2,132 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
Energy-Efficient Scheduling for Homogeneous Multiprocessor Systems
We present a number of novel algorithms, based on mathematical optimization
formulations, in order to solve a homogeneous multiprocessor scheduling
problem, while minimizing the total energy consumption. In particular, for a
system with a discrete speed set, we propose solving a tractable linear
program. Our formulations are based on a fluid model and a global scheduling
scheme, i.e. tasks are allowed to migrate between processors. The new methods
are compared with three global energy/feasibility optimal workload allocation
formulations. Simulation results illustrate that our methods achieve both
feasibility and energy optimality and outperform existing methods for
constrained deadline tasksets. Specifically, the results provided by our
algorithm can achieve up to an 80% saving compared to an algorithm without a
frequency scaling scheme and up to 70% saving compared to a constant frequency
scaling scheme for some simulated tasksets. Another benefit is that our
algorithms can solve the scheduling problem in one step instead of using a
recursive scheme. Moreover, our formulations can solve a more general class of
scheduling problems, i.e. any periodic real-time taskset with arbitrary
deadline. Lastly, our algorithms can be applied to both online and offline
scheduling schemes.Comment: Corrected typos: definition of J_i in Section 2.1; (3b)-(3c);
definition of \Phi_A and \Phi_D in paragraph after (6b). Previous equations
were correct only for special case of p_i=d_
Assigning real-time tasks on heterogeneous multiprocessors with two types of processors
Consider the problem of scheduling a set of implicitdeadline
sporadic tasks on a heterogeneous multiprocessor
so as to meet all deadlines. Tasks cannot migrate and
the platform is restricted in that each processor is either
of type-1 or type-2 (with each task characterized by a
different speed of execution upon each type of processor).
We present an algorithm for this problem with a timecomplexity
of O(n·m), where n is the number of tasks and
m is the number of processors. It offers the guarantee that
if a task set can be scheduled by any non-migrative algorithm
to meet deadlines then our algorithm meets deadlines
as well if given processors twice as fast. Although this result
is proven for only a restricted heterogeneous multiprocessor,
we consider it significant for being the first realtime
scheduling algorithm to use a low-complexity binpacking
approach to schedule tasks on a heterogeneous
multiprocessor with provably good performance
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