Response Time Analysis for Thermal-Aware Real-Time Systems Under Fixed-Priority Scheduling

International audienceThis paper investigates schedulability analysis for thermal-aware real-time systems. Thermal constraints are becoming more and more critical in new generation miniaturized embedded systems, e.g. Medicals implants. As part of this work, we adapt the PFPasap algorithm proposed in [1] for energy-harvesting systems to thermal-aware ones. We prove its optimality for non-concrete1 fixed-priority task sets and propose a response-time analysis based on worst-case response-time upper bounds. We evaluate the efficacy of the proposed bounds via extensive simulation over randomly-generated task systems

Green Scheduling of Control Systems

Electricity usage under peak load conditions can cause issues such as reduced power quality and power outages. For this reason, commercial electricity customers are often subject to demand-based pricing, which charges very high prices for peak electricity demand. Consequently, reducing peaks in electricity demand is desirable for both economic and reliability reasons. In this thesis, we investigate the peak demand reduction problem from the perspective of safe scheduling of control systems under resource constraint. To this end, we propose Green Scheduling as an approach to schedule multiple interacting control systems within a constrained peak demand envelope while ensuring that safety and operational conditions are facilitated. The peak demand envelope is formulated as a constraint on the number of binary control inputs that can be activated simultaneously. Using two different approaches, we establish a range of sufficient and necessary schedulability conditions for various classes of affine dynamical systems. The schedulability analysis methods are shown to be scalable for large-scale systems consisting of up to 1000 subsystems. We then develop several scheduling algorithms for the Green Scheduling problem. First, we develop a periodic scheduling synthesis method, which is simple and scalable in computation but does not take into account the influence of disturbances. We then improve the method to be robust to small disturbances while preserving the simplicity and scalability of periodic scheduling. However the improved algorithm usually result in fast switching of the control inputs. Therefore, event-triggered and self-triggered techniques are used to alleviate this issue. Next, using a feedback control approach based on attracting sets and robust control Lyapunov functions, we develop event-triggered and self-triggered scheduling algorithms that can handle large disturbances affecting the system. These algorithms can also exploit prediction of the disturbances to improve their performance. Finally, a scheduling method for discrete-time systems is developed based on backward reachability analysis. The effectiveness of the proposed approach is demonstrated by an application to scheduling of radiant heating and cooling systems in buildings. Green Scheduling is able to significantly reduce the peak electricity demand and the total electricity consumption of the radiant systems, while maintaining thermal comfort for occupants

Schedulability of Rate Monotonic Algorithm using Improved Time Demand Analysis for Multiprocessor Environment

Real-Time Monotonic algorithm (RMA) is a widely used static priority scheduling algorithm. For application of RMA at various systems, it is essential to determine the system’s feasibility first. The various existing algorithms perform the analysis by reducing the scheduling points in a given task set. In this paper we propose a schedubility test algorithm, which reduces the number of tasks to be analyzed instead of reducing the scheduling points of a given task. This significantly reduces the number of iterations taken to compute feasibility. This algorithm can be used along with the existing algorithms to effectively reduce the high complexities encountered in processing large task sets. We also extend our algorithm to multiprocessor environment and compare number of iterations with different number of processors. This paper then compares the proposed algorithm with existing algorithm. The expected results show that the proposed algorithm performs better than the existing algorithms

