CyEnSe: Cyclic energy-aware scheduling for energy-harvested embedded systems

New advances in energy harvesting from human's body enable battery-less wearable and implantable devices to have more advanced functionalities and hence higher number of tasks to be scheduled on the device. The nature of variable and cyclic energy harvesting from periodic body movements (e.g: walking, heartbeat) challenges the tasks scheduling in these real-time systems, especially for the safety-critical applications when the tasks deadlines are hard. For the first time, this paper addresses cyclic energy harvesting in an offline cyclic-executive scheduling. The paper defines CyEnSe, a scheduling problem in presence of cyclic energy. It proposes two methods, a heuristic, and a linear-programming to solve the hard-deadline periodic task scheduling problem while considers variable cyclic energy arrivals from the energy harvester. We present a comparison among the proposed methods and a First-Fit approach from different optimization point of views, for instance, task utilization, number of tasks, and amount of harvested energy.