Schedulability Analysis of Real-Time Systems with Uncertain Worst-Case Execution Times

Schedulability analysis is about determining whether a given set of real-time software tasks are schedulable, i.e., whether task executions always complete before their specified deadlines. It is an important activity at both early design and late development stages of real-time systems. Schedulability analysis requires as input the estimated worst-case execution times (WCET) for software tasks. However, in practice, engineers often cannot provide precise point WCET estimates and prefer to provide plausible WCET ranges. Given a set of real-time tasks with such ranges, we provide an automated technique to determine for what WCET values the system is likely to meet its deadlines, and hence operate safely. Our approach combines a search algorithm for generating worst-case scheduling scenarios with polynomial logistic regression for inferring safe WCET ranges. We evaluated our approach by applying it to a satellite on-board system. Our approach efficiently and accurately estimates safe WCET ranges within which deadlines are likely to be satisfied with high confidence

k2U: A General Framework from k-Point Effective Schedulability Analysis to Utilization-Based Tests

To deal with a large variety of workloads in different application domains in real-time embedded systems, a number of expressive task models have been developed. For each individual task model, researchers tend to develop different types of techniques for deriving schedulability tests with different computation complexity and performance. In this paper, we present a general schedulability analysis framework, namely the k2U framework, that can be potentially applied to analyze a large set of real-time task models under any fixed-priority scheduling algorithm, on both uniprocessor and multiprocessor scheduling. The key to k2U is a k-point effective schedulability test, which can be viewed as a "blackbox" interface. For any task model, if a corresponding k-point effective schedulability test can be constructed, then a sufficient utilization-based test can be automatically derived. We show the generality of k2U by applying it to different task models, which results in new and improved tests compared to the state-of-the-art. Analogously, a similar concept by testing only k points with a different formulation has been studied by us in another framework, called k2Q, which provides quadratic bounds or utilization bounds based on a different formulation of schedulability test. With the quadratic and hyperbolic forms, k2Q and k2U frameworks can be used to provide many quantitive features to be measured, like the total utilization bounds, speed-up factors, etc., not only for uniprocessor scheduling but also for multiprocessor scheduling. These frameworks can be viewed as a "blackbox" interface for schedulability tests and response-time analysis

Reasoning About the Reliability of Multi-version, Diverse Real-Time Systems

This paper is concerned with the development of reliable real-time systems for use in high integrity applications. It advocates the use of diverse replicated channels, but does not require the dependencies between the channels to be evaluated. Rather it develops and extends the approach of Little wood and Rush by (for general systems) by investigating a two channel system in which one channel, A, is produced to a high level of reliability (i.e. has a very low failure rate), while the other, B, employs various forms of static analysis to sustain an argument that it is perfect (i.e. it will never miss a deadline). The first channel is fully functional, the second contains a more restricted computational model and contains only the critical computations. Potential dependencies between the channels (and their verification) are evaluated in terms of aleatory and epistemic uncertainty. At the aleatory level the events ''A fails" and ''B is imperfect" are independent. Moreover, unlike the general case, independence at the epistemic level is also proposed for common forms of implementation and analysis for real-time systems and their temporal requirements (deadlines). As a result, a systematic approach is advocated that can be applied in a real engineering context to produce highly reliable real-time systems, and to support numerical claims about the level of reliability achieved

WCET and Priority Assignment Analysis of Real-Time Systems using Search and Machine Learning

