Handling mixed sets of tasks in combined offline and online scheduled real-time systems

Abstract

Many industrial applications with real-time demands are composed of mixed sets of tasks with a variety of requirements. These can be in the form of standard timing constraints, such as period and deadline, or complex, e.g., to express application specific or nontemporal constraints, reliability, performance, etc. As many algorithms focus on specific sets of task types and constraints only, system design has to focus on those supported by a particular algorithm, at the expense of the rest. In this paper, we present a method to deal with a combination of mixed sets of tasks and constraints: periodic tasks with complex and simple constraints, soft and firm aperiodic, and sporadic tasks. We propose the use of an offline scheduler to manage complex timing and resource constraints of periodic tasks and transform these into a simple EDF model with start-times and deadlines. At run-time, the execution of the offline scheduled tasks is flexibly shifted in order to allow for feasible inclusion of dynamically arriving sporadic and aperiodic tasks. Sporadic tasks are guaranteed offline based on their worst-case activation frequencies. At run-time, this pessimism is reduced by the online algorithm which uses the exact knowledge about sporadic arrivals to reclaim resources and improve response times and acceptance of firm aperiodic tasks.