A time series-based approach for power management in mobile processors and disks

Abstract

In this paper, we present a time series-based approach for managing power in mobile processors and disks that see multimedia workloads. Since multimedia applications impose soft real-time constraints, a key goal of our approach is to reduce energy consumption of multimedia applications without degrading performance. We present simple statistical techniques based on time series to dynamically compute the processor and I/O demands of multimedia applications and present techniques to dynamically vary the voltage settings and rotational speeds of mobile processors and disks, respectively. We implement our approaches in the Linux kernel running on a Sony Transmeta laptop and in a trace-driven simulator. Our experiments show that, compared to the traditional system-wide CPU voltage scaling approaches, our technique can achieve up to a 38.6% energy saving while delivering good performance to applications. Simulation results for our disk power management technique show a 20.3% reduction in energy consumption without any significant performance loss when compared to a traditional disk power management scheme.