Real-time systems have become indispensable for human life as they are used in numerous industries, such as vehicles, medical devices, and satellite systems. These systems are very sensitive to violations of their time constraints (deadlines), which can have catastrophic consequences. To verify whether the systems meet their time constraints, engineers perform schedulability analysis from early stages and throughout development. However, there are challenges in obtaining precise results from schedulability analysis due to estimating the worst-case execution times (WCETs) and assigning optimal priorities to tasks. Estimating WCET is an important activity at early design stages of real-time systems. Based on such WCET estimates, engineers make design and implementation decisions to ensure that task executions always complete before their specified deadlines. However, in practice, engineers often cannot provide a precise point of WCET estimates and they prefer to provide plausible WCET ranges. Task priority assignment is an important decision, as it determines the order of task executions and it has a substantial impact on schedulability results. It thus requires finding optimal priority assignments so that tasks not only complete their execution but also maximize the safety margins from their deadlines. Optimal priority values increase the tolerance of real-time systems to unexpected overheads in task executions so that they can still meet their deadlines. However, it is a hard problem to find optimal priority assignments because their evaluation relies on uncertain WCET values and complex engineering constraints must be accounted for. This dissertation proposes three approaches to estimate WCET and assign optimal priorities at design stages. Combining a genetic algorithm and logistic regression, we first suggest an automatic approach to infer safe WCET ranges with a probabilistic guarantee based on the worst-case scheduling scenarios. We then introduce an extended approach to account for weakly hard real-time systems with an industrial schedule simulator. We evaluate our approaches by applying them to industrial systems from different domains and several synthetic systems. The results suggest that they are possible to estimate probabilistic safe WCET ranges efficiently and accurately so the deadline constraints are likely to be satisfied with a high degree of confidence. Moreover, we propose an automated technique that aims to identify the best possible priority assignments in real-time systems. The approach deals with multiple objectives regarding safety margins and engineering constraints using a coevolutionary algorithm. Evaluation with synthetic and industrial systems shows that the approach significantly outperforms both a baseline approach and solutions defined by practitioners. All the solutions in this dissertation scale to complex industrial systems for offline analysis within an acceptable time, i.e., at most 27 hours

