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Toward an Optimal Fixed-Priority Algorithm for Energy-Harvesting Real-Time Systems

This 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 scheduling policy should account for incoming energy, capacity of the battery and tasks cost of energy. Thus, classical fixed-priority schedulers are no longer suitable for this model. Some algorithms were proposed in precedent works to solve this problem, however, none of them has been proved optimal for concrete tasksets1 . Based on this motivation, we propose FPCasap a scheduling algorithm that handles both energy and timing constraints by predicting future possible failure. Such kind of algorithm is said to be clairvoyant. We expect this algorithm to be optimal.