Multiframe Task Research Articles

Response time analysis of memory-bandwidth-regulated multiframe mixed-criticality systems

The multiframe mixed-criticality task model eliminates the pessimism in many systems where the worst-case execution times (WCETs) of successive jobs vary greatly by design, in a known pattern. Existing feasibility analysis techniques for multiframe mixed-criticality tasks are shared-resource-oblivious, hence unsafe for commercial-off-the-shelf (COTS) multicore platforms with a memory controller shared among all cores. Conversely, the feasibility analyses that account for the interference on shared resource(s) in COTS platforms do not leverage the WCET variation in multiframe tasks. This paper extends the state-of-the-art by presenting an analysis that incorporates the memory access stall in memory-bandwidth-regulated multiframe mixed-criticality multicore systems. An exhaustive enumeration approach is proposed for this analysis to further enhance the schedulability success ratio. The running time of the exhaustive analysis is improved by proposing a pruning mechanism that eliminates the combinations of interfering job sequences that subsume others. Experimental evaluation, using synthetic task sets, demonstrates up to 72% improvement in terms of schedulability success ratio, compared to frame-agnostic analysis.

Response time analysis of multiframe mixed-criticality systems with arbitrary deadlines

The well-known model of Vestal aims to avoid excessive pessimism in the quantification of the processing requirements of mixed-criticality systems, while still guaranteeing the timeliness of higher-criticality functions. This can bring important savings in system costs, and indirectly help meet size, weight and power constraints. This efficiency is promoted via the use of multiple worst-case execution time (WCET) estimates for the same task, with each such estimate characterized by a confidence associated with a different criticality level. However, even this approach can be very pessimistic when the WCET of successive instances of the same task can vary greatly according to a known pattern, as in MP3 and MPEG codecs or the processing of ADVB video streams. In this paper, we present a schedulability analysis for the new multiframe mixed-criticality model, which allows tasks to have multiple, periodically repeating, WCETs in the same mode of operation. Our work extends both the analysis techniques for Static Mixed-Criticality scheduling (SMC) and Adaptive Mixed-Criticality scheduling (AMC), on one hand, and the schedulability analysis for multiframe task systems on the other. A constrained-deadline model is initially targeted, and then extended to the more general, but also more complex, arbitrary-deadline scenario. The corresponding optimal priority assignment for our schedulability analysis is also identified. Our proposed worst-case response time (WCRT) analysis for multiframe mixed-criticality systems is considerably less pessimistic than applying the static and adaptive mixed-criticality scheduling tests oblivious to the WCET variation patterns. Experimental evaluation with synthetic task sets demonstrates up to 20% and 31.4% higher scheduling success ratio (in absolute terms) for constrained-deadline analyses and arbitrary-deadline analyses, respectively, when compared to the best of their corresponding frame-oblivious tests.

Real-time semi-partitioned scheduling of fork-join tasks using work-stealing

This paper extends the work presented in Maia et al. (Semi-partitioned scheduling of fork-join tasks using work-stealing, 2015) where we address the semi-partitioned scheduling of real-time fork-join tasks on multicore platforms. The proposed approach consists of two phases: an offline phase where we adopt a multi-frame task model to perform the task-to-core mapping so as to improve the schedulability and the performance of the system and an online phase where we use the work-stealing algorithm to exploit tasks’ parallelism among cores with the aim of improving the system responsiveness. The objective of this work is twofold: (1) to provide an alternative scheduling technique that takes advantage of the semi-partitioned properties to accommodate fork-join tasks that cannot be scheduled in any pure partitioned environment and (2) to reduce the migration overheads which has been shown to be a traditional major source of non-determinism for global scheduling approaches. In this paper, we consider different allocation heuristics and we evaluate the behavior of two of them when they are integrated within our approach. The simulation results show an improvement up to 15% of the proposed heuristic over the state-of-the-art in terms of the average response time per task set.

Parameter adaptation for generalized multiframe tasks: schedulability analysis, case study, and applications to self-suspending tasks

The generalized multiframe task model (GMF) extends the sporadic task model and multiframe task model. Each frame in the GMF model contains an execution time, a relative deadline, and a minimum inter-arrival time. These parameters are fixed after task specification time in the GMF model. However, multimedia and adaptive control systems may be overloaded and no longer stabilized when the task parameters in such systems are not flexible. In order to address this problem, deadlines and periods of frames may change to alleviate temporal overload, e.g., in the parameter adaptation and elastic scheduling model. In this paper, we propose a new model GMF-PA (the GMF model with parameter adaptation). This model allows task parameters to be flexible in arbitrary-deadline systems. A necessary schedulability test based on mixed-integer linear programming is given to check the schedulability under EDF scheduling and optimally assign frame deadlines and periods at the same time. We also prove that the test is a sufficient and necessary schedulability test when frame deadlines and periods must be integers. An approximation algorithm is also deployed to reduce computational running time and indicates a sufficient schedulability test in general. The speed-up factor of our approximation algorithm is $$1+\epsilon $$ where $$\epsilon $$ can be arbitrarily small, with respect to the exact schedulability test of GMF-PA tasks under EDF. We also apply the GMF model to self-suspending tasks. By extending recent work on scheduling self-suspending tasks, we remove the assumption that frame deadlines are equally assigned in self-suspending tasks, and the system is extended from constrained-deadline systems to arbitrary-deadline systems. We have done extensive experiments to show that the schedulability ratio is improved using our techniques in our GMF-PA model.

