Abstract
The effectiveness of sensor networks depends critically on efficient power management of the sensor nodes. Dynamic voltage frequency scaling (DVFS) and dynamic power management (DPM) have been proposed to enable energy-efficient scheduling for real-time and embedded systems. However, most power-aware scheduling algorithms are designed to deal with only those cases in which the task execution time is determined solely by the clock frequency of the processor. In this study, we propose an extended task execution model that is appropriate for the sensor nodes and an algorithm that determines the optimal clock frequency for a node's processor. We analyze the extended model and verify that our algorithm calculates the clock frequency that optimizes energy savings while satisfying the timing constraints.
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