Abstract

The growth of environmental energy harvesting has been explosive in wireless computing systems especially when replacing or recharging batteries manually is impracticable. This work investigates the scheduling of periodic weekly hard real-time tasks under energy constraints. Based on this motivation, we proposed a real-time scheduling algorithm, namely energy guarantee dynamic voltage and frequency scaling (EG-DVFS), that utilizes the earliest deadline-harvesting (ED-H) scheduling algorithm combined with dynamic voltage and frequency scaling. This one is qualified as real-time since tasks must satisfy their timing constraints. We assume that the preemptable tasks receive dynamic priorities according to the earliest deadline first (EDF) rule. EG-DVFS adjusts the processor’s behavior by characterizing the properties of the energy source module, capacity of the stored energy as well as the harvested energy in a future duration. Specifically, tasks are executed at full processor speed if the amount of energy in the battery is enough to finish its execution. Otherwise, the processor slows down task execution to the lowest possible processor speed while still guaranteeing to meet all the timing constraints. EG-DVFS mainly depends on the on-line computation of the slack time and the slack energy with dynamic voltage and frequency selection in order to achieve an improved system performance. Experimental results show that EG-DVFS can achieve capacity savings up of up to 33% when compared to ED-H.

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