Ordonnancement des systèmes avec différents niveaux de criticité

Real-time safety-critical systems must complete their tasks within a given time limit. Failure to successfully perform their operations, or missing a deadline, can have severe consequences such as destruction of property and/or loss of life. Examples of such systems include automotive systems, drones and avionics among others. Safety guarantees must be provided before these systems can be deemed usable. This is usually done through certification performed by a certification authority.Safety evaluation and certification are complicated and costly even for smaller systems.One answer to these difficulties is the isolation of the critical functionality. Executing tasks of different criticalities on separate platforms prevents non-critical tasks from interfering with critical ones, provides a higher guaranty of safety and simplifies the certification process limiting it to only the critical functions. But this separation, in turn, introduces undesirable results portrayed by an inefficient resource utilization, an increase in the cost, weight, size and energy consumption which can put a system in a competitive disadvantage.To overcome the drawbacks of isolation, Mixed Criticality (MC) systems can be used. These systems allow functionalities with different criticalities to execute on the same platform. In 2007, Vestal proposed a model to represent MC-systems where tasks have multiple Worst Case Execution Times (WCETs), one for each criticality level. In addition, correctness conditions for scheduling policies were formally defined, allowing lower criticality jobs to miss deadlines or be even dropped in cases of failure or emergency situations.The introduction of multiple WCETs and different conditions for correctness increased the difficulty of the scheduling problem for MC-systems. Conventional scheduling policies and schedulability tests proved inadequate and the need for new algorithms arose. Since then, a lot of work has been done in this field.In this thesis, we contribute to the study of schedulability in MC-systems. The workload of a system is represented as a set of jobs that can describe the execution over the hyper-period of tasks or over a duration in time. This model allows us to study the viability of simulation-based correctness tests in MC-systems. We show that simulation tests can still be used in mixed-criticality systems, but in this case, the schedulability of the worst case scenario is no longer sufficient to guarantee the schedulability of the system even for the fixed priority scheduling case. We show that scheduling policies are not predictable in general, and define the concept of weak-predictability for MC-systems. We prove that a specific class of fixed priority policies are weakly predictable and propose two simulation-based correctness tests that work for weakly-predictable policies.We also demonstrate that contrary to what was believed, testing for correctness can not be done only through a linear number of preemptions.The majority of the related work focuses on systems of two criticality levels due to the difficulty of the problem. But for automotive and airborne systems, industrial standards define four or five criticality levels, which motivated us to propose a scheduling algorithm that schedules mixed-criticality systems with theoretically any number of criticality levels. We show experimentally that it has higher success rates compared to the state of the art.We illustrate how our scheduling algorithm, or any algorithm that generates a single time-triggered table for each criticality mode, can be used as a recovery strategy to ensure the safety of the system in case of certain failures.Finally, we propose a high level concurrency language and a model for designing an MC-system with coarse grained multi-core interference.Les systèmes temps-réel critiques doivent exécuter leurs tâches dans les délais impartis. En cas de défaillance, des événements peuvent avoir des catastrophes économiques. Des classifications des défaillances par rapport aux niveaux des risques encourus ont été établies, en particulier dans les domaines des transports aéronautique et automobile. Des niveaux de criticité sont attribués aux différentes fonctions des systèmes suivant les risques encourus lors d'une défaillance et des probabilités d'apparition de celles-ci. Ces différents niveaux de criticité influencent les choix d'architecture logicielle et matérielle ainsi que le type de composants utilisés pour sa réalisation. Les systèmes temps-réels modernes ont tendance à intégrer sur une même plateforme de calcul plusieurs applications avec différents niveaux de criticité. Cette intégration est nécessaire pour des systèmes modernes comme par exemple les drones (UAV) afin de réduire le coût, le poids et la consommation d'énergie. Malheureusement, elle conduit à des difficultés importantes lors de leurs conceptions. En plus, ces systèmes doivent être certifiés en prenant en compte ces différents niveaux de criticités.Il est bien connu que le problème d'ordonnancement des systèmes avec différents niveaux de criticités représente un des plus grand défi dans le domaine de systèmes temps-réel. Les techniques traditionnelles proposent comme solution l’isolation complète entre les niveaux de criticité ou bien une certification globale au plus haut niveau. Malheureusement, une telle solution conduit à une mauvaise des ressources et à la perte de l’avantage de cette intégration. En 2007, Vestal a proposé un modèle pour représenter les systèmes avec différents niveaux de criticité dont les tâches ont plusieurs temps d’exécution, un pour chaque niveau de criticité. En outre, les conditions de validité des stratégies d’ordonnancement ont été définies de manière formelle, permettant ainsi aux tâches les moins critiques d’échapper aux délais, voire d’être abandonnées en cas de défaillance ou de situation d’urgence.Les politiques de planification conventionnelles et les tests d’ordonnoncement se sont révélés inadéquats.Dans cette thèse, nous contribuons à l’étude de l’ordonnancement dans les systèmes avec différents niveaux de criticité. La surcharge d'un système est représentée sous la forme d'un ensemble de tâches pouvant décrire l'exécution sur l'hyper-période de tâches ou sur une durée donnée. Ce modèle nous permet d’étudier la viabilité des tests de correction basés sur la simulation pour les systèmes avec différents niveaux de criticité. Nous montrons que les tests de simulation peuvent toujours être utilisés pour ces systèmes, et la possibilité de l’ordonnancement du pire des scénarios ne suffit plus, même pour le cas de l’ordonnancement avec priorité fixe. Nous montrons que les politiques d'ordonnancement ne sont généralement pas prévisibles. Nous définissons le concept de faible prévisibilité pour les systèmes avec différents niveaux de criticité et nous montrons ensuite qu'une classe spécifique de stratégies à priorité fixe sont faiblement prévisibles. Nous proposons deux tests de correction basés sur la simulation qui fonctionnent pour des stratégies faiblement prévisibles.Nous montrons également que, contrairement à ce que l’on croyait, le contrôle de l’exactitude ne peut se faire que par l’intermédiaire d’un nombre linéaire de préemptions.La majorité des travaux reliés à notre domaine portent sur des systèmes à deux niveaux de criticité en raison de la difficulté du problème. Mais pour les systèmes automobiles et aériens, les normes industrielles définissent quatre ou cinq niveaux de criticité, ce qui nous a motivés à proposer un algorithme de planification qui planifie les systèmes à criticité mixte avec théoriquement un nombre quelconque de niveaux de criticité. Nous montrons expérimentalement que le taux de réussite est supérieur à celui de l’état de la technique

