DocumentCode :
262010
Title :
A Heuristic-Based Approach for Reducing the Power Consumption of Real-Time Embedded Systems
Author :
Radulescu, Vlad ; Andrei, Stefan ; Cheng, Albert M. K.
Author_Institution :
Dept. of Comput. Sci., Al.I. Cuza Univ. of Iasi, Iasi, Romania
fYear :
2014
fDate :
22-25 Sept. 2014
Firstpage :
172
Lastpage :
179
Abstract :
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.
Keywords :
embedded systems; multiprocessing systems; optimisation; power aware computing; processor scheduling; CPU frequency reduction; central processing units; energy consumption; heuristic techniques; multivariate optimization problem; nonpreemptive single-instance n-task set; personal computer-like systems; power saving; power-aware scheduling problem; power-efficient devices; real-time embedded systems; task deadlines; Energy consumption; Optimization; Power demand; Processor scheduling; Real-time systems; Schedules; Scheduling; heuristic techniques; multivariate optimization; power saving; task scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2014 16th International Symposium on
Conference_Location :
Timisoara
Print_ISBN :
978-1-4799-8447-3
Type :
conf
DOI :
10.1109/SYNASC.2014.31
Filename :
7034681
Link To Document :
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