A journey into time-triggered communication protocols with a focus on Ethernet TSN

This presentation provides an historical perspective on time-triggered (TT) protocols and highlights a few possible misconceptions about TT communication. The presentation is organized as follows: 1) landscape of real-time (wired) communication networks, 2) Time-triggered (TT) protocols evolution: TTP, FlexRay, TTEthernet, TSN/TAS (IEEE802.1Qbv) 3) Misconceptions about TT communication 4) Takeaways and what is ahead of us

Towards Trusted Seamless Reconfiguration of IoT Nodes

IoT networks are growing rapidly with the addition of new sensors, nodes and devices to existing IoT networks. Due to the ever-increasing demand for IoT nodes to adapt to changing environment conditions and application requirements, the need for reconfiguring these already existing IoT nodes is increasing rapidly. A reconfiguration of an IoT network includes alterations to the devices connected, changing the behavioural patterns of the devices and modifying the software modules that control the IoT network and devices. Reconfiguring an already existing IoT network is a challenge due to the amount of data loss and network downtime faced when carrying out a reconfiguration procedure in a limited power supply environment. This paper proposes an architecture for trusted dynamic reconfiguration of IoT nodes with the least amount of data loss and downtime. The proposed approach uses multiple IoT nodes to facilitate dynamic reconfiguration

Towards Digital Twin-enabled DevOps for CPS providing Architecture-Based Service Adaptation & Verification at Runtime

Industrial Product-Service Systems (IPSS) denote a service-oriented (SO) way of providing access to CPS capabilities. The design of such systems bears high risk due to uncertainty in requirements related to service function and behavior, operation environments, and evolving customer needs. Such risks and uncertainties are well known in the IT sector, where DevOps principles ensure continuous system improvement through reliable and frequent delivery processes. A modular and SO system architecture complements these processes to facilitate IT system adaptation and evolution. This work proposes a method to use and extend the Digital Twins (DTs) of IPSS assets for enabling the continuous optimization of CPS service delivery and the latter's adaptation to changing needs and environments. This reduces uncertainty during design and operations by assuring IPSS integrity and availability, especially for design and service adaptations at CPS runtime. The method builds on transferring IT DevOps principles to DT-enabled CPS IPSS. The chosen design approach integrates, reuses, and aligns the DT processing and communication resources with DevOps requirements derived from literature. We use these requirements to propose a DT-enabled self-adaptive CPS model, which guides the realization of DT-enabled DevOps in CPS IPSS. We further propose detailed design models for operation-critical DTs that integrate CPS closed-loop control and architecture-based CPS adaptation. This integrated approach enables the implementation of A/B testing as a use case and central concept to enable CPS IPSS service adaptation and reconfiguration. The self-adaptive CPS model and DT design concept have been validated in an evaluation environment for operation-critical CPS IPSS. The demonstrator achieved sub-millisecond cycle times during service A/B testing at runtime without causing CPS operation interferences and downtime.Comment: Final published version appearing in 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2022

Just a Second -- Scheduling Thousands of Time-Triggered Streams in Large-Scale Networks

Deterministic real-time communication with bounded delay is an essential requirement for many safety-critical cyber-physical systems, and has received much attention from major standardization bodies such as IEEE and IETF. In particular, Ethernet technology has been extended by time-triggered scheduling mechanisms in standards like TTEthernet and Time-Sensitive Networking. Although the scheduling mechanisms have become part of standards, the traffic planning algorithms to create time-triggered schedules are still an open and challenging research question due to the problem's high complexity. In particular, so-called plug-and-produce scenarios require the ability to extend schedules on the fly within seconds. The need for scalable scheduling and routing algorithms is further supported by large-scale distributed real-time systems like smart energy grids with tight communication requirements. In this paper, we tackle this challenge by proposing two novel algorithms called Hierarchical Heuristic Scheduling (H2S) and Cost-Efficient Lazy Forwarding Scheduling (CELF) to calculate time-triggered schedules for TTEthernet. H2S and CELF are highly efficient and scalable, calculating schedules for more than 45,000 streams on random networks with 1,000 bridges as well as a realistic energy grid network within sub-seconds to seconds

Using Machine Learning to Speed Up the Design Space Exploration of Ethernet TSN networks

In this work, we ask if Machine Learning (ML) can provide a viable alternative to conventional schedulability analysis to determine whether a real-time Ethernet network meets a set of timing constraints. Otherwise said, can an algorithm learn what makes it difficult for a system to be feasible and predict whether a configuration will be feasible without executing a schedulability analysis? In this study, we apply standard supervised and unsupervised ML techniques and compare them, in terms of their accuracy and running times, with precise and approximate schedulability analyses in Network-Calculus. We show that ML techniques are efficient at predicting the feasibility of realistic TSN networks and offer new trade-offs between accuracy and computation time especially interesting for design-space exploration algorithms

A Survey of Scheduling in Time-Sensitive Networking (TSN)

TSN is an enhancement of Ethernet which provides various mechanisms for real-time communication. Time-triggered (TT) traffic represents periodic data streams with strict real-time requirements. Amongst others, TSN supports scheduled transmission of TT streams, i.e., the transmission of their packets by edge nodes is coordinated in such a way that none or very little queuing delay occurs in intermediate nodes. TSN supports multiple priority queues per egress port. The TAS uses so-called gates to explicitly allow and block these queues for transmission on a short periodic timescale. The TAS is utilized to protect scheduled traffic from other traffic to minimize its queuing delay. In this work, we consider scheduling in TSN which comprises the computation of periodic transmission instants at edge nodes and the periodic opening and closing of queue gates. In this paper, we first give a brief overview of TSN features and standards. We state the TSN scheduling problem and explain common extensions which also include optimization problems. We review scheduling and optimization methods that have been used in this context. Then, the contribution of currently available research work is surveyed. We extract and compile optimization objectives, solved problem instances, and evaluation results. Research domains are identified, and specific contributions are analyzed. Finally, we discuss potential research directions and open problems.Comment: 34 pages, 19 figures, 9 tables 110 reference