Scalable real-time system design using preemption thresholds

• Authors: Manas Saksena;Yun Wang
• Venue: RTSS'10 Proceedings of the 21st IEEE conference on Real-time systems symposium
• Year: 2000

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 scales well even when the design consists of a large number of concurrent jobs. The approach avoids any unnecessary preemptability in the system, thereby resulting in reduced run-time overheads from preemptions and associated context-switches. It also allows significant memory savings by grouping jobs into non-preemptive groups and then sharing the stack space between them. Our approach is based on our earlier work on scheduling using preemption thresholds that allows parametric control over preemptability in a priority based system. 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.