The Non-preemptive Scheduling of Periodic Tasks upon Multiprocessors

The non-preemptive scheduling of periodic task systems upon processing platforms comprised of several identical processors is considered. The exact problem has previously been proven intractable even upon single processors; sufficient conditions are presented here for determining whether a given periodic task system will meet all deadlines if scheduled non-preemptively upon a multiprocessor platform using the earliest-deadline first scheduling algorithm

A Rapid Heuristic for Scheduling Non-Preemptive Dependent Periodic Tasks onto Multiprocessor

International audienceWe address distributed real-time applications represented by systems of non-preemptive dependent periodic tasks. This system is described by an acyclic directed graph. Because the distribution and the scheduling of these tasks onto a multiprocessor is an NP-hard problem we propose a greedy heuristic to solve it. Our heuristic sequences three algorithms: assignment, unrolling, and scheduling. The tasks of the same, or multiple, periods are assigned to the same processor according to a mixed sort. Then, the initial graph of tasks is unrolled, i.e. each task is repeated according to the ratio between its period and the least common multiple of all periods of tasks. Finally, the tasks of the unrolled graph are distributed and scheduled onto the processors where they have been assigned. Then, we give the complexity of this heuristic, and we illustrate it with an example. A performance analysis comparing our heuristic with an optimal Branch and Cut algorithm concludes that our heuristic is effective in terms of scheduling success ratio and speed

Job-shop Scheduling Over a Heterogeneous Platform

Real-time scheduling involves determining the allocation of platform resources in such a way tasks can meet their temporal restrictions. This work focuses on job-shop tasks model in which a task have a finite number of nonpreemptive different instances (jobs) that share a unique hard deadline and their time requirements are known until task arrival. Non-preemptive scheduling is considered because this characteristic is widely used in industry. Besides job-shop scheduling has direct impacts on the production efficiency and costs of manufacturing systems. So that the development of analysis for tasks with these characteristics is necessary. The aim of this work is to propose an online scheduling test able to guarantee the execution of a new arriving task, which is generated by human interaction with an embedded system, otherwise to discart it. An extension of the schedulability test proposed by Baruah in 2006 for non-preemptive periodic tasks over an identical platform is presented in this paper. Such extension is applied to non-preemptive tasks that have hard deadlines over a heterogeneous platform. To do that, some virtual changes over both the task set and the platform are effectuated

A UNIFIED HARDWARE/SOFTWARE PRIORITY SCHEDULING MODEL FOR GENERAL PURPOSE SYSTEMS

Migrating functionality from software to hardware has historically held the promise of enhancing performance through exploiting the inherent parallel nature of hardware. Many early exploratory efforts in repartitioning traditional software based services into hardware were hampered by expensive ASIC development costs. Recent advancements in FPGA technology have made it more economically feasible to explore migrating functionality across the hardware/software boundary. The flexibility of the FPGA fabric and availability of configurable soft IP components has opened the potential to rapidly and economically investigate different hardware/software partitions. Within the real time operating systems community, there has been continued interest in applying hardware/software co-design approaches to address scheduling issues such as latency and jitter. Many hardware based approaches have been reported to reduce the latency of computing the scheduling decision function itself. However continued adherence to classic scheduler invocation mechanisms can still allow variable latencies to creep into the time taken to make the scheduling decision, and ultimately into application timelines. This dissertation explores how hardware/software co-design can be applied past the scheduling decision itself to also reduce the non-predictable delays associated with interrupts and timers. By expanding the window of hardware/software co-design to these invocation mechanisms, we seek to understand if the jitter introduced by classical hardware/software partitionings can be removed from the timelines of critical real time user processes. This dissertation makes a case for resetting the classic boundaries of software thread level scheduling, software timers, hardware timers and interrupts. We show that reworking the boundaries of the scheduling invocation mechanisms helps to rectify the current imbalance of traditional hardware invocation mechanisms (timers and interrupts) and software scheduling policy (operating system scheduler). We re-factor these mechanisms into a unified hardware software priority scheduling model to facilitate improvements in performance, timeliness and determinism in all domains of computing. This dissertation demonstrates and prototypes the creation of a new framework that effects this basic policy change. The advantage of this approach lies within it's ability to unify, simplify and allow for more control within the operating systems scheduling policy

Using Imprecise Computing for Improved Real-Time Scheduling

Conventional hard real-time scheduling is often overly pessimistic due to the worst case execution time estimation. The pessimism can be mitigated by exploiting imprecise computing in applications where occasional small errors are acceptable. This leverage is investigated in a few previous works, which are restricted to preemptive cases. We study how to make use of imprecise computing in uniprocessor non-preemptive real-time scheduling, which is known to be more difficult than its preemptive counterpart. Several heuristic algorithms are developed for periodic tasks with independent or cumulative errors due to imprecision. Simulation results show that the proposed techniques can significantly improve task schedulability and achieve desired accuracy– schedulability tradeoff. The benefit of considering imprecise computing is further confirmed by a prototyping implementation in Linux system. Mixed-criticality system is a popular model for reducing pessimism in real-time scheduling while providing guarantee for critical tasks in presence of unexpected overrun. However, it is controversial due to some drawbacks. First, all low-criticality tasks are dropped in high-criticality mode, although they are still needed. Second, a single high-criticality job overrun leads to the pessimistic high-criticality mode for all high-criticality tasks and consequently resource utilization becomes inefficient. We attempt to tackle aforementioned two limitations of mixed-criticality system simultaneously in multiprocessor scheduling, while those two issues are mostly focused on uniprocessor scheduling in several recent works. We study how to achieve graceful degradation of low-criticality tasks by continuing their executions with imprecise computing or even precise computing if there is sufficient utilization slack. Schedulability conditions under this Variable-Precision Mixed-Criticality (VPMC) system model are investigated for partitioned scheduling and global fpEDF-VD scheduling. And a deferred switching protocol is introduced so that the chance of switching to high-criticality mode is significantly reduced. Moreover, we develop a precision optimization approach that maximizes precise computing of low-criticality tasks through 0-1 knapsack formulation. Experiments are performed through both software simulations and Linux proto- typing with consideration of overhead. Schedulability of the proposed methods is studied so that the Quality-of-Service for low-criticality tasks is improved with guarantee of satisfying all deadline constraints. The proposed precision optimization can largely reduce computing errors compared to constantly executing low-criticality tasks with imprecise computing in high-criticality mode

Tardiness bounds under global EDF scheduling on a multiprocessor

We consider the scheduling of a sporadic real-time task system on an identical multiprocessor. Though Pfair algorithms are theoretically optimal for such task systems, in practice, their runtime overheads can significantly reduce the amount of useful work that is accomplished. On the other hand, if all deadlines need to be met, then every known non-Pfair algorithm requires restrictions on total system utilization that can approach approximately 50% of the available processing capacity. This may be overkill for soft real-time systems, which can tolerate occasional or bounded deadline misses (i.e., bounded tardiness). In this paper we derive tardiness bounds under preemptive and non-preemptive global EDF when the total system utilization is not restricted, except that it not exceed the available processing capacity. Hence, processor utilization can be improved for soft real-time systems on multiprocessors. Our tardiness bounds depend on the total system utilization and per-task utilizations and execution costs — the lower these values, the lower the tardiness bounds. As a final remark, we note that global EDF may be superior to partitioned EDF for multiprocessor-based soft real-time systems in that the latter does not offer any scope to improve system utilization even if bounded tardiness can be tolerated