Efficient and Effective Multi-Objective Optimization for Real-Time Multi-Task Systems.

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. 2012 ACM Subject Classification Computer systems organization → Real-time systems; Software and its engineering → Compilers