Projekter pr. år
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.
|Tidsskrift||International Journal on Software Tools for Technology Transfer|
|Status||Udgivet - 7 feb. 2021|
Bibliografisk noteFunding Information:
This work was in part funded by Independent Research Fund Denmark under Grant Number DFF-7017-00348, Compositional Verification of Real-time MULTI-CORE SAFETY Critical Systems.
© 2021, The Author(s).
Copyright 2021 Elsevier B.V., All rights reserved.
FingeraftrykDyk ned i forskningsemnerne om 'Model-based optimization of ARINC-653 partition scheduling'. Sammen danner de et unikt fingeraftryk.
- 1 Afsluttet
01/08/2017 → 31/07/2021
Projekter: Projekt › Andet