Statistical quality analysis of schedulers under soft-real-time constraints

Abstract

This paper describes an algorithm to determine the performance of real-time systems with tasks using stochastic processing times. Such an algorithm can be used for guaranteeing Quality of Service of periodic tasks with soft real-time constraints. We use a discrete distribution model of processing times instead of worst case times like in hard real-time systems. Such a model gives a more realistic view on the actual requirements of the system. The presented algorithm works for all deterministic scheduling systems, which makes it more general than existing 6algorithms and allows us to compare performance between these systems. To demonstrate our method, we make a comparison between the performance of the well known scheduling algorithms Earliest Deadline First and Rate Monotonic. We show that the complexity of our method can compete with other algorithms that work for a wide range of schedulers