| Summary: | The concept of a firm real-time task implies the notion of a firm deadline that should not be missed by the jobs of this task. If a deadline miss occurs, the concerned job yields no value to the system. For some applications domains, this restrictive notion can be relaxed. For example, robust control systems can tolerate that single executions of a control loop miss their deadlines, and still yield an acceptable behaviour. Thus, systems can be developed under more optimistic assumptions, e.g. by allowing overloads. However, care must be taken that deadline misses do not accumulate. This restriction can be expressed by the model of (m,k)-firm real-time tasks that require that from any k consecutive jobs at least m are executed successfully. In this article, we extend our prior work on the MKU scheduling heuristic. MKU uses history-cognisant utility functions as means for making decisions in overload situations. We present new theoretical results on MKU and on other schedulers for (m,k)-firm real-time tasks. Based on extensive simulations, we assess the performance of these schedulers. The results allow us to identify task set characteristics that can be used as guidelines for choosing a scheduler for a concrete use case.
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