Task Scheduling in Energy Harvesting Real-time Embedded Systems

International audienceHarvesting energy from the environment is very desirable for many emerging applications that use embedded devices. Energy harvesting also known as energy scavenging enables us to guarantee quasi-perpetual system operation for wireless sensors, medical implants, etc. without requiring human intervention which is normally necessary for recharging batteries in classical battery-operated systems. Nevertheless, energy harvesting calls for solving numerous technological problems in relation with chemistry when batteries are used for temporary energy storage for example, power management of the embedded computing system that consumes the energy, etc. And this latter problem becomes more complex when the embedded system has real-time constraints i.e. deadlines attached to computations. This paper surveys the main issues involved in designing energy harvesting embedded systems that present strict timing requirements

Temps-Réel Libre et Conduite d'un Robot Mobile Opto-guidé

International audienceLe travail présenté ici a été réalisé dans le cadre d'un projet1 national de R&D dans le domaine des technologies logicielles dédiées aux applications temps-réel, initialisé en 2002. Ce projet avait pour finalité la conception d'un système d'exploitation temps réel baptisé « système Cléopatre » à code source ouvert et gratuit. Ce système d'exploitation temps réel a la particularité de se présenter sous forme d'un assemblage de composants sélectionnables par l'utilisateur selon ses besoins. Nous présentons le démonstrateur de ce projet, un AGV (Automated Guided Vehicle) conduit en temps-réel par l'O.S. Cléopatre. L'objectif était d'évaluer ses performances d'un point de vue temporel, le gain engendré par l'approche composant en termes d'empreinte mémoire et d'accessibilité mais aussi vérifier l'inter-opérabilité des composants logiciels développés. L'application mise en œuvre consiste à conduire cet AGV opto-guidé muni de son informatique embarquée, en exécutant en temps-réel des ordres de mission émis par une liaison sans fil à partir d'une station de supervision

Real-time Scheduling of periodic tasks in a monoprocessor system with a rechargeable battery

International audienceWe are interested in a real-time computing system that is powered through a rechargeable battery. In this context, two constraints need to be addressed: energy and deadlines. Classical task scheduling, in particular Earliest Deadline First, only accounts for timing parameters of the tasks and conse- quently is not suitable when considering energy constraints. We show here how to modify Earliest Deadline so as to account for the properties of the energy source, capacity of the energy storage as well as energy consumption of the tasks. We present an exact feasibility test that decides for periodic task sets, whether they can be scheduled without deadline violations. To this end, we introduce the concepts of energy demand and slack energy

Performance Evaluation of Real-Time Scheduling Heuristics for Energy Harvesting Systems

International audienceEnergy constrained systems can increase their usable lifetimes by extracting energy from their environment. This is known as energy harvesting. This paper investigates scheduling issues in uni-processor real time embedded systems using regenerative energy. Task scheduling should account for the properties of the regenerative energy source which fluctuates, capacity of the energy storage as well as deadlines of the time critical tasks that characterize most of real time embedded systems. In this context, designing efficient scheduling strategies is significantly more complex compared to conventional real-time scheduling. In this paper we compare several scheduling heuristics with the optimal algorithm known as LSA (Lazy Scheduling Algorithm). We report results of an experiment study in terms of percentage of deadlines satisfied

Schedulers for BGW Tasks to Guarantee Quality of Service of Embedded Real-Time Systems

International audienceWe present a new task model called BGW for preemptable, periodic task sets, scheduled on a uniprocessor embedded platform. The tasks may be subject to faults and the processor may be overloaded. According to BGW, any Black job has to execute a primary algorithm before deadline, any Grey job may execute either the primary or the backup algorithm and any White job may be discarded. We describe several Earliest Deadline First (EDF) based scheduling frameworks suitable for this model. We also present and discuss the results of experiments that compare the EDF scheduler applied to conventional Liu and Layland task sets to various schedulers applied to BGW task sets. The Quality of Service is observed through metrics including ratio of deadline success, preemption rate, etc

An efficient aperiodic task server for energy harvesting embedded systems

International audienceThe energy existing in our environment can be converted into electricity to supply a wireless device such as sensor node. In this paper, we will address a problem of scheduling for a device that executes a mixed set of real-time tasks, composed of aperiodic and hard deadline periodic tasks. High responsiveness of the aperiodic tasks and timeliness of the periodic tasks can be performed through an aperiodic task server that takes into account both time and energy limitations. This paper describes an extension of the well known TBS (Total Bandwidth Server) which is energy harvesting aware. The performance of the new aperiodic server, called TB-H, is evaluated and compared to background approaches through simulation experiments

