Abstract-This article studies the scheduling of critical embedded systems, which consist of a set of communicating periodic tasks with constrained deadlines. Currently, tasks are usually sequenced manually, partly because available scheduling policies do not ensure the determinism of task communications. Ensuring this determinism requires scheduling policies supporting task precedence constraints (which we call dependent tasks), which are used to force the order in which communicating tasks execute. We propose fixed priority scheduling policies for different classes of dependent tasks: with simultaneous or arbitrary release times, with simple precedences (between tasks of the same period) or extended precedences (between tasks of different periods). We only consider policies that do not require synchronization mechanisms (like semaphores). This completely prevents deadlocks or scheduling anomalies without requiring further proofs.
This paper gives and proves correct a simulation interval for any schedule generated by a deterministic and memoryless scheduler (i.e., one where the scheduling decision is the same and unique for any two identical system states) for identical multiprocessor platforms. We first consider independent periodic tasks, then generalize the simulation interval to tasks sharing critical resources, and subject to precedence constraints or self-suspension. The simulation interval is based only on the periods, release times and deadlines, and is independent from any other parameters. It is proved large enough to cover any feasible schedule produced by any deterministic and memoryless scheduler on multiprocessor platforms, including non conservative schedulers. To the best of our knowledge, this simulation interval covers the largest class of tasks systems and scheduling algorithms on identical multiprocessor platforms ever studied. This simulation interval is used to derive a simulation algorithm using a linear space complexity. Finally, a generic exact schedulability test based on simulation is presented. This test can be applied only when sustainability is consistent with online variability of the tasks' parameters.
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