You are here:

Time and Energy Efficient DVS Scheduling for Real-Time Pinwheel Tasks
ARTICLE

, Department of Information Management, National Taichung University of Science and Technology ; , Department of Computer Science and Information, Engineering National Taichung University of Science and Technology ; , Department of Information Management, Hwa Hsia University of Technology

Journal of Applied Research and Technology Volume 12, Number 6, ISSN 1665-6423 Publisher: Elsevier Ltd

Abstract

Dynamic voltage/frequency scaling (DVFS) is one of the most effective techniques for reducing energy use. In this paper, we focus on the pinwheel task model to develop a variable voltage processor with d discrete voltage/speed levels. Depending on the granularity of execution unit to which voltage scaling is applied, DVFS scheduling can be defined in two categories: (i) inter-task DVFS and (ii) intra-task DVFS. In the periodic pinwheel task model, we modified the definitions of both intra- and inter-task and design their DVFS scheduling to reduce the power consumption of DVFS processors. Many previous approaches have solved DVFS problems by generating a canonical schedule in advance and thus require pseudo polynomial time and space because the length of a canonical schedule depends on the hyperperiod of the task periods and is generally of exponential length. To limit the length of the canonical schedules and predict their task execution, tasks with arbitrary periods are first transformed into harmonic periods and their key features are profiled. The proposed methods have polynomial time and space complexities, and experimental results show that, under identical assumptions, the proposed methods achieve more energy savings than the previous methods.

Citation

Da-Ren, C., Young-Long, C. & You-Shyang, C. (2014). Time and Energy Efficient DVS Scheduling for Real-Time Pinwheel Tasks. Journal of Applied Research and Technology, 12(6), 1025-1039. Elsevier Ltd. Retrieved May 9, 2021 from .

This record was imported from Journal of Applied Research and Technology on January 29, 2019. Journal of Applied Research and Technology is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/S1665-6423(14)71663-3

Keywords