An adaptive scheduling and voltage/frequency selection algorithm for real-time energy harvesting systems

Shaobo Liu, Qing Wu, Qinru Qiu

Research output: Chapter in Book/Entry/PoemConference contribution

66 Scopus citations

Abstract

In this paper we propose an adaptive scheduling and voltage/frequency selection algorithm which targets at energy harvesting systems. The proposed algorithm adjusts the processor operating frequency under the timing and energy constraints based on workload information so that the system-wide energy efficiency is achieved. In this approach, we decouple the timing and energy constraints and simplify the original scheduling problem by separating constraints in timing and energy domains. The proposed algorithm utilizes maximum task slack for energy saving. Experimental results show that the proposed method improves the system performance in remaining energy, deadline miss rate and the minimum storage capacity requirement for zero deadline miss rate. Comparing to the existing algorithms, the new algorithm decreases the deadline miss rate by at least 23%, and the minimum storage capacity by at least 20% under various processor utilizations.

Original languageEnglish (US)
Title of host publication2009 46th ACM/IEEE Design Automation Conference, DAC 2009
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages782-787
Number of pages6
ISBN (Print)9781605584973
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 46th ACM/IEEE Design Automation Conference, DAC 2009 - San Francisco, CA, United States
Duration: Jul 26 2009Jul 31 2009

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Other

Other2009 46th ACM/IEEE Design Automation Conference, DAC 2009
Country/TerritoryUnited States
CitySan Francisco, CA
Period7/26/097/31/09

Keywords

  • Dynamic voltage and frequency selection
  • Energy harvesting

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

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