A Heuristic-Based Approach for Reducing the Power Consumption of Real-Time Embedded Systems

The current trend in designing power-efficient devices is concerning not only Personal Computer-like (PC) systems, but also real-time embedded systems. While a lot of research has been done on minimizing the total energy of a system, adapting the scheduling techniques for lower energy consumption has been less popular. Nevertheless, this can prove highly efficient, as the Central Processing Units (CPUs) are usually responsible for the largest part of the whole system's energy consumption. This paper presents an approach on improving the energy consumption of a real-time system. Starting with a given feasible schedule for a non-preemptive, single-instance, n-task set, power saving is achieved by reducing the CPU frequency whenever possible, without breaking the task deadlines. The goal can be described in analytical terms as a multivariate optimization problem. Due to the complexity of the resulting problem, the use of heuristic techniques provides good chances for finding the desired optimum. To the best of our knowledge, the use of these methods for the power-aware scheduling problem has not been attempted.

I. Introduction

The dramatic increase in the processing power of the computing devices has led to a tremendous growth in the request for real-time embedded systems, which are now capable of performing very complex tasks. Their applicability now covers, among other fields, telecommunications (with the smartphones as flagship), data transmission (fax machines, GPS receivers), transportation (cars, airplanes, boats), medicine (life-support and monitoring devices, blood pressure monitors), or entertainment (Xboxes, PSPs, Wii).