Study, analysis and new scheduling proposals in partitioned real-time systems

[ES] En nuestra vida cotidiana, cada vez más ordenadores controlan nuestro entorno: teléfonos móviles, procesos industriales, asistencia a la conducción, etc. Todos estos sistemas presentan requisitos estrictos para garantizar un comportamiento adecuado. En muchos de estos sistemas, cumplir con las restricciones de tiempo es un factor tan importante como el resultado lógico de los cálculos. Desde hace aproximadamente 40 años, los sistemas en tiempo real son muy atractivos en el campo de la computación y hoy en día se aplican en áreas de gran alcance como aplicaciones industriales, aplicaciones aeroespaciales, telecomunicaciones, electrónica de consumo, etc. Algunos retos a abordar en el campo del tiempo real son el determinismo y la predecibilidad del comportamiento temporal del sistema. En este sentido, garantizar la ejecución del programa y los tiempos de respuesta del sistema son requisitos esenciales que deben cumplirse estrictamente a través de estrategias apropiadas de planificación de tareas. Además, las arquitecturas multiprocesador se están volviendo más populares debido al hecho de que las capacidades de procesamiento y los recursos computacionales de los sistemas están aumentando. Un estudio reciente estima que existe una tendencia creciente entre las arquitecturas multiprocesador a combinar diferentes niveles de criticidad en el mismo sistema. En este sentido, proporcionar aislamiento entre las aplicaciones es extremadamente necesario. La tecnología particionada es capaz de lidiar con este propósito. Además, la gestión de la energía es un problema relevante en los sistemas en tiempo real. Muchos sistemas empotrados de tiempo real, como dispositivos portátiles o robots móviles que requieren baterías, buscan encontrar técnicas que reduzcan el consumo de energía y, como consecuencia, aumenten la vida útil de sus baterías. También se obtienen claros beneficios operativos, financieros, monetarios y ambientales al minimizar el consumo de energía. Con todo ello, este trabajo aborda el problema de planificabilidad y contribuye al estudio de las nuevas técnicas de planificación en sistemas particionados de tiempo real. Estas técnicas proporcionan el tiempo mínimo para planificar de manera factible conjuntos de tareas. Además, se proponen técnicas de asignación para sistemas multiprocesador cuyo objetivo principal es reducir el consumo de energía del sistema global. Finalmente, se presentan los resultados obtenidos así como los trabajos futuros relacionados con este trabajo[CA] En la nostra vida quotidiana, cada vegada més ordenadors controlen el nostre entorn: telèfons mòbils, processos industrials, assistència a la conducció, etc. Tots aquests sistemes presenten requisits estrictes per a garantir un comportament adequat. En molts d' aquests sistemes, complir amb les restriccions de temps és un factor tan important com el resultat lògic dels càlculs. Des de fa aproximadament 40 anys, els sistemes en temps real són molt atractius en el camp de la computació i hui dia s' apliquen en àrees de gran abast com a aplicacions industrials, aplicacions aeroespacials, telecomunicacions, electrònica de consum, etc. Alguns reptes a abordar en el camp del temps real són el determinisme i la predictibilitat del comportament temporal del sistema. En aquest sentit, garantir l'execució del programa i els temps de resposta del sistema són requisits essencials que han de complir-se estrictament a través d'estratègies apropiades de planificació de tasques. A més, les arquitectures multiprocessador s'estan tornant més populars a causa del fet que les capacitats de processament i els recursos computacionals dels sistemes estan augmentant. Un estudi recent estima que existeix una tendència creixent entre les arquitectures multiprocessador a combinar diferents nivells de criticitat en el mateix sistema. En aquest sentit, proporcionar aïllament entre les aplicacions és extremadament necessari. La tecnologia particionada és capaç de bregar amb aquest propòsit. A més, la gestió de l'energia és un problema rellevant en els sistemes en temps real. Molts sistemes embebits de temps real, com a dispositius portàtils o robots mòbils que requereixen bateries, busquen trobar tècniques que reduïsquen el consum d'energia i, com a conseqüència, augmenten la vida útil de les seues bateries. També s'obtenen clars beneficis operatius, financers, monetaris i ambientals en minimitzar el consum d'energia. Amb tot això, aquest treball aborda el problema de planificabilitat i contribueix a l'estudi de les noves tècniques de planificació en sistemes particionats de temps real. Aquestes tècniques proporcionen el temps mínim per a planificar de manera factible conjunts de tasques. A més, es proposen tècniques d'assignació per a sistemes multiprocessador l'objectiu principal del qual és reduir el consum d'energia del sistema global. Finalment, es presenten els resultats obtinguts així com els treballs futurs relacionats amb aquest treball.[EN] In our everyday lives, more and more computers are controlling our environment: mobile phones, industrial processes, driving assistance, etc. All these systems present strict requirements to ensure proper behaviour. In many of these systems, the time at which the action is delivered is as important as the logical result of the computation. About 40 years ago, real-time systems began to attract attention in computing field and nowadays are applied in wide ranging areas as industrial applications, aerospace, telecommunication applications, consumer electronics, etc. Some real-time challenges that must be addressed are determinism and predictability of the temporal behaviour of the system. In this sense, to guarantee program execution and system response times are essential requirements that must be strictly met through appropriate task scheduling strategies. Furthermore, multiprocessor architectures are becoming more popular due to the fact that processing capabilities and computational resources are increasing. A recent study estimates that there is an increasing tendency among multiprocessor architectures to combine different levels of criticality in the same system. In this sense, to provide isolation between applications is extremely required. Partitioned technology is able to deal with this purpose. In addition, energy management is a relevant problem in real-time systems. Many real-time embedded systems, as wearable devices or mobile robots that require batteries, seek to find techniques that reduce the energy consumption and, as a consequence, increase the lifetime of their batteries. Also clear operational, financial, monetary and environmental gains are reached when minimizing energy consumption. Faced with all this, this work addresses the problem of schedulability and contributes to the study of new scheduling techniques in partitioned real-time systems. These techniques provide the minimum time to feasible schedule tasks sets. Moreover, allocation techniques for multicore systems whose main objective is to reduce the energy consumption of the overall system are also proposed. Finally, some of the obtained results are discussed as conclusions and future works are introduced.Guasque Ortega, A. (2019). Study, analysis and new scheduling proposals in partitioned real-time systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/135279TESI

