Non-preemptive real-time scheduling of dataflow systems

Real-time signal processing applications can be described naturally with dataflow graphs. The systems we consider have a mix of real-time and non-real-time processing, where independent dataflow graphs represent tasks and individual dataflow actors are subtasks. Rate-monotonic scheduling is optimal for fixed-priority, preemptive scheduling of periodic tasks. Priority inheritance protocols extend rate-monotonic scheduling theory to include tasks that contend for exclusive access to shared resources. We show that non-preemptive rate-monotonic scheduling can be viewed as preemptive scheduling where the processor is explicitly considered a shared resource. We propose a dynamic, real-time execution model inspired by multithreaded dataflow architectures.