Tardiness bounds for global EDF with deadlines different from periods

Jeremy Erickson, Nan Guan, Sanjoy Baruah

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

10 Citations (Scopus)

Abstract

The Earliest Deadline First (EDF) scheduling algorithm is known to be suboptimal for meeting all deadlines under global scheduling on multiprocessor platforms. However, EDF is an attractive choice for scheduling soft-real-time systems on multiprocessors. Previous work has demonstrated that the maximum tardiness is bounded, and has derived formulas for computing tardiness bounds, in EDF-scheduled real-time systems that can be modeled as collections of recurrent tasks modeled using the well-known implicit-deadline (Liu and Layland) task model. This research extends the applicability of previous techniques to systems that are modeled using the more general arbitrary sporadic task model. It also improves on prior work even for implicit-deadline systems. An algorithm is derived here that computes tardiness bounds in polynomial time. Previously, these bounds could only have been approximated in sub-exponential time.
Original languageEnglish
Title of host publicationPrinciples of Distributed Systems - 14th International Conference, OPODIS 2010, Proceedings
Pages286-301
Number of pages16
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event14th International Conference on Principles of Distributed Systems, OPODIS 2010 - Tozeur, Tunisia
Duration: 14 Dec 201017 Dec 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6490 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Principles of Distributed Systems, OPODIS 2010
Country/TerritoryTunisia
CityTozeur
Period14/12/1017/12/10

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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