Value Based Overload Handling of Aperiodic Tasks in Offline Scheduled Real-Time Systems

This paper describes a runtime scheduling method for a mix of off-line scheduled and value based dynamic tasks with a focus on overload situations. We present a formulation of overload handling as a general binary optimisation problem and give an algorithm for solving it. Our method is based on slot shifting [4] to provide for the integration of offline and online scheduling. Dynamic tasks are scheduled according to basic EDF, extended with an algorithm for overload detection and resolution. We include a penalty value for tasks which have been guaranteed but missed their deadline, e.g., due to rejection under overload. The mixed taskset enables designers to choose a tradeoff between predictability and flexibility for each activity in the system individually and to guarantee predictable execution of offline tasks even under overload situations. The algorithm ensures that overload situations are handled efficiently with respect to the values of the dynamic tasks. [3], [2], [8], and [7] discuss overload handling based on earliest deadline first scheduling. [1] presents scheduling scheme calculating priorities dynamically based on value and deadlines. These focus on online scheduling. Our method handles overload situations while guaranteeing the feasible execution of offline scheduled tasks.

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