckla TSN-baserade distribuerade inbyggda system.