International audienceIn this paper, we study the problem of real-time scheduling of parallel tasks represented by a Directed Acyclic Graph (DAG) on multiprocessor architectures. We focus on Global Earliest Deadline First scheduling of sporadic DAG tasksets with constrained-deadlines on a system of homogeneous processors. Our contributions consist in analyzing DAG tasks by considering their internal structures and providing a tighter bound on the workload and interference analysis. This approach consists in assigning a local offset and deadline for each subtask in the DAG. We derive an improved sufficient schedulability test w.r.t. an existing test proposed in the state of the art. Then we discuss the sustainability of this test

In this paper, we focus on the scheduling of periodic fork-join real-time tasks on multiprocessor systems. Parallel real-time tasks in the fork-join model have strict parallel segments without laxity. We propose a partitioned scheduling algorithm which increases the laxity of the parallel segments and therefore the schedulability of tasksets of this model. A similar algorithm has been proposed in the literature but it produces job migrations. Our algorithm eliminates the use of job migrations in order to create a portable algorithm that can be implemented on a standard Linux kernel. Results of extensive simulations are provided in order to analyze the schedulability of the proposed algorithm, and to provide comparisons with the other algorithm proposed in the literature.

International audienceParallelism is becoming more important nowadays due to the increasing use of multiprocessor systems. In this paper, we study the problem of scheduling periodic parallel real-time Directed Acyclic graph (DAG) tasks on m homogeneous multiprocessor systems. A DAG task is an example of inter-subtask parallelism. It consists of a collection of dependent subtasks under precedence constraints. The dependencies between subtasks make scheduling process more challenging. We propose a stretching algorithm applied on each DAG tasks to transform them into a set of independent sequential threads with intermediate offsets and deadlines. The threads obtained with the transformation are two types, (i) fully-stretched master threads with utilization equal to 1 and (ii) constrained-deadline independent threads. The fully-stretched master threads are assigned to dedicated processors and the remaining processors m' ≤ m, are scheduled using global EDF scheduling algorithm. Then, we prove that preemptive global EDF scheduling of stretched threads has a resource augmentation bound equal to (3+ √ 5)/2 for all tasksets with n < ϕ * m , where n is the number of tasks in the taskset and ϕ is the golden ratio 1

The new generation of embedded systems will have the capability to harvest energy from the environment. The electrical energy which is available to power these devices changes over time and is limited by the size of the energy storage unit such as battery or capacitor and the size of the harvester such as a solar panel. In order to cope with this limitation, the system has to dynamically decide when to be active and when to sleep in order to provide the best quality of service without wasting the harvested energy. In this paper, we study this problem for a uniprocessor architecture where periodic tasks have to execute with deadline constraints according to a preemptive fixed priority rule. We evaluate and compare several scheduling approaches by means of simulation.

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We address in this paper the problem of jointly scheduling hard periodic tasks and soft aperiodic events using the Real-Time Specification for Java (RTSJ). We present the programming constraints of RTSJ and propose slack time evaluation and utilization algorithms which take these constraints into account. We evaluate these algorithms and compare their performances with the Background Scheduling (BS) through simulations.

This paper considers the problem of non-preemptive hard realtime scheduling of sporadic task graphs on a uniprocessor with Earliest Deadline First (EDF) scheduling. A sporadic task graph associated to an application is characterized by a set of subtasks under precedence constraints with deadline constraints. We study feasibility conditions based on the computation of the worst case response times of any subtask of a task graph. We investigate the late deadline constraint.

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