No abstract

The paper addresses the real-time fixed-priority scheduling problem for battery-powered embedded systems whose energy storage unit is replenished by an environmental energy source. In this context, a task may meet its deadline only if its cost of energy can be satisfied early enough. Hence, a scheduling policy for such a system should account for properties of the source of energy, capacity of the energy storage unit and tasks cost of energy. Classical fixed-priority schedulers are no more suitable for this model. Based on these motivations, we propose P F PASAP an optimal scheduling algorithm that handles both energy and timing constraints. Furthermore, we state the worst case scenario for non concrete tasksets 1 scheduled with this algorithm and build a necessary and sufficient feasibility condition for non concrete tasksets. Moreover, a minimal bound of the storage unit capacity that keeps a taskset schedulable with P F PASAP is also proposed. Finally, we validate the proposed theory with large scale simulations and compare our algorithm with other existing ones.

The new generation of embedded systems will have the capability to harvest energy from the environment. The electrical energy which is available to power these devices changes over time and is limited by the size of the energy storage unit such as battery or capacitor and the size of the harvester such as a solar panel. In order to cope with this limitation, the system has to dynamically decide when to be active and when to sleep in order to provide the best quality of service without wasting the harvested energy. In this paper, we study this problem for a uniprocessor architecture where periodic tasks have to execute with deadline constraints according to a preemptive fixed priority rule. We evaluate and compare several scheduling approaches by means of simulation.

International audienceIn this paper, we propose feasibility and schedulability tests for a real-time scheduling problem under energy constraints. We first introduce the problem and show how to model it using timed automata. We propose then a feasibility test based on CTL model checking and schedulability tests for EDF and fixed priority algorithms. Our approach also permits to generate a feasible schedule if one exists and otherwise to find the good characteristics of a battery to make the problem feasible. It is finally possible to generate schedules that optimize some criteria, such as the number of mode switching (battery charge or discharge), the minimal and the maximal energy level, or the number of preemptions. The approach is illustrated by some experiments using the model checking tool U PPAAL