Dynamic voltage scaling (DVS) is a well-known low power design technique that reduces the processor energy by slowing down the DVS processor and stretching the task execution time. But in a DVS system consisting of a DVS processor and multiple devices, slowing down the processor increases the device energy consumption and thereby the system-level energy consumption. In this paper, we present dynamic task scheduling algorithms for periodic tasks that minimize the system-level energy (CPU energy + device standby energy). The algorithms use a combination of (i)  optimal speed  setting, which is the speed that minimizes the system energy for a specific task, and (ii)  limited preemption  which reduces the numbers of possible preemptions. For the case when the CPU power and device power are comparable, these algorithms achieve up to 43% energy savings compared to [1], but only up to 12% over the non-DVS scheduling. If the device power is large compared to the CPU power, we show that DVS should not be employed.
['Jianli Zhuo', 'Chaitali Chakrabarti']
System-level energy-efficient dynamic task scheduling