Wen-Hung Huang

Schedulability and Optimization Analysis for Non-preemptive Static Priority Scheduling Based on Task Utilization and Blocking Factors

For real time task sets, allowing preemption is often considered to be important to ensure the schedulability, as it allows high-priority tasks to be allocated to the processor nearly immediately. However, preemptive scheduling also introduces some additional overhead and may not be allowed for some hardware components, which motivates the needs of non-preemptive or limited-preemptive scheduling. We present a safe sufficient schedulability test for non-preemptive (NP) fixed priority scheduling that can verify the schedulability for Deadline Monotonic (DM-NP) and Rate Monotonic (RM-NP) scheduling in linear time, if task orders according to priority and period are given. This test leads to a better upper bound on the speedup factor for DM-NP and RM-NP in comparison to Earliest Deadline First (EDF-NP) than previously known, closing the gab between lower and upper bound. We improve our test, resulting in interesting properties of the blocking time that allow to determine schedulability by only considering the schedulability of the preemptive case if some conditions are met. Furthermore, we present a utilization bound for RM-NP, based on the ratio γ > 0 of the upper bound of the maximum blocking time to the execution time, significantly improving previous results.

MIRROR: symmetric timing analysis for real-time tasks on multicore platforms with shared resources

The emergence of multicore and manycore platforms poses a big challenge for the design of real-time embedded systems, especially for timing analysis. We observe in this paper that response-time analysis for multicore platforms with shared resources can be symmetrically approached from two perspectives: a core-centric and a shared-resource-centric perspective. The common “core-centric” perspective is that a task executes on a core until it suspends the execution due to shared resource accesses. The potentially less intuitive “shared-resource-centric” perspective is that a task performs requests on shared resources until suspending itself back to perform computation on its respective core. Based on the above observation, we provide a pseudo-polynomial-time schedulability test and response-time analysis for constrained-deadline sporadic task systems. In addition, we propose a task partitioning algorithm that achieves a speedup factor of 7, compared to the optimal schedule. This constitutes the first result in this research line with a speedup factor guarantee. The experimental evaluation demonstrates that our approach can yield high acceptance ratios if the tasks have only a few resource access segments.

A Unifying Response Time Analysis Framework for Dynamic Self-Suspending Tasks

For real-time embedded systems, self-suspending behaviors can cause substantial performance/schedulability degradations. In this paper, we focus on preemptive fixed-priority scheduling for the dynamic self-suspension task model on uniprocessor. This model assumes that a job of a task can dynamically suspend itself during its execution (for instance, to wait for shared resources or access co-processors or external devices). The total suspension time of a job is upper-bounded, but this dynamic behavior drastically influences the interference generated by this task on lower-priority tasks. The state-of-the-art results for this task model can be classified into three categories (i) modeling suspension as computation, (ii) modeling suspension as release jitter, and (iii) modeling suspension as a blocking term. However, several results associated to the release jitter approach have been recently proven to be erroneous, and the concept of modeling suspension as blocking was never formally proven correct. This paper presents a unifying response time analysis framework for the dynamic self-suspending task model. We provide a rigorous proof and show that the existing analyses pertaining to the three categories mentioned above are analytically dominated by our proposed solution. Therefore, all those techniques are in fact correct, but they are inferior to the proposed response time analysis in this paper. The evaluation results show that our analysis framework can generate huge improvements (an increase of up to 50% of the number of task sets deemed schedulable) over these state-of-the-art analyses.

On the Pitfalls of Resource Augmentation Factors and Utilization Bounds in Real-Time Scheduling.

In this paper, we take a careful look at speedup factors, utilization bounds, and capacity augmentation bounds. These three metrics have been widely adopted in real-time scheduling research as the de facto standard theoretical tools for assessing scheduling algorithms and schedulability tests. Despite that, it is not always clear how researchers and designers should interpret or use these metrics. In studying this area, we found a number of surprising results, and related to them, ways in which the metrics may be misinterpreted or misunderstood. In this paper, we provide a perspective on the use of these metrics, guiding researchers on their meaning and interpretation, and helping to avoid pitfalls in their use. Finally, we propose and demonstrate the use of parametric augmentation functions as a means of providing nuanced information that may be more relevant in practical settings.

Response time bounds for sporadic arbitrary-deadline tasks under global fixed-priority scheduling on multiprocessors

In this paper, we study the problem of scheduling arbitrary-deadline real-time sporadic task sets on a multiprocessor system under global fixed-priority scheduling. Two contributions are made in this paper. First, it has been shown that the existing response time analysis in arbitrary-deadline systems is flawed: the response time may be larger than the derived bound. This paper provides a revised analysis resolving the problems with the original approach, and then propose a corresponding schedulability test. Secondly, we derive a linear-time upper bound on the response time of arbitrary-deadline tasks in multiprocessor systems. To the best of our knowledge, this is the first work presenting a linear-time response time upper bound for arbitrary-deadline sporadic tasks in multiprocessor systems. Empirically, this linear-time response time bound is shown to be highly effective in terms of the number of task sets that are deemed schedulable.