Using Imprecise Computing for Improved Real-Time Scheduling

Conventional hard real-time scheduling is often overly pessimistic due to the worst case execution time estimation. The pessimism can be mitigated by exploiting imprecise computing in applications where occasional small errors are acceptable. This leverage is investigated in a few previous works, which are restricted to preemptive cases. We study how to make use of imprecise computing in uniprocessor non-preemptive real-time scheduling, which is known to be more difficult than its preemptive counterpart. Several heuristic algorithms are developed for periodic tasks with independent or cumulative errors due to imprecision. Simulation results show that the proposed techniques can significantly improve task schedulability and achieve desired accuracy– schedulability tradeoff. The benefit of considering imprecise computing is further confirmed by a prototyping implementation in Linux system. Mixed-criticality system is a popular model for reducing pessimism in real-time scheduling while providing guarantee for critical tasks in presence of unexpected overrun. However, it is controversial due to some drawbacks. First, all low-criticality tasks are dropped in high-criticality mode, although they are still needed. Second, a single high-criticality job overrun leads to the pessimistic high-criticality mode for all high-criticality tasks and consequently resource utilization becomes inefficient. We attempt to tackle aforementioned two limitations of mixed-criticality system simultaneously in multiprocessor scheduling, while those two issues are mostly focused on uniprocessor scheduling in several recent works. We study how to achieve graceful degradation of low-criticality tasks by continuing their executions with imprecise computing or even precise computing if there is sufficient utilization slack. Schedulability conditions under this Variable-Precision Mixed-Criticality (VPMC) system model are investigated for partitioned scheduling and global fpEDF-VD scheduling. And a deferred switching protocol is introduced so that the chance of switching to high-criticality mode is significantly reduced. Moreover, we develop a precision optimization approach that maximizes precise computing of low-criticality tasks through 0-1 knapsack formulation. Experiments are performed through both software simulations and Linux proto- typing with consideration of overhead. Schedulability of the proposed methods is studied so that the Quality-of-Service for low-criticality tasks is improved with guarantee of satisfying all deadline constraints. The proposed precision optimization can largely reduce computing errors compared to constantly executing low-criticality tasks with imprecise computing in high-criticality mode

Budgeting Under-Specified Tasks for Weakly-Hard Real-Time Systems

In this paper, we present an extension of slack analysis for budgeting in the design of weakly-hard real-time systems. During design, it often happens that some parts of a task set are fully specified while other parameters, e.g. regarding recovery or monitoring tasks, will be available only much later. In such cases, slack analysis can help anticipate how these missing parameters can influence the behavior of the whole system so that a resource budget can be allocated to them. It is, however, sufficient in many application contexts to budget these tasks in order to preserve weakly-hard rather than hard guarantees. We thus present an extension of slack analysis for deriving task budgets for systems with hard and weakly-hard requirements. This work is motivated by and validated on a realistic case study inspired by industrial practice

Control techniques for thermal-aware energy-efficient real time multiprocessor scheduling

La utilización de microprocesadores multinúcleo no sólo es atractiva para la industria sino que en muchos ámbitos es la única opción. La planificación tiempo real sobre estas plataformas es mucho más compleja que sobre monoprocesadores y en general empeoran el problema de sobre-diseño, llevando a la utilización de muchos más procesadores /núcleos de los necesarios. Se han propuesto algoritmos basados en planificación fluida que optimizan la utilización de los procesadores, pero hasta el momento presentan en general inconvenientes que los alejan de su aplicación práctica, no siendo el menor el elevado número de cambios de contexto y migraciones.Esta tesis parte de la hipótesis de que es posible diseñar algoritmos basados en planificación fluida, que optimizan la utilización de los procesadores, cumpliendo restricciones temporales, térmicas y energéticas, con un bajo número de cambios de contexto y migraciones, y compatibles tanto con la generación fuera de línea de ejecutivos cíclicos atractivos para la industria, como de planificadores que integran técnicas de control en tiempo de ejecución que permiten la gestión eficiente tanto de tareas aperiódicas como de desviaciones paramétricas o pequeñas perturbaciones.A este respecto, esta tesis contribuye con varias soluciones. En primer lugar, mejora una metodología de modelo que representa todas las dimensiones del problema bajo un único formalismo (Redes de Petri Continuas Temporizadas). En segundo lugar, propone un método de generación de un ejecutivo cíclico, calculado en ciclos de procesador, para un conjunto de tareas tiempo real duro sobre multiprocesadores que optimiza la utilización de los núcleos de procesamiento respetando también restricciones térmicas y de energía, sobre la base de una planificación fluida. Considerar la sobrecarga derivada del número de cambios de contexto y migraciones en un ejecutivo cíclico plantea un dilema de causalidad: el número de cambios de contexto (y en consecuencia su sobrecarga) no se conoce hasta generar el ejecutivo cíclico, pero dicho número no se puede minimizar hasta que se ha calculado. La tesis propone una solución a este dilema mediante un método iterativo de convergencia demostrada que logra minimizar la sobrecarga mencionada.En definitiva, la tesis consigue explotar la idea de planificación fluida para maximizar la utilización (donde maximizar la utilización es un gran problema en la industria) generando un sencillo ejecutivo cíclico de mínima sobrecarga (ya que la sobrecarga implica un gran problema de los planificadores basados en planificación fluida).Finalmente, se propone un método para utilizar las referencias de la planificación fuera de línea establecida en el ejecutivo cíclico para su seguimiento por parte de un controlador de frecuencia en línea, de modo que se pueden afrontar pequeñas perturbaciones y variaciones paramétricas, integrando la gestión de tareas aperiódicas (tiempo real blando) mientras se asegura la integridad de la ejecución del conjunto de tiempo real duro.Estas aportaciones constituyen una novedad en el campo, refrendada por las publicaciones derivadas de este trabajo de tesis.<br /

