Efficient optimal multiprocessor scheduling algorithms for real-time systems

Real-time systems are composed of a set of tasks that must respect some deadlines. We find them in applications as diversified as the telecommunications, medical devices, cars, planes, satellites, military applications, etc. Missing deadlines in a real-time system may cause various results such as a diminution of the quality of service provided by the system, the complete stop of the application or even the death of people. Being able to prove the correct operation of such systems is therefore primordial. This is the goal of the real-time scheduling theory.These last years, we have witnessed a paradigm shift in the computing platform architectures. Uniprocessor platforms have given place to multiprocessor architectures. While the real-time scheduling theory can be considered as being mature for uniprocessor systems, it is still an evolving research field for multiprocessor architectures. One of the main difficulties with multiprocessor platforms, is to provide an optimal scheduling algorithm (i.e., scheduling algorithm that constructs a schedule respecting all the task deadlines for any task set for which a solution exists). Although optimal multiprocessor real-time scheduling algorithms exist, they usually cause an excessive number of task preemptions and migrations during the schedule. These preemptions and migrations cause overheads that must be added to the task execution times. Therefore, task sets that would have been schedulable if preemptions and migrations had no cost, become unschedulable in practice. An efficient scheduling algorithm is therefore an algorithm that either minimize the number of preemptions and migrations, or reduce their cost.In this dissertation, we expose the following results:- We show that reducing the "fairness" in the schedule, advantageously impacts the number of preemptions and migrations. Hence, all the scheduling algorithms that will be proposed in this thesis, tend to reduce or even suppress the fairness in the computed schedule. - We propose three new online scheduling algorithms. One of them --- namely, BF2 --- is optimal for the scheduling of sporadic tasks in discrete-time environments, and reduces the number of task preemptions and migrations in comparison with the state-of-the-art in discrete-time systems. The second one is optimal for the scheduling of periodic tasks in a continuous-time environment. Because this second algorithm is based on a semi-partitioned scheme, it should favorably impact the preemption overheads. The third algorithm --- named U-EDF --- is optimal for the scheduling of sporadic and dynamic task sets in a continuous-time environment. It is the first real-time scheduling algorithm which is not based on the notion of "fairness" and nevertheless remains optimal for the scheduling of sporadic (and dynamic) systems. This important result was achieved by extending the uniprocessor algorithm EDF to the multiprocessor scheduling problem. - Because the coding techniques are also evolving as the degree of parallelism increases in computing platforms, we provide solutions enabling the scheduling of parallel tasks with the currently existing scheduling algorithms, which were initially designed for the scheduling of sequential independent tasks.