Task scheduling in supercapacitor based environmentally powered wireless sensor nodes
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The objective of this dissertation is to develop task scheduling guidelines and algorithms for wireless sensor nodes that harvest energy from ambient environment and use supercapacitor based storage systems to buffer the harvested energy. This dissertation makes five contributions. First, a physics based equivalent circuit model for supercapacitors is developed. The variable leakage resistance (VLR) model takes into account three mechanisms of supercapacitors: voltage dependency of capacitance, charge redistribution, and self-discharge. Second, the effects of time and supercapacitor initial state on supercapacitor voltage change and energy loss during charge redistribution are investigated. Third, the task scheduling problem in supercapacitor based environmentally powered wireless sensor nodes is studied qualitatively. The impacts of supercapacitor state and energy harvesting on task scheduling are examined. Task scheduling rules are developed. Fourth, the task scheduling problem in supercapacitor based environmentally powered wireless sensor nodes is studied quantitatively. The modified earliest deadline first (MEDF) algorithm is developed to schedule nonpreemptable tasks without precedence constraints. Finally, the modified first in first out (MFIFO) algorithm is proposed to schedule nonpreemptable tasks with precedence constraints. The MEDF and MFIFO algorithms take into account energy constraints of tasks in addition to timing constraints. The MEDF and MFIFO algorithms improve the energy performance and maintain the timing performance of the earliest deadline first (EDF) and first in first out (FIFO) algorithms, respectively.