12,059 research outputs found
Integrating Job Parallelism in Real-Time Scheduling Theory
We investigate the global scheduling of sporadic, implicit deadline,
real-time task systems on multiprocessor platforms. We provide a task model
which integrates job parallelism. We prove that the time-complexity of the
feasibility problem of these systems is linear relatively to the number of
(sporadic) tasks for a fixed number of processors. We propose a scheduling
algorithm theoretically optimal (i.e., preemptions and migrations neglected).
Moreover, we provide an exact feasibility utilization bound. Lastly, we propose
a technique to limit the number of migrations and preemptions
Replica determinism and flexible scheduling in hard real-time dependable systems
Fault-tolerant real-time systems are typically based on active replication where replicated entities are required to deliver their outputs in an identical order within a given time interval. Distributed scheduling of replicated tasks, however, violates this requirement if on-line scheduling, preemptive scheduling, or scheduling of dissimilar replicated task sets is employed. This problem of inconsistent task outputs has been solved previously by coordinating the decisions of the local schedulers such that replicated tasks are executed in an identical order. Global coordination results either in an extremely high communication effort to agree on each schedule decision or in an overly restrictive execution model where on-line scheduling, arbitrary preemptions, and nonidentically replicated task sets are not allowed. To overcome these restrictions, a new method, called timed messages, is introduced. Timed messages guarantee deterministic operation by presenting consistent message versions to the replicated tasks. This approach is based on simulated common knowledge and a sparse time base. Timed messages are very effective since they neither require communication between the local scheduler nor do they restrict usage of on-line flexible scheduling, preemptions and nonidentically replicated task sets
A Novel Side-Channel in Real-Time Schedulers
We demonstrate the presence of a novel scheduler side-channel in preemptive,
fixed-priority real-time systems (RTS); examples of such systems can be found
in automotive systems, avionic systems, power plants and industrial control
systems among others. This side-channel can leak important timing information
such as the future arrival times of real-time tasks.This information can then
be used to launch devastating attacks, two of which are demonstrated here (on
real hardware platforms). Note that it is not easy to capture this timing
information due to runtime variations in the schedules, the presence of
multiple other tasks in the system and the typical constraints (e.g.,
deadlines) in the design of RTS. Our ScheduLeak algorithms demonstrate how to
effectively exploit this side-channel. A complete implementation is presented
on real operating systems (in Real-time Linux and FreeRTOS). Timing information
leaked by ScheduLeak can significantly aid other, more advanced, attacks in
better accomplishing their goals
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 Backward Algorithm for the Multiprocessor Online Feasibility of Sporadic Tasks
The online feasibility problem (for a set of sporadic tasks) asks whether
there is a scheduler that always prevents deadline misses (if any), whatever
the sequence of job releases, which is a priori} unknown to the scheduler. In
the multiprocessor setting, this problem is notoriously difficult. The only
exact test for this problem has been proposed by Bonifaci and
Marchetti-Spaccamela: it consists in modelling all the possible behaviours of
the scheduler and of the tasks as a graph; and to interpret this graph as a
game between the tasks and the scheduler, which are seen as antagonistic
players. Then, computing a correct scheduler is equivalent to finding a winning
strategy for the `scheduler player', whose objective in the game is to avoid
deadline misses. In practice, however this approach is limited by the
intractable size of the graph. In this work, we consider the classical
attractor algorithm to solve such games, and introduce antichain techniques to
optimise its performance in practice and overcome the huge size of the game
graph. These techniques are inspired from results from the formal methods
community, and exploit the specific structure of the feasibility problem. We
demonstrate empirically that our approach allows to dramatically improve the
performance of the game solving algorithm.Comment: Long version of a conference paper accepted to ACSD 201
Statistic Rate Monotonic Scheduling
In this paper we present Statistical Rate Monotonic Scheduling (SRMS), a generalization of the classical RMS results of Liu and Layland that allows scheduling periodic tasks with highly variable execution times and statistical QoS requirements. Similar to RMS, SRMS has two components: a feasibility test and a scheduling algorithm. The feasibility test for SRMS ensures that using SRMS' scheduling algorithms, it is possible for a given periodic task set to share a given resource (e.g. a processor, communication medium, switching device, etc.) in such a way that such sharing does not result in the violation of any of the periodic tasks QoS constraints.
The SRMS scheduling algorithm incorporates a number of unique features. First, it allows for fixed priority scheduling that keeps the tasks' value (or importance) independent of their periods. Second, it allows for job admission control, which allows the rejection of jobs that are not guaranteed to finish by their deadlines as soon as they are released, thus enabling the system to take necessary compensating actions. Also, admission control allows the preservation of resources since no time is spent on jobs that will miss their deadlines anyway. Third, SRMS integrates reservation-based and best-effort resource scheduling seamlessly. Reservation-based scheduling ensures the delivery of the minimal requested QoS; best-effort scheduling ensures that unused, reserved bandwidth is not wasted, but rather used to improve QoS further. Fourth, SRMS allows a system to deal gracefully with overload conditions by ensuring a fair deterioration in QoS across all tasks---as opposed to penalizing tasks with longer periods, for example. Finally, SRMS has the added advantage that its schedulability test is simple and its scheduling algorithm has a constant overhead in the sense that the complexity of the scheduler is not dependent on the number of the tasks in the system.
We have evaluated SRMS against a number of alternative scheduling algorithms suggested in the literature (e.g. RMS and slack stealing), as well as refinements thereof, which we describe in this paper. Consistently throughout our experiments, SRMS provided the best performance. In addition, to evaluate the optimality of SRMS, we have compared it to an inefficient, yet optimal scheduler for task sets with harmonic periods.National Science Foundation (CCR-970668
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