Scalable Real-Time System Design using Preemption Thresholds

The maturity of schedulabilty analysis techniques for fixed-priority preemptive scheduling has enabled the consideration of timing issues at design time using a specification of the tasking architecture and estimates of execution times for tasks. While successful, this approach has limitations since the preemptive multi-tasking model does not scale well for a large number of tasks, and the fixed priority scheduling theory does not work well with many object-oriented design methods. In this paper we present an approach that uses a scalable implementation architecture where design level tasks are grouped into a smaller number of run-time threads during implementation. The schedulability analysis for this implementation architecture is based on the preemption threshold scheduling model. We show that our approach provides significant advantages over one using fixed-priority preemptive scheduling architecture. The benefits include higher schedulability for small number of tasks, and lower run-time overheads, and hence better scalability. We develop algorithms that allow design time consideration of schedulability, and automatic synthesis of an implementation model to minimize run-time overheads.