Scheduling Computational and Energy Harvesting Tasks in Deadline-Aware Intermittent Systems

The sporadic nature of harvestable energy and the mutually exclusive computing and charging cycles of intermittently powered batteryless systems pose a unique and challenging real-time scheduling problem. Existing literature focus either on the time or the energy constraints but not both at the same time. In this paper, we propose two scheduling algorithms, named Celebi-Offline and Celebi-Online, for intermittent systems that schedule both computational and energy harvesting tasks by harvesting the required minimum amount of energy while maximizing the schedulability of computational jobs. To evaluate Celebi, we conduct simulation as well as trace-based and real-life experiments. Our results show that the proposed Celebi-Offline algorithm has 92% similar performance as an optimal scheduler, and Celebi-Online scheduler schedules 8% - 22% more jobs than the earliest deadline first (EDF), rate monotonic (RM), and as late as possible (ALAP) scheduling algorithms. We deployed solar-powered batteryless systems where four intermittent applications are executed in the TI-MSP430FR5994 microcontroller and demonstrate that the system with Celebi-Online misses 63% less deadline than a non-realtime system and 8% less deadline than the system with a baseline (as late as possible) scheduler.