An Average-Case Analysis for Rate-Monotonic Multiprocessor Real-time Scheduling

We introduce the "First Fit Matching Periods" algorithm for static-priority multiprocessor scheduling of periodic tasks with implicit deadlines and show that it yields asymptotically optimal processor assignments if utilization values are chosen uniformly at random. More precisely we prove that the expected waste is upper bounded by O(n^(3/4) * (log n)^(3/8)). Here the waste denotes the ratio of idle times, cumulated over all processors and n gives the number of tasks. The algorithm can be implemented to run in time O(n log n) and even in the worst case, an asymptotic approximation ratio of 2 is guaranteed. Experiments yield an expected waste proportional to n^0.70, indicating that the above upper bound on the expected waste is almost tight

Multi-source and multicore automotive ECUs - OS protection mechanisms and scheduling

International audienceAs the demand for computing power is quickly increasing in the automotive domain, car manufacturers and tier-one suppliers are gradually introducing multicore ECUs in their electronic architectures. Additionally, these multicore ECUs offer new features such as higher levels of parallelism which ease the respect of the safety requirements such as the ISO 26262 and the implementation of other automotive use-cases. These new features involve also more complexity in the design, development and verification of the software applications. Hence, OEMs and suppliers will require new tools and methodologies for deployment and validation. In this paper, we review the operating system protection mechanisms (e.g., memory, timing), needed for multi-source software in a safety critical context, with a clear focus on AUTOSAR OS which is the upcoming de-facto standard for automotive ECUs. We then identify the main use cases for multicore ECUs and eventually focus on one of them. Precisely, we address the problem of scheduling numerous elementary software components, called runnables, on a limited set of identical cores. In the context of an automotive design, we assume the use of the static task partitioning scheme which provides simplicity and better predictability for the ECU designers by comparison with a global scheduling approach. We show how the global scheduling problem can be addressed as two sub-problems: partitioning the set of runnables and building the schedule on each core. Then, we prove that each of the sub-problems cannot be solved optimally due to their algorithmic complexity. We then present low complexity heuristics to partition and build a schedule of the runnable set on each core before discussing schedulability verification methods. Finally, we assess the performance of our approach on a case-study