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Energy minimization with soft real-time and DVS for uniprocessor and multiprocessor embedded systems

  • Meikang Qiu*
  • , Chun Xue
  • , Zili Shao
  • , Edwin H.M. Sha
  • *Corresponding author for this work
  • University of Texas at Dallas
  • Hong Kong Polytechnic University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Energy-saving is extremely important in real-time embedded systems. Dynamic Voltage Scaling (DVS) is one of the prime techniques used to achieve energy-saving. Due to the uncertainties in execution times of some tasks of systems, this paper models each varied execution time as a random variable. By using probabilistic approach, we propose two optimal algorithms, one for uniprocessor and one for multiprocessor to explore soft real-time embedded systems and avoid over-designing them. Our goal is to minimize the expected total energy consumption while satisfying the timing constraint with a guaranteed confidence probability. The solutions can be applied to both hard and soft real-time systems. The experimental results show that our approach achieves significant energy-saving than previous work.

Original languageEnglish
Title of host publicationProceedings - Design, Automation and Test in Europe Conference and Exhibition, DATE 2007
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1641-1646
Number of pages6
ISBN (Print)3981080122, 9783981080124
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 Design, Automation and Test in Europe Conference and Exhibition, DATE 2007 - Nice Acropolis, France
Duration: 16 Apr 200720 Apr 2007

Publication series

NameProceedings -Design, Automation and Test in Europe, DATE
ISSN (Print)1530-1591

Conference

Conference2007 Design, Automation and Test in Europe Conference and Exhibition, DATE 2007
Country/TerritoryFrance
CityNice Acropolis
Period16/04/0720/04/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

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