In this paper we present a new algorithm for CPU resource reservation in real-time systems that allows the coexistence of hard, soft and non real-time tasks. The proposed algorithm is specifically designed to handle computational overload. A task that needs more CPU-time than reserved can re-use the spare bandwidth, without interfering with the others tasks. With respect to other reclamation schemes, the novelty of the proposed algorithm is that the spare bandwidth is fairly distributed among the needing servers. The effectiveness of the algorithm is demonstrated with an extensive set of experiments. We also propose a methodology to set scheduling parameters depending on the type of the task and on the time constraints needed.

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In the framework of RT digital control, two fundamental parameters are defined, the control effort and the control action interval. The first one is related to the strength of the control that, due to the intersampling open-loop control, determines the degrading of performances under unexpected delays. The second one refers to the unavoidable delays in the multitasking environment due to interactions among the tasks. As a consequence, the scheduling policy should consider not only the tasks delays but also their influence in the control loop behavior, being calculated to minimize the overall degrading of performances.

In this paper a new task model with periods defined as ranges is proposed with the main goal of drastically reduce the hyperperiod of the task set. The model is focused to be applied in cyclic scheduling, where the length of the major cycle of the plan is determined by the hyperperiod. But it also can be applied in synthetic task sets generation, where having a small hyperperiod reduces complexity and simulation time. A new algorithm, which allows to calculate the minimum hyperperiod of such a set of tasks, is presented. This algorithm calculates the minimum value even with a large number of tasks, where exhaustive search becomes intractable.