Semi-Federated Scheduling of Parallel Real-Time Tasks on Multiprocessors

Xu Jiang, Nan Guan, Xiang Long, Wang Yi

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

34 Citations (Scopus)


Federated scheduling is a promising approach to schedule parallel real-time tasks on multi-cores, where each heavy task exclusively executes on a number of dedicated processors, while light tasks are treated as sequential sporadic tasks and share the remaining processors. However, federated scheduling suffers resource waste since a heavy task with processing capacity requirement x+epsilon (where x is an integer and 0 epsilon 1) needs x+1 dedicated processors. In the extreme case, almost half of the processing capacity is wasted. In this paper we propose the semi-federate scheduling approach, which only grants x dedicated processors to a heavy task with processing capacity requirement x+epsilon, and schedules the remaining epsilon part together with light tasks on shared processors. Experiments with randomly generated task sets show the semi-federated scheduling approach significantly outperforms not only federated scheduling, but also all existing approaches for scheduling parallel real-time tasks on multi-cores.
Original languageEnglish
Title of host publicationProceedings - 2017 IEEE Real-Time Systems Symposium, RTSS 2017
Number of pages12
ISBN (Electronic)9781538614143
Publication statusPublished - 31 Jan 2018
Event38th IEEE Real-Time Systems Symposium, RTSS 2017 - Paris, France
Duration: 5 Oct 20178 Oct 2017

Publication series

NameProceedings - Real-Time Systems Symposium
ISSN (Print)1052-8725


Conference38th IEEE Real-Time Systems Symposium, RTSS 2017


  • DAG
  • federated-scheduling
  • parallel-tasks
  • real-time-scheduling

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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