Search

Time-Sensitive Networking (TSN) extends IEEE 802.1 Ethernet for safety-critical and real-time applications in several areas, for example, automotive, aerospace or industrial automation. However, many of these systems also have stringent security requirements, and security attacks may impair safety. Given a TSN-based distributed architecture, a set of applications with tasks and messages as well as a set of security and redundancy requirements, the authors are interested to synthesise a system configuration such that the real-time, safety and security requirements are upheld. The Timed Efficient Stream Loss-Tolerant Authentication (TESLA) low-resource multicast authentication protocol is used to guarantee the security requirements and redundant disjunct message routes to tolerate link failures. The authors consider that tasks are dispatched using a static cyclic schedule table and that the messages use the time-sensitive traffic class in TSN, which relies on schedule tables (called Gate Control Lists, GCLs) in the network switches. A configuration consists of the schedule tables for tasks as well as the disjoint routes and GCLs for messages. A Constraint Programing-based formulation, which can be used to find an optimal solution with respect to the cost function, is proposed. Additionally, a Simulated Annealing-based metaheuristic, which can find good solution for large test cases, is proposed. The authors evaluate both approaches on several test cases.

Modern Advanced Driver-Assistance Systems (ADAS) combine critical real-time and non-critical best-effort tasks and messages onto an integrated multi-core multi-SoC hardware platform. The real-time safety-critical software tasks have complex interdependencies in the form of end-to-end latency chains featuring, e.g., sensing, processing/sensor fusion, and actuating. The underlying real-time operating systems running on top of the multi-core platform use static cyclic scheduling for the software tasks, while the communication backbone is either realized through PCIe or Time-Sensitive Networking (TSN). In this paper, we address the problem of configuring ADAS platforms for automotive applications, which means deciding the mapping of tasks to processing cores and the scheduling of tasks and messages. Time-critical messages are transmitted in a scheduled manner via the timed-gate mechanism described in IEEE 802.1Qbv according to the pre-computed Gate Control List (GCL) schedule. We study the computation of the assignment of tasks to the available platform CPUs/cores, the static schedule tables for the real-time tasks, as well as the GCLs, such that task and message deadlines, as well as end-to-end task chain latencies, are satisfied. This is an intractable combinatorial optimization problem. As the ADAS platforms and applications become increasingly complex, such problems cannot be optimally solved and require problem-specific heuristics or metaheuristics to determine good quality feasible solutions in a reasonable time. We propose two metaheuristic solutions, a Genetic Algorithm (GA) and one based on Simulated Annealing (SA), both creating static schedule tables for tasks by simulating Earliest Deadline First (EDF) dispatching with different task deadlines and offsets. Furthermore, we use a List Scheduling-based heuristic to create the GCLs in platforms featuring a TSN backbone. We evaluate the proposed solution with real-world and synthetic test cases scaled to fit the

Modern Advanced Driver-Assistance Systems (ADAS) merge critical and non-critical software functions with complex timing requirements and inter-dependencies onto the same integrated hardware platform. Real-time safety-critical automotive applications feature complex dependency chains between tasks (e.g., performing sensing, processing and actuation) which have to satisfy worst-case end-to-end latency constraints. The resulting scheduling problem requires both the assignment of tasks to the available cores of the platform and the computation static schedule tables for the real-time tasks, such that task deadlines, as well as end-to-end task chain constraints, are satisfied. We propose a heuristic approach based on Simulated Annealing (SA) which creates static schedule tables by simulating Earliest Deadline First (EDF) scheduling parameterized by task offsets and local deadlines decided by SA. We evaluate the proposed solution with real-world and synthetic test cases scaled to fit the future requirements of ADAS systems.

Distributed safety-critical applications in industrial automation, aerospace, and automotive, require worst-case end-to-end latency analysis for critical communication flows in order to prove their correct behavior in the temporal domain.With the advent of Time Sensitive Networks (TSN), distributed applications can be built on top of standard Ethernet technologies without sacrificing real-time characteristics. The time-based transmission selection and clock synchronization mechanism defined in TSN enable the real-time transmission of frames based on a global schedule configured through so-called Gate Control Lists (GCLs). This paper has an enhancement of allowing a mixture of the priority-based scheduling and time-triggered, which expand the solution space for GCLs. Then, it is necessary to analyze the latency bounds for the critical traffic in the TSN network. In this work, we start from the assumption that the GCLs, i.e. the communication schedules, and the traffic class (priority) assignment for critical flows are given for each output port and derive, using network calculus, an analysis of the worst-case delays that individual critical flows can experience along the hops from sender to receiver(s). Our method can be employed for the analysis of TSN networks where the GCLs have been created in advance, as well as for driving the GCL synthesis that explores a larger solution space than previous methods, which required a complete isolation of transmission events from different traffic classes. We validate our model and analysis by performing experiments on both synthetic and real-world use-cases, showing the scalability of our implementation as well as the impact of certain GCL properties (gate overlapping and traffic class assignments) on the worst-case latency of critical communication flows.

In this paper we are interested in safety-critical real-time applications implemented on distributed architectures supporting the Time-SensitiveNetworking (TSN) standard. The ongoing standardization of TSN is an IEEE effort to bring deterministic real-time capabilities into the IEEE 802.1 Ethernet standard supporting safety-critical systems and guaranteed Quality-of-Service. TSN will support Time-Triggered (TT) communication based on schedule tables, Audio-Video-Bridging (AVB) flows with bounded end-to-end latency as well as Best-Effort messages. We first present a survey of research related to the optimization of distributed cyber-physical systems using real-time Ethernet for communication. Then, we formulate two novel optimization problems related to the scheduling and routing of TT and AVB traffic in TSN. Thus, we consider that we know the topology of the network as well as the set of TT and AVB flows. We are interested to determine the routing of both TT and AVB flows as well as the scheduling of the TT flows such that all frames are schedulable and the AVB worst-case end-to-end delay is minimized. We have proposed an Integer Linear Programming (ILP) formulation for the scheduling problem and a Greedy Randomized Adaptive Search Procedure (GRASP)-based heuristic for the routing problem. The proposed approaches have been evaluated using several test cases.

We introduce variable-bandwidth servers (VBS) for scheduling and executing processes under programmable temporal isolation. A VBS is an extension of a constant-bandwidth server where throughput and latency of process execution can not only be controlled to remain constant across different competing workloads but also to vary in time as long as the resulting bandwidth stays below a given bandwidth cap. We have designed and implemented a VBS-based EDF-style constant-time scheduling algorithm, a constant-time admission test, and four alternative queue management plugins which influence the scheduling algorithm's overall temporal and spatial complexity. Experiments confirm the theoretical bounds in a number of microbenchmarks and demonstrate that the scheduler can effectively manage in constant time any number of processes up to available memory while maintaining response times of individual processes within a bounded range. We have also developed a small-footprint, bare-metal virtual machine that uses VBS for temporal isolation of multiple, concurrently running processes executing real code.