A Semi-Partitioned Model for Mixed Criticality Systems

Hao Xu, Alan Burns

Research output: Contribution to journalArticlepeer-review


Many Mixed Criticality algorithms have been developed with an assumption that
lower criticality-level tasks may be abandoned in order
to guarantee the schedulability of higher-criticality tasks when the criticality level of the system changes.
But it is valuable to explore means by which all of the tasks remain schedulable through these criticality level changes.
This paper introduces a semi-partitioned model for a multi-core platform that
allows all of the tasks to remain schedulable if
only a bounded number of cores increase their criticality level. In such a model,
some lower-criticality tasks are allowed to migrate instead of being abandoned.
Detailed response time analysis for this model is derived.
This paper also introduces possible approaches for establishing migration routes.
Together with related previous work, an appropriate semi-partitioned model for mixed
criticality systems hosted on multi-core platforms is recommended.
Original languageEnglish
Pages (from-to)51-63
Number of pages13
JournalJournal of Systems and Software
Early online date9 Jan 2019
Publication statusPublished - 1 Apr 2019


  • Real-time
  • Mixed Criticality

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