• DocumentCode
    500813
  • Title

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

  • Author

    Liu, Shaobo ; Wu, Qing ; Qiu, Qinru

  • Author_Institution
    Dept. of Electr. & Comput. Eng., State Univ. of New York, Binghamton, NY, USA
  • fYear
    2009
  • fDate
    26-31 July 2009
  • Firstpage
    782
  • Lastpage
    787
  • 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.
  • Keywords
    adaptive scheduling; energy conservation; energy harvesting; power aware computing; processor scheduling; real-time systems; adaptive scheduling; energy efficiency; energy harvesting systems; processor operating frequency; real-time systems; voltage frequency selection algorithm; Adaptive scheduling; Energy efficiency; Energy storage; Frequency; Processor scheduling; Real time systems; Scheduling algorithm; System performance; Timing; Voltage; Dynamic voltage and frequency selection; Energy harvesting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design Automation Conference, 2009. DAC '09. 46th ACM/IEEE
  • Conference_Location
    San Francisco, CA
  • ISSN
    0738-100X
  • Print_ISBN
    978-1-6055-8497-3
  • Type

    conf

  • Filename
    5227068