An optimal resource sharing protocol for generalized multiframe tasks

Many different task models of varying expressiveness have been proposed to capture the timing constraints of real-time workloads. However, techniques for optimal scheduling and exact feasibility analysis of systems with mutually-exclusive shared resources have been available only for relatively simple task models, such as the sporadic task model. We consider sharing of mutually-exclusive resources in task models that are more expressive in terms of the job-release patterns that can be modeled. We propose a new scheduling algorithm and show that it is optimal for scheduling generalized multiframe tasks with shared resources on uniprocessor systems. We also present an efficient feasibility test for such systems, and show that it is both sufficient and necessary.

Task Optimization Scheduling Algorithm in Embedded System Based on Internet of Things

Embedded system has been widely used in the network, server, etc., and it has a good application prospect with the development of Internet of things. In the embedded heterogeneous computing system, task scheduling is the key to deciding the system performance. For multi-task scheduling, the current scheduling algorithm is mostly based on task duplication, without a full consideration of the correlation between the predecessor task and its subsequent tasks. Based on modeling the multi-frame task scheduling problem in the heterogeneous embedded system, this paper analyzes the availability of tasks through the design of genetic algorithm, so as to verify the algorithm's feasibility, which is of important guiding significance for the multi-task scheduling in the embedded heterogeneous computing system.

Exact scheduling analysis of non-accumulatively monotonic multiframe tasks

In this paper, we present exact analysis for the worst case response time of the general multiframe (MF) task model executing on a uniprocessor according to the fixed priority scheduling scheme. The analysis is developed in four stages. Firstly, we present the basic response time analysis where we optimize the number of frames that have to be considered in such analysis; we show how their number can be significantly reduced by eliminating non critical frames that are dominated by other frames. Secondly, we extend this analysis to be applicable to MF tasks with arbitrary deadlines. Thirdly, the basic analysis is extended to cope with frame specific deadlines. Lastly, the two models of frame specific deadlines and arbitrary deadlines are combined and the relative analysis is presented. An optimal priority assignment scheme for the frame specific deadline scenario is also presented in this paper.

Effective Scheduling Algorithms for I/O Blocking with a Multi-Frame Task Model

A task that suspends itself to wait for an I/O completion or to wait tor an event from another node in distributed environments is called an I/O blocking task. Conventional hard real-time scheduling theories use framework of rate monotonic analysis (RMA) to schedule such I/O blocking tasks. However, most of them are pessimistic. In this paper, we propose effective algorithms that can schedule a task set which has I/O blocking tasks under dynamic priority assignment. We present a new critical instant theorem for the multi-frame task set under dynamic priority assignment. The schedulability is analyzed under the new critical instant theorem. For the schedulability analysis, this paper presents saturation summation which is used to calculate the maximum interference function (MIF). With saturation summation, the schedulability of a task set having I/O blocking tasks can be analyzed more accurately. We propose an algorithm which is called Frame Laxity Monotonic Scheduling (FLMS). A genetic algorithm (GA) is also applied. From our experiments, we can conclude that FLMS can significantly reduce the calculation time, and GA can improve task schedulability ratio more than is possible with FLMS.

Efficient Exact Test for Rate-Monotonic Schedulability Using Large Period-Dependent Initial Values

Real-time systems using rate-monotonic fixed priority scheduling can be checked for schedulability either by sufficient but pessimistic schedulability conditions or by exact testing. Exact testing provides a more precise result but may not be performed in polynomial time. Audsley et al. proposed one of the earliest methods by iteratively deriving the response times of jobs. Other researchers have improved the exact test method by using different initial values for testing. In this paper, we propose new initial values of p, - p, , and f in a task set of i tasks, where p, is the period of task T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</sub> . We show that the new initial values can significantly improve the efficiency of exact testing. These period-dependent initial values can also be used for the schedulability test of multiframe task models and effectively reduce the number of iterations for testing.

Dynamic- and Static-priority Scheduling of Recurring Real-time Tasks

The recurring real-time task model for hard-real-time task is studied from a feasibility-analysis perspective. This model generalizes earlier models such as the sporadic task model and the generalized multiframe task model. Algorithms are presented for the static-priority and dynamic-priority feasibility-analysis of systems of independent recurring real-time tasks in a preemptive uniprocessor environment.

Generalized Multiframe Tasks

A new model for sporadic task systems is introduced. This model the generalized multiframe task modelfurther generalizes both the conventional sporadic-tasks model, and the more recent multiframe m...