Mapping and Integration of Event- and Time-triggered Real-time Tasks on Partitioned Multi-core Systems

In order to meet the requirements of critical applications, modern multi-core multi-SoC real-time systems must handle both periodic and sporadic events within specified deadlines. A two-level scheduling hierarchy that combines time-triggered and fixed-priority scheduling is effective for managing periodic time-triggered (TT) and sporadic event-triggered (ET) tasks, respectively. We introduce two polling-based approaches, called simple and advanced polling, for guaranteeing both TT and ET task deadlines within single core systems. We then propose an optimization heuristic for the task-to-core allocation problem based on genetic algorithms for fully partitioned multi-core systems that can be applied to both polling methods. We evaluate the schedulability and runtime performance of the polling approaches and investigate the effectiveness of the allocation heuristic using synthetic test cases based on real-world application characteristics. The results show that both polling approaches achieve high schedulability with low runtime, and the allocation heuristic can generate good solutions for fully partitioned systems. Furthermore, we show that the server design problem of the advanced polling approach can be integrated into the allocation heuristic to achieve better solutions in terms of schedulability and that our choice of the genetic algorithm has a good speedup when being parallelized.