Non-preemptive Fixed Priority Scheduling Research Articles

A framework for multi-core schedulability analysis accounting for resource stress and sensitivity

Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution.

Optimizing Energy in Non-Preemptive Mixed-Criticality Scheduling by Exploiting Probabilistic Information

The strict requirements on the timing correctness biased the modeling and analysis of real-time systems toward the worst-case performances. Such focus on the worst-case, however, does not provide enough information to effectively steer the resource/energy optimization. In this article, we integrate a probabilistic-based energy prediction strategy with the precise scheduling of mixed-criticality tasks, where the timing correctness must be met for all tasks at all scenarios. The dynamic voltage and frequency scaling (DVFS) is applied to this precise scheduling policy to enable energy minimization. We propose a probabilistic technique to derive an energy-efficient speed (for the processor) that minimizes the average energy consumption, while guaranteeing the (worst-case) timing correctness for all tasks, including LO-criticality ones, under any execution condition. We present a response time analysis for such systems under the nonpreemptive fixed-priority scheduling policy. Finally, we conduct an extensive simulation campaign based on randomly generated task sets to verify the effectiveness of our algorithm (with respect to energy savings) and it reports up to 46% energy-saving.

Speeding Up the Schedulability Analysis and Priority Assignment of Sporadic Tasks Under Uniprocessor FPNS

Fixed-priority non-preemptive scheduling (FPNS) is widely used in practice because of its simplicity and predictability. This article aims to enhance the efficiency of the schedulability analysis and priority assignment of sporadic tasks under uniprocessor FPNS. To speed-up the schedulability analysis, we first improve the state-of-the-art worst-case response time analysis for uniprocessor fixed-priority non-preemptive scheduling. In addition, we present two special conditions under which the worst-case response time of a task can be analyzed from its first job, which further improves the efficiency of the analysis. To accelerate the priority assignment, we present two priority-assignment algorithms based on the improved Audsley's algorithm: improved Audsley-based longest deadline first (IA-LDF) and improved Audsley-based longest worst-case execution time first (IA-LCF). The numerical experiments show that IA-LDF and IA-LCF can lead to 31.2% and 36% decrease in runtime compared to longest deadline first (LDF) and longest worst-case execution time first (LCF), respectively.

Improved Schedulability Test for Non-Preemptive Fixed-Priority Scheduling on Multiprocessors

Non-preemptive scheduling is essential to tasks that inherently disallow any preemption and useful for tasks that exhibit extremely large preemption/migration overhead; however, studies of non-preemptive scheduling have not matured for real-time tasks subject to timing constraints. In this letter, we propose an improved schedulability test for non-preemptive fixed-priority scheduling (NP-FP), which offers timing guarantees for a set of real-time tasks executed on a multiprocessor platform. To this end, we first carefully investigate the NP-FP properties, and present an observation why the existing technique is pessimistic in calculating interference from higher-priority tasks. We then develop a new technique that tightly upper bounds the amount of the interference, and show how to incorporate the technique into the existing schedulability test. Via simulations, we demonstrate that our proposed test improves schedulability performance of NP-FP up to 18%, compared with the state-of-the-art existing tests.

Optimal priority and threshold assignment for fixed-priority preemption threshold scheduling

Fixed-priority preemption-threshold scheduling (FPTS) is a generalization of fixed-priority preemptive scheduling (FPPS) and fixed-priority non-preemptive scheduling (FPNS). Since FPPS and FPNS are incomparable in terms of potential schedulability, FPTS has the advantage that it can schedule any task set schedulable by FPPS or FPNS and some that are not schedulable by either. FPTS is based on the idea that each task is assigned a priority and a preemption threshold. While tasks are admitted into the system according to their priorities, they can only be preempted by tasks that have priority higher than the preemption threshold. This paper presents a new optimal priority and preemption threshold assignment (OPTA) algorithm for FPTS which in general outperforms the existing algorithms in terms of the size of the explored state-space and the total number of worst case response time calculations performed. The algorithm is based on back-tracking, i.e. it traverses the space of potential priorities and preemption thresholds, while pruning infeasible paths, and returns the first assignment deemed schedulable. We present the evaluation results where we compare the complexity of the new algorithm with the existing one. We show that the new algorithm significantly reduces the time needed to find a solution. Through a comparative evaluation, we show the improvements that can be achieved in terms of schedulability ratio by our OPTA compared to a deadline monotonic priority assignment.

Exact speedup factors and sub-optimality for non-preemptive scheduling

Fixed priority scheduling is used in many real-time systems; however, both preemptive and non-preemptive variants (FP-P and FP-NP) are known to be sub-optimal when compared to an optimal uniprocessor scheduling algorithm such as preemptive earliest deadline first (EDF-P). In this paper, we investigate the sub-optimality of fixed priority non-preemptive scheduling. Specifically, we derive the exact processor speed-up factor required to guarantee the feasibility under FP-NP (i.e. schedulability assuming an optimal priority assignment) of any task set that is feasible under EDF-P. As a consequence of this work, we also derive a lower bound on the sub-optimality of non-preemptive EDF (EDF-NP). As this lower bound matches a recently published upper bound for the same quantity, it closes the exact sub-optimality for EDF-NP. It is known that neither preemptive, nor non-preemptive fixed priority scheduling dominates the other, in other words, there are task sets that are feasible on a processor of unit speed under FP-P that are not feasible under FP-NP and vice-versa. Hence comparing these two algorithms, there are non-trivial speedup factors in both directions. We derive the exact speed-up factor required to guarantee the FP-NP feasibility of any FP-P feasible task set. Further, we derive the exact speed-up factor required to guarantee FP-P feasibility of any constrained-deadline FP-NP feasible task set.