Conduite d'un Robot Mobile Opto-guidé Par Logiciels Temps-Réel Open-Source Démonstrateur du projet RNTL Cléopatre

National audienceLe travail présenté ici a été réalisé dans le cadre du projet Cléopatre1, projet national de R&D dans le domaine des technologies logicielles dédiées aux applications temps-réel, terminé en juin 2005. Ce projet avait pour finalité la conception d'un système d'exploitation temps réel baptisé « système Cléopatre » à code source ouvert, gratuit et téléchargeable à partir d'un site public de façon à en faciliter la diffusion. Ce système d'exploitation temps réel a la particularité de se présenter sous forme d'un assemblage de composants sélectionnables par l'utilisateur. Ces derniers peuvent être définis comme des briques logicielles disponibles sur les étagères d'une bibliothèque et implémentant des mécanismes novateurs principalement issus de la recherche en ordonnancement temps réel. Nous présentons le démonstrateur de ce projet, un AGV (Automated Guided Vehicle) conduit en temps-réel par l'O.S. Cléopatre. L'objectif était d'évaluer ses performances d'un point de vue temporel, le gain engendré par l'approche composant en termes d'empreinte mémoire et d'accessibilité mais aussi vérifier l'inter-opérabilité des composants logiciels développés. L'application mise en œuvre consiste à conduire cet AGV opto-guidé muni de son informatique embarquée, en exécutant en temps-réel des ordres de mission émis par une liaison sans fil à partir d'une station de supervision

A Nonclairvoyant Real-Time Scheduler for Ambient Energy Harvesting Sensors

International audienceAmbient energy harvesting also known as energy scavenging is the process where energy is obtained from the environment, converted, and stored to power small devices such as wireless sensors. We present a variant of EDF scheduling algorithm called EH-EDF (Energy Harvesting-Earliest Deadline First). Decisions are taken at run-time without having prior knowledge about the future energy production and task characteristics. We gauge the performance of EH-EDF by means of simulations in order to show its benefits .W eevaluat ean dcompar esevera lvariant so fEH-ED Fi nterm so fpercentag eo ffeasibl etas ksets .Metric ssuc ha saverage length of the idle times are also considered. Simulations tend to demonstrate that no online scheduler can reach optimality in a real-time energy harvesting environment

Partitioned EDF Scheduling in Multicore systems with Quality of Service constraints

International audienceIn this paper we study the partitioned EDF scheduling in a homogeneous multiprocessor environment with Quality of Service (QoS) constraints. The system considered here is a real-time multiprocessor system assumed to be powered by rechargeable batteries. We address the issue of how to best partition a set of firm real-time tasks that can occasionally skip one instance according to a predefined QoS threshold. The main goal is to minimize the energy consumption of the system while offering solutions with respect to transient energy starvation situations the system can experiment. The contribution of the paper is twofold. First, we present a schedulability analysis of firm multiprocessor task sets under QoS constraints. Second we propose new partitionning heuristics integrating skips. The evaluation is conducted from several points of view (minimization of the total processor number, maximization of the spare capacity on each processor)

Ensuring the sustainability of real-time embedded system under both QoS and Energy Constraints

Nowadays, wireless sensor networks (WSNs) are more and more used in applications such as environment monitoring, healthcare monitoring, etc...The challenge in sensor networks is to ensure the sustainability of the system by guaranteeing the required performance level. However, with the limited capacity of finite power sources and the need of guaranteeing a long lifetime of those systems, it is suitable to use energy harvesting which allows to supply low-power electronic systems by converting ambient energy into electric power. Hence, our study is concerned with the problem of soft periodic and aperiodic tasks scheduling in sensor nodes powered by energy harvesters. In this paper, we address this issue by proposing three energy-aware schedulers, namely BG-Green-RTO, BG-Green-BWP and Green-AWP which aim to improve the responsiveness of aperiodic tasks while still guaranteeing the execution of periodic tasks considering their timing and energy constraints. Such algorithms allow to gracefully cope with processing overload and energy starvation. Moreover, a simulation study permits to show their performance