1,129 research outputs found
EDF-Like Scheduling for Self-Suspending Real-Time Tasks
In real-time systems, schedulability tests are utilized to provide timing
guarantees. However, for self-suspending task sets, current suspension-aware
schedulability tests are limited to Task-Level Fixed-Priority~(TFP) scheduling
or Earliest-Deadline-First~(EDF) with constrained-deadline task systems. In
this work we provide a unifying schedulability test for the uniprocessor
version of Global EDF-Like (GEL) schedulers and arbitrary-deadline task sets. A
large body of existing scheduling algorithms can be considered as EDF-Like,
such as EDF, First-In-First-Out~(FIFO), Earliest-Quasi-Deadline-First~(EQDF)
and Suspension-Aware EDF~(SAEDF). Therefore, the unifying schedulability test
is applicable to those algorithms. Moreover, the schedulability test can be
applied to TFP scheduling as well.
Our analysis is the first suspension-aware schedulability test applicable to
arbitrary-deadline sporadic real-time task systems under Job-Level
Fixed-Priority (JFP) scheduling, such as EDF. Moreover, it is the first
unifying suspension-aware schedulability test framework that covers a wide
range of scheduling algorithms. Through numerical simulations, we show that the
schedulability test outperforms the state of the art for EDF under
constrained-deadline scenarios. Moreover, we demonstrate the performance of
different configurations under EQDF and SAEDF
Comments on "Gang EDF Schedulability Analysis"
This short report raises a correctness issue in the schedulability test
presented in Kato et al., "Gang EDF Scheduling of Parallel Task Systems", 30th
IEEE Real-Time Systems Symposium, 2009, pp. 459-468
Utilization-Based Scheduling of Flexible Mixed-Criticality Real-Time Tasks
Mixed-criticality models are an emerging paradigm for the design of real-time
systems because of their significantly improved resource efficiency. However,
formal mixed-criticality models have traditionally been characterized by two
impractical assumptions: once \textit{any} high-criticality task overruns,
\textit{all} low-criticality tasks are suspended and \textit{all other}
high-criticality tasks are assumed to exhibit high-criticality behaviors at the
same time. In this paper, we propose a more realistic mixed-criticality model,
called the flexible mixed-criticality (FMC) model, in which these two issues
are addressed in a combined manner. In this new model, only the overrun task
itself is assumed to exhibit high-criticality behavior, while other
high-criticality tasks remain in the same mode as before. The guaranteed
service levels of low-criticality tasks are gracefully degraded with the
overruns of high-criticality tasks. We derive a utilization-based technique to
analyze the schedulability of this new mixed-criticality model under EDF-VD
scheduling. During runtime, the proposed test condition serves an important
criterion for dynamic service level tuning, by means of which the maximum
available execution budget for low-criticality tasks can be directly determined
with minimal overhead while guaranteeing mixed-criticality schedulability.
Experiments demonstrate the effectiveness of the FMC scheme compared with
state-of-the-art techniques.Comment: This paper has been submitted to IEEE Transaction on Computers (TC)
on Sept-09th-201
k2U: A General Framework from k-Point Effective Schedulability Analysis to Utilization-Based Tests
To deal with a large variety of workloads in different application domains in
real-time embedded systems, a number of expressive task models have been
developed. For each individual task model, researchers tend to develop
different types of techniques for deriving schedulability tests with different
computation complexity and performance. In this paper, we present a general
schedulability analysis framework, namely the k2U framework, that can be
potentially applied to analyze a large set of real-time task models under any
fixed-priority scheduling algorithm, on both uniprocessor and multiprocessor
scheduling. The key to k2U is a k-point effective schedulability test, which
can be viewed as a "blackbox" interface. For any task model, if a corresponding
k-point effective schedulability test can be constructed, then a sufficient
utilization-based test can be automatically derived. We show the generality of
k2U by applying it to different task models, which results in new and improved
tests compared to the state-of-the-art.
Analogously, a similar concept by testing only k points with a different
formulation has been studied by us in another framework, called k2Q, which
provides quadratic bounds or utilization bounds based on a different
formulation of schedulability test. With the quadratic and hyperbolic forms,
k2Q and k2U frameworks can be used to provide many quantitive features to be
measured, like the total utilization bounds, speed-up factors, etc., not only
for uniprocessor scheduling but also for multiprocessor scheduling. These
frameworks can be viewed as a "blackbox" interface for schedulability tests and
response-time analysis
A C-DAG task model for scheduling complex real-time tasks on heterogeneous platforms: preemption matters
Recent commercial hardware platforms for embedded real-time systems feature
heterogeneous processing units and computing accelerators on the same
System-on-Chip. When designing complex real-time application for such
architectures, the designer needs to make a number of difficult choices: on
which processor should a certain task be implemented? Should a component be
implemented in parallel or sequentially? These choices may have a great impact
on feasibility, as the difference in the processor internal architectures
impact on the tasks' execution time and preemption cost. To help the designer
explore the wide space of design choices and tune the scheduling parameters, in
this paper we propose a novel real-time application model, called C-DAG,
specifically conceived for heterogeneous platforms. A C-DAG allows to specify
alternative implementations of the same component of an application for
different processing engines to be selected off-line, as well as conditional
branches to model if-then-else statements to be selected at run-time. We also
propose a schedulability analysis for the C-DAG model and a heuristic
allocation algorithm so that all deadlines are respected. Our analysis takes
into account the cost of preempting a task, which can be non-negligible on
certain processors. We demonstrate the effectiveness of our approach on a large
set of synthetic experiments by comparing with state of the art algorithms in
the literature
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