@inproceedings{JF23a,
Author = {Shashank Jadhav and Heiko Falk},
Title = {Efficient and Effective Multi-Objective Optimization for Real-Time Multi-Task Systems.},
Year = {(2023).},
Pages = {5:1-5:12},
Month = {July},
Note = {sjadhav, hfalk, teamplay, ESD, WCC},
Address = {Vienna / Austria},
Isbn = {10.4230/OASIcs.WCET.2023.5},
Howpublished = {23-75 JF23a WCET},
Booktitle = {<em>In Proceedings of the 21st International Workshop on Worst-Case Execution Time Analysis (WCET)</em>},
Abstract = {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.}
}

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