Approximation algorithms for power minimization of earliest deadline first and rate monotonic schedules

  • Authors:
  • Sushu Zhang;Karam S. Chatha;Goran Konjevod

  • Affiliations:
  • Arizona State University;Arizona State University;Arizona State University

  • Venue:
  • ISLPED '07 Proceedings of the 2007 international symposium on Low power electronics and design
  • Year:
  • 2007

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Abstract

We address power minimization of earliest deadline first and rate monotonic schedules by voltage and frequency scaling. We prove that the problems are NP-hard, and present (1+∈) fully polynomial time approximation techniques that generate solutions which are guaranteed to be within a specified quality bound (QB= ∈) (say within 1% of the optimal). We demonstrate that our techniques can match optimal solutions when QB is set at 1%, out perform existing approaches [1] even when QB is set at 10%, generate solutions that are quite close to optimal ( 5%) for large 100 node task sets.