Optimal processor management for priority-driven schedulers with energy harvesting

An increasing number of wireless devices deployments are utilizing harvested ambient energy to increase system lifetime. The temporal profiles of the diverse environmental energy sources may be highly variable. So, creating an adaptive processor management mechanism enables the computing device to adjust its activity to changing environmental conditions and adopt an energy neutral operation mode. In this paper, we take into consideration any Priority Assignment (PA) rule jointly to preemptive scheduling. The paper proposes the priority assignment with energy harvesting) framework, a generalized scheduling approach that integrates a predictive look-ahead processor management mechanism into any PA rule, whether fixed or dynamic. We demonstrate that the resulting scheduler is optimal in that it allows to achieve energy neutrality with no deadline missing, no wasted energy, and no energy starvation whenever feasible with the PA rule. Our simulation results demonstrate that PA-H achieves a $100%$ deadline success ratio as soon as the energy replenishment ratio reaches neutrality. Furthermore, we quantify the benefit of this approach, showing that it can reduce the minimum required storage capacity by ~ 90% compared with standard rate monotonic scheduling. This enables the design of smaller, more sustainable autonomous devices without compromising real-time reliability.