A Control-Theoretic Design And Analysis Framework For Resilient Hard Real-Time Systems

We introduce a new design metric called system-resiliency which characterizes the maximum unpredictable external stresses that any hard-real-time performance mode can withstand. Our proposed systemresiliency framework addresses resiliency determination for real-time systems with physical and hardware limitations. Furthermore, our framework advises the system designer about the feasible trade-offs between external system resources for the system operating modes on a real-time system that operates in a multi-parametric resiliency environment. Modern multi-modal real-time systems degrade the system’s operational modes as a response to unpredictable external stimuli. During these mode transitions, real-time systems should demonstrate a reliable and graceful degradation of service. Many control-theoretic-based system design approaches exist. Although they permit real-time systems to operate under various physical constraints, none of them allows the system designer to predict the system-resiliency over multi-constrained operating environment. Our framework fills this gap; the proposed framework consists of two components: the design-phase and runtime control. With the design-phase analysis, the designer predicts the behavior of the real-time system for variable external conditions. Also, the runtime controller navigates the system to the best desired target using advanced control-theoretic techniques. Further, our framework addresses the system resiliency of both uniprocessor and multicore processor systems. As a proof of concept, we first introduce a design metric called thermal-resiliency, which characterizes the maximum external thermal stress that any hard-real-time performance mode can withstand. We verify the thermal-resiliency for the external thermal stresses on a uniprocessor system through a physical testbed. We show how to solve some of the issues and challenges of designing predictable real-time systems that guarantee hard deadlines even under transitions between modes in an unpredictable thermal environment where environmental temperature may dynamically change using our new metric. We extend the derivation of thermal-resiliency to multicore systems and determine the limitations of external thermal stress that any hard-real-time performance mode can withstand. Our control-theoretic framework allows the system designer to allocate asymmetric processing resources upon a multicore proiii cessor and still maintain thermal constraints. In addition, we develop real-time-scheduling sub-components that are necessary to fully implement our framework; toward this goal, we investigate the potential utility of parallelization for meeting real-time constraints and minimizing energy. Under malleable gang scheduling of implicit-deadline sporadic tasks upon multiprocessors, we show the non-necessity of dynamic voltage/frequency regarding optimality of our scheduling problem. We adapt the canonical schedule for DVFS multiprocessor platforms and propose a polynomial-time optimal processor/frequency-selection algorithm. Finally, we verify the correctness of our framework through multiple measurable physical and hardware constraints and complete our work on developing a generalized framework

Real-time scheduling for energy harvesting sensor nodes

Energy harvesting has recently emerged as a feasible option to increase the operating time of sensor networks. If each node of the network, however, is powered by a fluctuating energy source, common power management solutions have to be reconceived. This holds in particular if real-time responsiveness of a given application has to be guaranteed. Task scheduling at the single nodes should account for the properties of the energy source, capacity of the energy storage as well as deadlines of the single tasks. We show that conventional scheduling algorithms (like e.g. EDF) are not suitable for this scenario. Based on this motivation, we have constructed optimal scheduling algorithms that jointly handle constraints from both energy and time domain. Further we present an admittance test that decides for arbitrary task sets, whether they can be scheduled without deadline violations. To this end, we introduce the concept of energy variability characterization curves (EVCC) which nicely captures the dynamics of various energy sources. Simulation results show that our algorithms allow significant reductions of the battery size compared to Earliest Deadline First schedulin