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

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

Energy Guarantee Scheme for Real-time Systems with Energy Harvesting Constraints

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Optimal Real-Time Scheduling Algorithm for Wireless Sensors with Regenerative Energy

Dynamic Voltage and Frequency Scaling (DVFS) is a promising and broadly used energy efficient technique to overcome the main problems arising from using a finite energy reservoir capacity and uncertain energy source in real-time embedded systems. This work investigates an energy management scheme for real-time task scheduling in variable voltage processors located in sensor nodes and powered by ambient energy sources. We use DVFS technique to decrease the energy consumption of sensors at the time when the energy sources are limited. In particular, we develop and prove an optimal real-time scheduling framework with speed stretching, namely Energy Guarantee Dynamic Voltage and Frequency Scaling (EG-DVFS), that jointly accounts not only for the timing constraints, but also for the energy state incurred by the properties of the system components. EG-DVFS relies on the well-known ED-H scheduling algorithm combined with DVFS technique where the sensor processing frequency is fine tuned to further minimize energy consumption and to achieve an energy autonomy of the system. Further, an exact feasibility test for a set of periodic, aperiodic or evern sporadic tasks is presented

Optimal Real-Time Scheduling Algorithm for Wireless Sensors with Regenerative Energy

International audienceAbstract Dynamic voltage and frequency scaling (DVFS) is a promising and broadly used energy-efficient technique to overcome the main problems arising from using a finite energy reservoir capacity and uncertain energy source in real-time embedded systems. This work investigates an energy management scheme for real-time task scheduling in variable voltage processors located in sensor nodes and powered by ambient energy sources. We use DVFS technique to decrease the energy consumption of sensors at the time when the energy sources are limited. In particular, we develop and prove an optimal real-time scheduling framework with speed stretching, namely energy guarantee DVFS (EG-DVFS), that jointly accounts not only for the timing constraints, but also for the energy state incurred by the properties of the system components. EG-DVFS relies on the well-known earliest deadline-harvesting scheduling algorithm combined with DVFS technique where the sensor processing frequency is fine tuned to further minimize energy consumption and to achieve an energy autonomy of the system. Further, an exact feasibility test for a set of periodic, aperiodic or even sporadic tasks is presented

Energy Saving EDF Scheduling for Wireless Sensors on Variable Voltage Processors

Abstract—Advances in micro technology has led to the development of miniaturized sensor nodes with wireless communication to perform several real-time computations. These systems are deployed wherever it is not possible to maintain a wired network infrastructure and to recharge/replace batteries and the goal is then to prolong as much as possible the lifetime of the system. In our work, we aim to modify the Earliest Deadline First (EDF) scheduling algorithm to minimize the energy consumption using the Dynamic Voltage and Frequency Selection. To this end, we propose an Energy Saving EDF (ES-EDF) algorithm that is capable of stretching the worst case execution time of tasks as much as possible without violating deadlines. We prove that ES-EDF is optimal in minimizing processor energy consumption and maximum lateness for which an upper bound on the processor energy saving is derived. In order to demonstrate the benefits of our algorithm, we evaluate it by means of simulation. Experimental results show that ES-EDF outperforms EDF and Enhanced EDF (E-EDF) algorithms in terms of both percentage of feasible task sets and energy savings. I

Aperiodic Task Servicing in Real-Time Energy Harvesting Devices

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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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