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Preemption-aware dynamic voltage scaling in hard real-time systems

Woonseok Kim, Jihong Kim, Sang Lyul Min

Open publisher page 70 citations

Abstract

Dynamic voltage scaling (DVS) is a well-known low-power design technique for embedded real-time systems. Because of its effectiveness on energy reduction, several variable voltage processors have been developed and many DVS algorithms targeting these processors have been proposed. However, most existing DVS algorithms focus on reducing the energy consumption of CPU only, ignoring their negative impacts on task scheduling and system wide energy consumption. In this paper, we address one of such side effects, an increase in task preemptions due to DVS. We present two preemption control techniques which can reduce the number of task preemptions of DVS algorithms. Experimental results show that the delayed-preemption technique is effective in reducing the number of preemptions incurred by DVS algorithms while achieving a high energy efficiency.

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What this paper is about

Dynamic voltage scaling (DVS) is a well-known low-power design technique for embedded real-time systems. Because of its effectiveness on energy reduction, several variable voltage processors have been developed and many DVS algorithms targeting these processors have been proposed. However, most existing DVS algorithms focus on reducing the energy consumption of CPU only, ignoring their negative impacts on task scheduling and system wide energy consumption. In this paper, we address one of such side effects, an increase in task preemptions due to DVS. We present two preemption control techniques which can reduce the number of task preemptions of DVS algorithms. Experimental results show that the delayed-preemption technique is effective in reducing the number of preemptions incurred by DVS algorithms while achieving a high energy efficiency.

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Available abstract

Dynamic voltage scaling (DVS) is a well-known low-power design technique for embedded real-time systems. Because of its effectiveness on energy reduction, several variable voltage processors have been developed and many DVS algorithms targeting these processors have been proposed. However, most existing DVS algorithms focus on reducing the energy consumption of CPU only, ignoring their negative impacts on task scheduling and system wide energy consumption. In this paper, we address one of such side effects, an increase in task preemptions due to DVS. We present two preemption control techniques which can reduce the number of task preemptions of DVS algorithms. Experimental results show that the delayed-preemption technique is effective in reducing the number of preemptions incurred by DVS algorithms while achieving a high energy efficiency.

Key concepts: Preemption, Dynamic voltage scaling, Computer science, Energy consumption, Scheduling (production processes), Embedded system, Scaling, Parallel computing

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