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

Contributions à l’Ordonnancement en Temps Réel pour les Systèmes Autonomes en Energie.

Nowadays, renewable energy harvesting such as that envisaged for manywireless things, allows the quasi-perpetual systems operation withouthuman intervention because it works without periodic recharging ofbattery. From an energy point of view, the design of this type of autonomoussystem becomes more complex since this process has in addition a behaviorconstrained by time, and particularly has to meet latest timingdeadlines. As with any real-time system, an unavoidable problem is to find a dynamicscheduling mechanism able of considering jointly two key constraints:time and energy.In this thesis, we focus on scheduling of mixed tasks consisting ofperiodic tasks and soft aperiodic tasks without deadline, by providingappropriate solutions for the following question: how to serve aperiodictasks in order to minimize their response time without challenging thefeasibility of periodic tasks. We consider a single-frequency uniprocessorsystem, powered by an energy reservoir which is charged through an ambientenergy source.In this context, four new aperiodic task servers were proposed, based onthe optimal scheduler ED-H. A theoretical analysis was performed withvalidation by a simulation study.Aujourd’hui, la récupération d’énergie renouvelable (energy harvesting)comme celle envisagée pour de nombreux objets sans fil, rend possible unfonctionnement quasi-perpétuel de ces systèmes, sans interventionhumaine, car sans recharge périodique de batterie ou de pile. Concevoirce type de système autonome d’un point de vue énergétique devient trèscomplexe lorsque celui-ci a en plus un comportement contraint par letemps et en particulier doit respecter des échéances de fin d’exécutionau plus tard. Comme pour tout système temps réel, une problématique incontournable estde trouver un mécanisme d’ordonnancement dynamique capable de prendre encompte conjointement deux contraintes clés : le temps et l’énergie.Dans cette thèse, nous nous intéressons à l’ordonnancement de tâchesmixtes constituées de tâches périodiques et de tâches apériodiques souplessans échéance, tout en répondant à une question clé: comment servir lestâches apériodiques pour minimiser leur temps de réponse sans remettre enquestion la faisabilité des tâches périodiques. Nous considérons unsystème monoprocesseur monofréquence, alimenté par un réservoir d’énergieapprovisionné par une source environnementale.Dans ce cadre, nous avons proposé quatre nouveaux serveurs de tâchesapériodiques utilisables avec l’ordonnanceur optimal ED-H. L’étude acomporté une phase de validation théorique puis une étude de simulation

Real-Time Scheduling of DAG Tasks in Self-Powered Sensors with Scavenged Energy

International audienceEnergy harvesting sensors move into the mainstream because they are regarded as a perfect match for the monitoring applications. Nonetheless, their implementation is only feasible if the computing unit, generally a microcontroller, is capable of running the real-time tasks using sophisticated scheduling and power management techniques. In this paper, we address the hard real-time scheduling problem of Directed Acyclic Graph (DAG) tasks in a uniprocessor RTEH (Real Time Energy Harvesting) computing system. In this model, a task is defined as a set of dependent sub-tasks that execute under precedence constraints with processing time and energy requirements. We demonstrate that the energy aware ED-H algorithm provides an optimal solution. We show that the scheduling policy directly includes a feasibility analysis by enforcing the precedence constraints, thus making it possible to get rid of semaphore synchronization

Multiprocessor Real-Time Scheduling for WirelessSensors Powered by Renewable Energy Sources

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Stratégies d’ordonnancement temps réel pour les systèmes embarqués autonomes en énergie

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Aperiodic Task Servicing in Real-Time Energy Harvesting Devices

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Minimizing the aperiodic responsiveness in Energy Harvesting Devices

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An optimal approach for minimizing aperiodic response times in Real-time Energy Harvesting Systems

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Scheduling mixed task sets in energy harvesting embedded systems

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Energy management and real-time scheduling for the Internet of Things

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