Exact speedup factors for linear-time schedulability tests for fixed-priority preemptive and non-preemptive scheduling

In this paper, we investigate the quality of several linear-time schedulability tests for preemptive and non-preemptive fixed-priority scheduling of uniprocessor systems. The metric used to assess the quality of these tests is the resource augmentation bound commonly known as the processor speedup factor. The speedup factor of a schedulability test corresponds to the smallest factor by which the processing speed of a uniprocessor needs to be increased such that any task set that is feasible under an optimal preemptive (non-preemptive) work-conserving scheduling algorithm is guaranteed to be schedulable with preemptive (non-preemptive) fixed priority scheduling if this scheduling test is used, assuming an appropriate priority assignment. We show the surprising result that the exact speedup factors for Deadline Monotonic (DM) priority assignment combined with sufficient linear-time schedulability tests for implicit-, constrained-, and arbitrary-deadline task sets are the same as those obtained for optimal priority assignment policies combined with exact schedulability tests. Thus in terms of the speedup-factors required, there is no penalty in using DM priority assignment and simple linear schedulability tests.

A Note on the Suboptimality of Nonpreemptive Real-time Scheduling

In this letter, processor speedup analysis is used to strengthen recent results regarding the suboptimality of uniprocessor nonpreemptive earliest deadline first (npEDF) scheduling. The suboptimality of npEDF is defined as the minimum amount of increase in the processor speed that is needed to guarantee the npEDF schedulability of any feasible task set. We show that any preemptively schedulable task set that is not schedulable by npEDF will become schedulable on a processor speeded up by a factor of not more than one plus the value of the largest execution requirement divided by the shortest relative deadline of any task. This reduces the pessimism compared to the best previous bound by factor of at least two. In addition, for the case of nonpreemptive Fixed Priority scheduling, we also show that twice this speedup bound is enough to guarantee the schedulability of any feasible task set.

Global and Partitioned Multiprocessor Fixed Priority Scheduling with Deferred Preemption

This article introduces schedulability analysis for Global Fixed Priority Scheduling with Deferred Preemption (gFPDS) for homogeneous multiprocessor systems. gFPDS is a superset of Global Fixed Priority Preemptive Scheduling (gFPPS) and Global Fixed Priority Nonpreemptive Scheduling (gFPNS). We show how schedulability can be improved using gFPDS via appropriate choice of priority assignment and final nonpreemptive region lengths, and provide algorithms that optimize schedulability in this way. Via an experimental evaluation we compare the performance of multiprocessor scheduling using global approaches: gFPDS, gFPPS, and gFPNS, and also partitioned approaches employing FPDS, FPPS, and FPNS on each processor.

Schedulability analysis for non-preemptive fixed-priority multiprocessor scheduling

Non-preemptive scheduling is usually considered inferior to preemptive scheduling for time critical systems, because the non-preemptive block would lead to poor task responsiveness. Although this is true in single-processor scheduling, we found by empirical simulation experiments that it is not necessarily the case in multiprocessor scheduling. Additionally, non-preemptive scheduling enjoys other benefits like lower implementation complexity and run-time overhead. So non-preemptive scheduling may be a better alternative compared to preemptive scheduling for a considerable part of real-time applications on multiprocessor/multi-core platforms. As the technical contribution, we study the schedulability analysis problem of global non-preemptive fixed-priority scheduling ( NP-FP ) on multiprocessors. We propose schedulability test conditions for NP-FP , building upon the “problem window analysis” by Baruah [8] for preemptive scheduling. We firstly derive a linear-time general schedulability test condition that works on not only NP-FP , but also any other work-conserving non-preemptive scheduling algorithm. Then we improve the analysis and present a test condition of quadratic time-complexity for NP-FP , which has significant performance improvement comparing to the first one. A notable advantage of our proposed test conditions is, while the test in [8] needs to enumerate for a large number of possible problem window sizes, our proposed test conditions only need to be conducted with a single problem window size, and thereby are significantly more efficient. Experiments with randomly generated task sets are conducted to evaluate the performance of the proposed test conditions.

Utilization Bound of Non-preemptive Fixed Priority Schedulers

It is known that the schedulability of a non-preemptive task set with fixed priority can be determined in pseudo-polynomial time. However, since Rate Monotonic scheduling is not optimal for non-preemptive scheduling, the applicability of existing polynomial time tests that provide sufficient schedulability conditions, such as Liu and Layland's bound, is limited. This letter proposes a new sufficient condition for non-preemptive fixed priority scheduling that can be used for any fixed priority assignment scheme. It is also shown that the proposed schedulability test has a tighter utilization bound than existing test methods.