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Efficient and effective multi-objective optimization for real-time multi-task systems
Citation Link: https://doi.org/10.15480/882.8710
Publikationstyp
Conference Paper
Publikationsdatum
2023-07-26
Sprache
English
First published in
Number in series
114
Volume
114
Article Number
5
Citation
21st International Workshop on Worst-Case Execution Time Analysis (WCET 2023)
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
Schloss Dagstuhl - Leibniz-Zentrum für Informatik GmbH
ISBN
978-3-95977-293-8
Embedded real-time multi-task systems must often not only comply with timing constraints but also need to meet energy requirements. However, optimizing energy consumption might lead to higher Worst-Case Execution Time (WCET), leading to an un-schedulable system, as frequently executed code can easily differ from timing-critical code. To handle such an impasse in this paper, we formulate a Metaheuristic Algorithm-based Multi-objective Optimization (MAMO) for multi-task real-time systems. But, performing multiple WCET, energy, and schedulability analyses to solve a MAMO poses a bottleneck concerning compilation times. Therefore, we propose two novel approaches - Path-based Constraint Approach (PCA) and Impact-based Constraint Approach (ICA) - to reduce the solution search space size and to cope with this problem. Evaluations showed that PCA and ICA reduced compilation times by 85.31% and 77.31%, on average, over MAMO. For all the task sets, out of all solutions found by ICA-FPA, on average, 88.89% were on the final Pareto front.
Schlagworte
Compilers
Design space reduction
Metaheuristic algorithms
Multi-objective optimization
Real-time systems
DDC Class
004: Computer Sciences
510: Mathematics
Publication version
publishedVersion
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OASIcs-WCET-2023-5.pdf
Type
main article
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768.21 KB
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