572 research outputs found
A Three Phase Scheduling for System Energy Minimization of Weakly Hard Real Time Systems
This paper aims to present a three phase scheduling algorithm that offers lesser energy consumption for weakly hard real time systems modeled with (1D55E;1D55E;1D55E;1D55E;, 1D55C;1D55C;1D55C;1D55C;) constraint. The weakly hard real time system consists of a DVS processor (frequency dependent) and peripheral devices (frequency independent) components. The energy minimization is done in three phase taking into account the preemption overhead. The first phase partitions the jobs into mandatory and optional while assigning processor speed ensuring the feasibility of the task set. The second phase proposes a greedy based preemption control technique which reduces the energy consumption due to preemption. While the third phase refines the feasible schedule received from the second phase by two methods, namely speed adjustment and delayed start. The proposed speed adjustment assigns optimal speed to each job whereas fragmented idle slots are accumulated to provide better opportunity to switch the component into sleep state by delayed start strategy as a result leads to energy saving. The simulation results and examples illustrate that our approach can effectively reduce the overall system energy consumption (especially for systems with higher utilizations) while guaranteeing the (1D55E;1D55E;1D55E;1D55E;, 1D55C;1D55C;1D55C;1D55C;) at the same time
Dynamic Voltage Scaling With Reduced Frequency Switching And Preemptions
Dynamic Voltage Scaling is an innovative technique for reducing the power consumption of a processor by utilizing its hardware functionality. Dynamic Voltage Scaling processors are mainly focusing on power management. Such processors can be switch between discrete frequency and voltage levels. The main challenges of Dynamic Voltage Scaling are increased number of preemptions and frequency switching. A part of dynamic energy as well as CPU time is lost due to these processes. To limit such processes, an algorithm is proposed which reduces both unwanted frequency switching and preemptions
Reclaiming the energy of a schedule: models and algorithms
We consider a task graph to be executed on a set of processors. We assume
that the mapping is given, say by an ordered list of tasks to execute on each
processor, and we aim at optimizing the energy consumption while enforcing a
prescribed bound on the execution time. While it is not possible to change the
allocation of a task, it is possible to change its speed. Rather than using a
local approach such as backfilling, we consider the problem as a whole and
study the impact of several speed variation models on its complexity. For
continuous speeds, we give a closed-form formula for trees and series-parallel
graphs, and we cast the problem into a geometric programming problem for
general directed acyclic graphs. We show that the classical dynamic voltage and
frequency scaling (DVFS) model with discrete modes leads to a NP-complete
problem, even if the modes are regularly distributed (an important particular
case in practice, which we analyze as the incremental model). On the contrary,
the VDD-hopping model leads to a polynomial solution. Finally, we provide an
approximation algorithm for the incremental model, which we extend for the
general DVFS model.Comment: A two-page extended abstract of this work appeared as a short
presentation in SPAA'2011, while the long version has been accepted for
publication in "Concurrency and Computation: Practice and Experience
Energy-Efficient Concurrency Control for Dynamic-Priority Real-Time Tasks with Abortable Critical Sections
In this paper, we are interested in energy-efficient concurrency control for real-time tasks on a non-ideal DVS processor. Based on well-known ceiling-based concurrency control protocols (such as priority ceiling protocol (PCP) and stack resource policy (SRP)), researchers have proposed energy-efficient approaches to mange concurrent accesses to shared resources so that the energy consumption can be reduced. However, ceiling-based protocols have a problem of ceiling blocking which imposes a great impact on the performance of real-time systems. In order to achieve sufficient performance, we propose a new protocol, called conditional abortable stack resource policy (CA-SRP), to resolve the ceiling blocking problem for dynamic-priority real-time tasks by incorporating a conditional abort rule into SRP. Based on the schedulability analysis of CA-SRP, we also propose a method, called dynamic speed assignment (DSA), to dynamically calculate and assign proper processor speeds for task execution so that the energy consumption can be reduced further. The capabilities of our proposed CA-SRP and DSA have been evaluated by a series of experiments, for which we have encouraging results
Process Algebraic Modeling and Analysis of Power-Aware Real-Time Systems
The paper describes a unified formal framework for designing and reasoning about power-constrained, real-time systems. The framework is based on process algebra, a formalism which has been developed to describe and analyze communicating, concurrent systems. The proposed extension allows the modeling of probabilistic resource failures, priorities of resource usages, and power consumption by resources within the same formalism. Thus, it is possible to evaluate alternative power-consumption behaviors and tradeoffs under different real-time schedulers, resource limitations, resource failure probabilities, etc. This paper describes the modeling and analysis techniques, and illustrates them with examples, including a dynamic voltage-scaling algorithm
MORA: an Energy-Aware Slack Reclamation Scheme for Scheduling Sporadic Real-Time Tasks upon Multiprocessor Platforms
In this paper, we address the global and preemptive energy-aware scheduling
problem of sporadic constrained-deadline tasks on DVFS-identical multiprocessor
platforms. We propose an online slack reclamation scheme which profits from the
discrepancy between the worst- and actual-case execution time of the tasks by
slowing down the speed of the processors in order to save energy. Our algorithm
called MORA takes into account the application-specific consumption profile of
the tasks. We demonstrate that MORA does not jeopardize the system
schedulability and we show by performing simulations that it can save up to 32%
of energy (in average) compared to execution without using any energy-aware
algorithm.Comment: 11 page
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