On static execution-time analysis

Proving timeliness is an integral part of the verification of safety-critical real-time systems. To this end, timing analysis computes upper bounds on the execution times of programs that execute on a given hardware platform. Modern hardware platforms commonly exhibit counter-intuitive timing behaviour: a locally slower execution can lead to a faster overall execution. Such behaviour challenges efficient timing analysis. In this work, we present and discuss a hardware design, the strictly in-order pipeline, that behaves monotonically w.r.t. the progress of a program's execution. Based on monotonicity, we prove the absence of the aforementioned counter-intuitive behaviour. At least since multi-core processors have emerged, timing analysis separates concerns by analysing different aspects of the system's timing behaviour individually. In this work, we validate the underlying assumption that a timing bound can be soundly composed from individual contributions. We show that even simple processors exhibit counter-intuitive behaviour - a locally slow execution can lead to an even slower overall execution - that impedes the soundness of the composition. We present the compositional base bound analysis that accounts for any such amplifying effects within its timing contribution. This enables a sound compositional analysis even for complex processors. Furthermore, we discuss hardware modifications that enable efficient compositional analyses.Echtzeitsysteme müssen unter allen Umständen beweisbar pünktlich arbeiten. Zum Beweis errechnet die Zeitanalyse obere Schranken der für die Ausführung von Programmen auf einer Hardware-Plattform benötigten Zeit. Moderne Hardware-Plattformen sind bekannt für unerwartetes Zeitverhalten bei dem eine lokale Verzögerung in einer global schnelleren Ausführung resultiert. Solches Zeitverhalten erschwert eine effiziente Analyse. Im Rahmen dieser Arbeit diskutieren wir das Design eines Prozessors mit eingeschränkter Fließbandverarbeitung (strictly in-order pipeline), der sich bzgl. des Fortschritts einer Programmausführung monoton verhält. Wir beweisen, dass Monotonie das oben genannte unerwartete Zeitverhalten verhindert. Spätestens seit dem Einsatz von Mehrkernprozessoren besteht die Zeitanalyse aus einzelnen Teilanalysen welche nur bestimmte Aspekte des Zeitverhaltens betrachten. Eine zentrale Annahme ist hierbei, dass sich die Teilergebnisse zu einer korrekten Zeitschranke zusammensetzen lassen. Im Rahmen dieser Arbeit zeigen wir, dass diese Annahme selbst für einfache Prozessoren ungültig ist, da eine lokale Verzögerung zu einer noch größeren globalen Verzögerung führen kann. Für bestehende Prozessoren entwickeln wir eine neuartige Teilanalyse, die solche verstärkenden Effekte berücksichtigt und somit eine korrekte Komposition von Teilergebnissen erlaubt. Für zukünftige Prozessoren beschreiben wir Modifikationen, die eine deutlich effizientere Zeitanalyse ermöglichen

A Practical Comparison of Scheduling Algorithms for Mixed Criticality Embedded Systems

With the consolidation of automotive control processes onto single highperformance ECUs the issue of running, and thus scheduling, processes of varying criticality on a single CPU has moved to the fore. This has resulted in a number of new algorithms for scheduling such systems, for example Adaptive Mixed Criticality (AMC). This project attempts to measure the performance of some of these algorithms on a singlecore embedded system CPU and compares them in order to shed some light on their different advantages and disadvantages