Handling Sporadic Tasks in Real-time Systems - Combined Offline and Online Approach -

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 non temporal constraints, reliability, performance, etc. Arrival patterns determine whether tasks will be treated as periodic, sporadic, or aperiodic. 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 work, we present a set of algorithms to deal with a combination of mixed sets of tasks and constraints: periodic tasks with complex and simple constraints, soft and firm aperiodic, and in particular sporadic tasks. Instead of providing algorithms tailored for a specific set of constraints, we propose an EDF based runtime algorithm, and the use of an offline scheduler for complexity reduction to transform complex constraints into the EDF model. At runtime, an extension to EDF, two level EDF, ensures feasible execution of tasks with complex constraints in the presence of additional tasks or overloads. We present a combined offline and online approach for handling sporadic tasks. First, the sporadic tasks are guaranteed offline, during design time, which allows rescheduling or redesign in the case of failure. Since we do not know the arrival time of sporadics we need to perform the worst-case offline guarantee. Second, we try online to reduce the pessimism intoduced by worstcase assumption. An online algorithm keeps track of arrivals of instances of sporadic tasks to reduce pessimism about future sporadic arrivals and improve response times and acceptance of firm aperiodic tasks. A simulation study underlines the effectiveness of the proposed approach.