Abstract
Energy efficiency is an important factor in embedded systems design. We consider an embedded system with a dynamic voltage scaling (DVS) capable processor and its system-wide power consumption is dominated by the processor and memory. We present speed assignment polices for a set of periodic/aperiodic tasks that minimize the overall system energy consumption including active and idle power of CPU and other components. A limitation of most DVS-based system-wide energy optimization techniques is that they assume the number of worst-case execution cycles (WCEC) of a task is a constant, independent of CPU frequency. This is not the case when other system components such as memory are taken into account. In this paper, we decompose task execution time into two parts: on-chip inside CPU and off-chip outside the CPU. We propose a frequency-aware system-wide energy minimization approach and establish necessary and sufficient conditions for the optimality. By exploiting properties of the conditions, we derive a bisection algorithm that finds the optimal solution to offline periodict asks in a linear time complexity. We apply a similar analytical approach to online aperiodic tasks scheduling and devise an iterative speed assignment algorithm in the complexity of O ( n 2 ). We prove it is optimal among all online algorithms without assumptions about future task releases.
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