{"title":"Preemption-aware dynamic voltage scaling in hard real-time systems","authors":"Woonseok Kim, Jihong Kim, S. Min","doi":"10.1145/1013235.1013328","DOIUrl":null,"url":null,"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.","PeriodicalId":120002,"journal":{"name":"Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"80","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2004 International Symposium on Low Power Electronics and Design (IEEE Cat. No.04TH8758)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1013235.1013328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 80
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.