MIRROR: Symmetric timing analysis for real-time tasks on multicore platforms with shared resources

The emergence of multicore and manycore platforms poses a big challenge for the design of real-time embedded systems, especially for timing analysis. We observe in this paper that response-time analysis for multicore platforms with shared resources can be symmetrically approached from two perspectives: a core-centric and a shared-resource-centric perspective. The common “core-centric” perspective is that a task executes on a core until it suspends the execution due to shared resource accesses. The potentially less intuitive “shared-resource-centric” perspective is that a task performs requests on shared resources until suspending itself back to perform computation on its respective core. Based on the above observation, we provide a pseudo-polynomial-time schedulability test and response-time analysis for constrained-deadline sporadic task systems. In addition, we propose a task partitioning algorithm that achieves a speedup factor of 7, compared to the optimal schedule. This constitutes the first result in this research line with a speedup factor guarantee. The experimental evaluation demonstrates that our approach can yield high acceptance ratios if the tasks have only a few resource access segments.