Self-suspending Tasks Research Articles

Schedulability Analysis for Coscheduling Real-Time Tasks on Multiprocessors

The real-time coscheduling problem, where tasks may have multiple phases executing on different types of processors, is known to be hard. The (already hard) self-suspending task scheduling simplifies the coscheduling problem by assuming that the latency a task may experience on the other type of processors is naturally bounded, which is unfortunately not true in practice. In this article, we present a novel analysis technique, namely, the vertical view analysis, for analyzing the schedulability of coscheduling sporadic tasks under global earliest-deadline-first (GEDF) on a heterogeneous multiprocessor consisting of two types of processors. We derive both hard (no deadline miss) and soft (bounded response times) real-time utilization-based tests. To the best of our knowledge, these results are the first-of-its-kind for the coscheduling problem and may allow real-time schedulability analysis to be carried out on more practical scenarios under heterogeneous computing.

A note on slack enforcement mechanisms for self-suspending tasks

This paper provides counterexamples for the slack enforcement mechanisms to handle segmented self-suspending real-time tasks by Lakshmanan and Rajkumar (Proceedings of the Real-Time and Embedded Technology and Applications Symposium (RTAS), pp 3–12, 2010).

Pessimism in multicore global schedulability analysis

Abstract When it comes to multicore real-time systems, the global scheduling that allows tasks to migrate between different cores and the partitioned scheduling that statically allocates tasks to individual cores are two popular policies. However, due to the complexity and pessimism of multicore schedulability tests, there is no simple way to compare the effectiveness of global versus partitioned scheduling, and it is hard to improve existing analysis methods. In this paper, we formally prove that, according to state-of-the-art global schedulability tests, if a multicore task system (with Di ≤ Ti) is deemed schedulable under global fixed priority policy, we can easily find a schedulable partitioning for it too. This result holds also for self-suspending tasks that can suspend its own execution voluntarily. Such a fact reveals the high pessimism in current global schedulability tests. To tackle this, we propose a 2-part execution scenario, by simply considering the task execution into two parts, that helps better estimate the interference a task suffers. Using this method, a new global schedulability test can detect schedulable tasksets that will be non-schedulable by any partitioned scheduling algorithm. Our proposed method indicates a new direction for designing global schedulability tests. In the experiments, comparisons with other global and partitioned schedulability tests confirm the improvement by using our new test.

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.

Constant bandwidth server revisited

The Constant Bandwidth Server (CBS) is an algorithm for providing temporal protection and real-time guarantees to real-time sporadic tasks. Recently, an implementation of this algorithim called SCHED_DEADLINE has been included in the Linux kernel. Therefore, the CBS algorithm is now used to serve more generic tasks than do not obey to the classical sporadic task model. One important type of tasks which was not considered by the original CBS algorithm is the so called "self-suspending task model", where a task instance can suspend itself waiting for an external event. Even if the original algorithm is adapted so that the temporal protection property continues to hold, it is difficult for developers to provide guarantees and to select the most appropriate server parameters for such tasks. This paper investigates the problem of using the CBS algorithm for serving self-suspending tasks, by analysing it from a theoretical point of view and showing how to select the server parameters (budget and periods) for self-suspending tasks. Finally, the effectiveness of these proposals is shown through both simulations and real experiments on Linux / SCHED_DEADLINE.

Schedulability Analysis of Task Sets with Upper- and Lower-Bound Temporal Constraints

Increasingly, real-time systems must handle the self-suspension of tasks (that is, lower-bound wait times between subtasks) in a timely and predictable manner. A fast schedulability test that does not significantly overestimate the temporal resources needed to execute self-suspending task sets would be of benefit to these modern computing systems. In this paper, a polynomial-time test is presented that is known to be the first to handle nonpreemptive self-suspending task sets with hard deadlines, where each task has any number of self-suspensions. To construct the test, a novel priority scheduling policy is leveraged, the th subtask first, which restricts the behavior of the self-suspending model to provide an analytical basis for an informative schedulability test. In general, the problem of sequencing according to both upper-bound and lower-bound temporal constraints requires an idling scheduling policy and is known to be nondeterministic polynomial-time hard. However, the tightness of the schedulability test and scheduling algorithm are empirically validated, and it is shown that the processor is able to effectively use up to 95% of the self-suspension time to execute tasks.

A new technique for analyzing soft real-time self-suspending task systems

We consider the problem of globally scheduling soft real-time sporadic self-suspending task systems on multiprocessors. Existing analysis methods are pessimistic, yielding O(n) utilization loss where n is the number of tasks in the system. Unless the number of tasks is small and suspension delays are short, such methods entail significant capacity loss. We identify the fundamental sources that cause pessimism in existing methods, and propose a new analysis technique that entails only O(m) suspension-related utilization loss, where m is the number of processors.