[183642] |
Title: Efficient and Effective Multi-Objective Optimization for Real-Time Multi-Task Systems. <em>In Proceedings of the 21st International Workshop on Worst-Case Execution Time Analysis (WCET)</em> |
Written by: Shashank Jadhav and Heiko Falk |
in: July (2023). |
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on pages: 5:1-5:12 |
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Address: Vienna / Austria |
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ISBN: 10.4230/OASIcs.WCET.2023.5 |
how published: 23-75 JF23a WCET |
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Note: sjadhav, hfalk, teamplay, ESD, WCC
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.