184 research outputs found
Gang FTP scheduling of periodic and parallel rigid real-time tasks
In this paper we consider the scheduling of periodic and parallel rigid
tasks. We provide (and prove correct) an exact schedulability test for Fixed
Task Priority (FTP) Gang scheduler sub-classes: Parallelism Monotonic, Idling,
Limited Gang, and Limited Slack Reclaiming. Additionally, we study the
predictability of our schedulers: we show that Gang FJP schedulers are not
predictable and we identify several sub-classes which are actually predictable.
Moreover, we extend the definition of rigid, moldable and malleable jobs to
recurrent tasks
Multiprocessor Global Scheduling on Frame-Based DVFS Systems
In this ongoing work, we are interested in multiprocessor energy efficient
systems, where task durations are not known in advance, but are know
stochastically. More precisely, we consider global scheduling algorithms for
frame-based multiprocessor stochastic DVFS (Dynamic Voltage and Frequency
Scaling) systems. Moreover, we consider processors with a discrete set of
available frequencies
Predictability of Fixed-Job Priority Schedulers on Heterogeneous Multiprocessor Real-Time Systems
The multiprocessor Fixed-Job Priority (FJP) scheduling of real-time systems
is studied. An important property for the schedulability analysis, the
predictability (regardless to the execution times), is studied for
heterogeneous multiprocessor platforms. Our main contribution is to show that
any FJP schedulers are predictable on unrelated platforms. A convenient
consequence is the fact that any FJP schedulers are predictable on uniform
multiprocessors
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
(m,k)-firm constraints and DBP scheduling: impact of the initial k-sequence and exact schedulability test
In this paper we study the scheduling of (m,k)-firm synchronous periodic task
systems using the Distance Based Priority (DBP) scheduler. We first show three
phenomena: (i) choosing, for each task, the initial k-sequence 1^k is not
optimal, (ii) we can even start the scheduling from a (fictive) error state (in
regard to the initial k-sequence) and (iii) the period of feasible
DBP-schedules is not necessarily the task hyper-period. We then show that any
feasible DBP-schedule is periodic and we upper-bound the length of that period.
Lastly, based on our periodicity result we provide an exact schedulability
test
On the periodic behavior of real-time schedulers on identical multiprocessor platforms
This paper is proposing a general periodicity result concerning any
deterministic and memoryless scheduling algorithm (including
non-work-conserving algorithms), for any context, on identical multiprocessor
platforms. By context we mean the hardware architecture (uniprocessor,
multicore), as well as task constraints like critical sections, precedence
constraints, self-suspension, etc. Since the result is based only on the
releases and deadlines, it is independent from any other parameter. Note that
we do not claim that the given interval is minimal, but it is an upper bound
for any cycle of any feasible schedule provided by any deterministic and
memoryless scheduler
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
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