Model-based optimization of ARINC-653 partition scheduling

Pujie Han*, Zhengjun Zhai, Brian Nielsen, Ulrik Nyman

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

3 Citations (Scopus)
139 Downloads (Pure)


The architecture of ARINC-653 partitioned scheduling has been widely applied to avionics systems owing to its robust temporal isolation among applications. However, this partitioning mechanism causes the problem of how to optimize the partition scheduling of a complex system while guaranteeing its schedulability. In this paper, a model-based optimization approach is proposed. We formulate the problem as a parameter sweep application, which searches for the optimal partition scheduling parameters with respect to minimum processor occupancy via an evolutionary algorithm. An ARINC-653 partitioned scheduling system is modeled as a set of timed automata in the model checker UPPAAL. The optimizer tentatively assigns parameter settings to the models and subsequently invokes UPPAAL to verify schedulability as well as evaluate promising solutions. The parameter space is explored with an evolutionary algorithm that combines refined genetic operators and the self-adaptation of evolution strategies. The experimental results show the applicability of our optimization method.
Original languageEnglish
JournalInternational Journal on Software Tools for Technology Transfer
Issue number5
Pages (from-to)721-740
Number of pages20
Publication statusPublished - 7 Feb 2021


  • Evolutionary algorithm
  • Model-based optimization
  • Parameter sweep
  • Partitioned scheduling
  • Timed automata


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