Reference : Optimal Priority Assignment for Real-Time Systems: A Coevolution-Based Approach
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/50804
Optimal Priority Assignment for Real-Time Systems: A Coevolution-Based Approach
English
Lee, Jaekwon mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV >]
Shin, Seung Yeob mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV >]
Nejati, Shiva [University of Ottawa, Canada > School of Electrical Engineering and Computer Science]
Briand, Lionel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV > ; University of Ottawa,Canada > School of Electrical Engineering and Computer Science]
In press
Empirical Software Engineering
Kluwer Academic Publishers
Advances in Search-Based Software Engineering
Yes
International
1382-3256
1573-7616
Netherlands
[en] Priority Assignment ; Schedulability Analysis ; Real-Time Systems ; Coevolutionary Search ; Search-Based Software Engineering
[en] In real-time systems, priorities assigned to real-time tasks determine the order of task executions, by relying on an underlying task scheduling policy. Assigning optimal priority values to tasks is critical to allow the tasks to complete their executions while maximizing safety margins from their specified deadlines. This enables real-time systems to tolerate unexpected overheads in task executions and still meet their deadlines. In practice, priority assignments result from an interactive process between the development and testing teams. In this article, we propose an automated method that aims to identify the best possible priority assignments in real-time systems, accounting for multiple objectives regarding safety margins and engineering constraints. Our approach is based on a multi-objective, competitive coevolutionary algorithm mimicking the interactive priority assignment process between the development and testing teams. We evaluate our approach by applying it to six industrial systems from different domains and several synthetic systems. The results indicate that our approach significantly outperforms both our baselines, i.e., random search and sequential search, and solutions defined by practitioners. Our approach scales to complex industrial systems as an offline analysis method that attempts to find near-optimal solutions within acceptable time, i.e., less than 16 hours.
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab) ; University of Luxembourg: High Performance Computing - ULHPC
European Research Council (ERC) ; NSERC
http://hdl.handle.net/10993/50804
H2020 ; 694277 - TUNE - Testing the Untestable: Model Testing of Complex Software-Intensive Systems

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