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Partly Proportionate fair (Partly-Pfair) scheduling, which allows task migration at runtime and assigns each task processing time with regard to its weight, makes it possible to build highly efficient embedded multi-core systems. Due to its non-work-conserving behavior, which might leave the CPU idle even when tasks are ready to execute, tasks finish only shortly before their deadlines are reached. Benefits are lower task jitter, but additional workload, e.g. through interrupts, can lead to deadline violations. In this paper we present a work-conserving extension of Partly-Pfair scheduling, called PERfair scheduling and the algorithm P-ERfair-PD2 which applies Pfair modifications used for Partly-Pfair on the concept of ERfairness and PD2 policies. With a simulation based schedulability examination we show for multiple time base (MTB) task sets that P-ERfair- PD2 has the same performance as Partly-Pfair-PD2. Additionally, we show that P-ERfair- PD2 has a much higher robustness against perturbations, and therefore it is well suited for embedded domains, especially for the Automotive domain.
Proportionate fair (Pfair) scheduling, which allows task migration at runtime and assigns each task processing time with regard to its weight, is one of the most efficient group of SMP multiprocessor scheduling algorithms known up to now. Drawbacks are tight requirements to the task system, namely the restriction to periodic task systems with synchronized task activation, quantized task execution time, and implicit task deadline. Most likely, a typical embedded real-time system does not fulfill these requirements. In this paper we address violations of these requirements. For heterogeneous task systems, we define the multiple time base (MTB) task system, which is a less pessimistic model than sporadic task systems and is used for automotive systems. We apply the concept of Pfair scheduling to MTB task systems, called partly proportionate fair (Partly-Pfair) scheduling. The restrictions on MTB task systems required for Partly-Pfair ness are weaker than restrictions on periodic task systems required for Pfair ness. In a simulation based study we examined the performance of Partly-Pfair-PD and found it capable to schedule feasible MTB task sets causing a load of up to 100% of the system capacity.