Real-time systems are often designed using a set of periodic tasks. Task periods are usually set by the system requirements, but deadlines and computation times can be modified in order to improve system performance. Sensitivity analysis in real-time systems has focused on changes in task computation times using fixed priority analysis. Only a few studies deal with the modification of deadlines in dynamic-priority scheduling. The aim of this work is to provide a sensitivity analysis for task deadlines in the context of dynamic-priority, preemptive, uniprocessor scheduling. In this paper, we present a deadline minimization method that computes the shortest deadline of a periodic task. As undertaken in other studies concerning computation times, we also define and calculate the critical scaling factor for task deadlines. Our proposal is evaluated and compared with other works. The deadline minimization proposed strongly reduces jitter and the response time of control tasks, which can lead to a significant improvement in system performance.

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 reuse 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.

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.

One of the most promising approaches to mixed-criticality systems is the use of multi-core execution platforms based on a hypervisor. Several successful EU Projects are based on this approach and have overcome some of the difficulties that this approach introduces. However, interference in COTS systems due to the use of shared resources in a computer is one of the unsolved problems. In this paper, we attempt to provide realistic solutions to this problem. This paper proposes a feedback control scheme implemented at hypervisor level and transparent to partitions (critical and non-critical). The control scheme defines two controller types. One type of controller is oriented towards limiting the use of shared resources by limiting bus accesses for non-critical cores. A second type measures the activity of a critical core and acts on non-critical cores when performance decreases. The hypervisor uses a performance monitor unit that provides event counters configured and handled by the hypervisor. This paper proposes two control strategies at hypervisor level that can guarantee the execution of critical partitions. Advantages and drawbacks of both strategies are discussed. Control theory requires to identify the process to be controlled. In consequence, the activities of the critical partitions must be identified in order to tune the controller. A methodology to deal with controller tuning is proposed. A set of experiments will show the impact of the controller parameters.