Power-aware scheduling for periodic real-time tasks

We address power-aware scheduling of periodic tasks to reduce CPU energy consumption in hard real-time systems through dynamic voltage scaling. Our intertask voltage scheduling solution includes three components: 1) a static (offline) solution to compute the optimal speed, assuming worst-case workload for each arrival, 2) an online speed reduction mechanism to reclaim energy by adapting to the actual workload, and 3) an online, adaptive and speculative speed adjustment mechanism to anticipate early completions of future executions by using the average-case workload information. All these solutions still guarantee that all deadlines are met. Our simulation results show that our reclaiming algorithm alone outperforms other recently proposed intertask voltage scheduling schemes. Our speculative techniques are shown to provide additional gains, approaching the theoretical lower-bound by a margin of 10 percent.

1 Introduction

In the last decade, the research community has addressed low-power system design problems with a multidimensional effort. Reducing the energy consumption of a computer system has necessarily multiple aspects, involving separate components such as CPU, memory system, and I/O subsystem. Hardware and software manufacturers have agreed to introduce standards such as the ACPI (Advanced Configuration and Power Interface) [10] for power management of laptop computers that allows several modes of operation, such as predictive system shutdown. An obvious target for energy reduction is the processor: An early study found that 18-30 percent of the total energy consumption is due to the CPU alone [17]. More recent reports show that this fraction can exceed 50 percent for CPU-intensive workloads [24], [31]. Dynamic voltage scaling (DVS) framework, which involves dynamically adjusting the voltage and frequency to reduce CPU power consumption, has recently become a major research area.