Techniques for Schedulability Analysis in Mode Change Systems under Fixed-Priority Scheduling

With the advent of cyber-physical systems, realtime tasks shall be run in different modes over time to react to the change of the physical environment. It is preferable to adopt high expressive models in real-time systems. In the light of simple implementation in kernels, fixed-priority scheduling has been widely adopted in commercial real-time systems. In this work we derive a technique for analyzing schedulability of the system where tasks can undergo mode change under fixed-priority scheduling. We study two types of fixed-priority scheduling in mode change systems: task-level and mode-level fixed-priority scheduling. The proposed tests run in polynomial time. We further show that a utilization of 2 - √2 ≈ 0.5857 can be guaranteed in implicit-deadline multi-mode systems if each mode is prioritized according to rate-monotonic policy. The effectiveness of the proposed tests is also shown via extensive simulation results.

Resource-Oriented Partitioned Scheduling in Multiprocessor Systems: How to Partition and How to Share?

When concurrent real-time tasks have to access shared resources, to prevent race conditions, the synchronization and resource access must ensure mutual exclusion, e.g., by using semaphores. That is, no two concurrent accesses to one shared resource are in their critical sections at the same time. For uniprocessor systems, the priority ceiling protocol (PCP) has been widely accepted and supported in real-time operating systems. However, it is still arguable whether there exists a preferable approach for resource sharing in multiprocessor systems. In this paper, we show that the proposed resource-oriented partitioned scheduling using PCP combined with a reasonable allocation algorithm can achieve a non-trivial speedup factor guarantee. Specifically, we prove that our task mapping and resource allocation algorithm has a speedup factor 11-6/(m+1) on a platform comprising m processors, where a task may request at most one shared resource and the number of requests on any resource by any single job is at most one. Our empirical investigations show that the proposed algorithm is highly effective in terms of task sets deemed schedulable.

Hybrid self-suspension models in real-time embedded systems

1To tackle the unavoidable self-suspension behavior due to I/O-intensive interactions, multi-core processors, computation offloading systems with coprocessors, etc., the dynamic and the segmented self-suspension sporadic task models have been widely used in the literature. We propose new self-suspension models that are hybrids of the dynamic and the segmented models. Those hybrid models are capable of exploiting knowledge about execution paths, potentially reducing modelling pessimism. In addition, we provide the corresponding schedulability analysis under fixed-relative-deadline (FRD) scheduling and explain how the state-of-the-art FRD scheduling strategy can be applied. Empirically, these hybrid approaches are shown to be effective with regards to the number of schedulable task sets.

Systems with Dynamic Real-Time Guarantees in Uncertain and Faulty Execution Environments

In many practical real-time systems, the physical environment and the system platform can impose uncertain execution behaviour to the system. For example, if transient faults are detected, the execution time of a task instance can be increased due to recovery operations. Such fault recovery routines make the system very vulnerable with respect to meeting hard real-time deadlines. In theory and in practical systems, this problem is often handled by aborting not so important tasks to guarantee the response time of the more important tasks. However, for most systems such faults occur rarely and the results of not so important tasks might still be useful, even if they are a bit late. This implicates to not abort these not so important tasks but keep them running even if faults occur, provided that the more important tasks still meet their hard real time properties. In this paper, we present Systems with Dynamic Real-Time Guarantees to model this behaviour and determine if the system can provide full timing guarantees or limited timing guarantees without any online adaptation after a fault occurred. We present a schedulability test, provide an algorithm for optimal priority assignment, determine the maximum interval length until the system will again provide full timing guarantees and explain how we can monitor the system state online. The approaches presented in this paper can also be applied to mixed criticality systems with dual criticality levels.

State of the art for scheduling and analyzing self-suspending sporadic real-time tasks

In computing systems, a job/process/task/thread may suspend itself when it has to wait for some other internal or external activities, such as computation offloading or memory accesses, to finish before it can continue its execution. In the literature, there are two commonly adopted self-suspending sporadic task models in real-time systems: 1) the dynamic self-suspension model and 2) the segmented self-suspension sporadic task model. A dynamic self-suspending sporadic task is specified with an upper bound on the maximum suspension time for a job (task instance), which allows a job to dynamically suspend itself arbitrary often as long as the suspension time upper bound is not violated. By contrast, a segmented self-suspending sporadic task has a predefined execution and suspension pattern in an interleaving manner. The dynamic self-suspension model is very flexible but inaccurate, whilst the segmented self-suspension model is very restrictive but very accurate. The gap between these two widely-adopted self-suspension task models can be potentially filled by the hybrid self-suspension task model. The investigation of the impact of self-suspension on timing predictability has been started in 1988. This survey paper provides a short summary of the state of the art in the design and analysis of scheduling algorithms and schedulability tests for self-suspending tasks in real-time systems.