Priority-Driven Scheduling of Periodic Task Systems on Multiprocessors

The scheduling of systems of periodic tasks upon multiprocessor platforms is considered. Utilization-based conditions are derived for determining whether a periodic task system meets all deadlines when scheduled using the earliest deadline first scheduling algorithm (EDF) upon a given multiprocessor platform. A new priority-driven algorithm is proposed for scheduling periodic task systems upon multiprocessor platforms: this algorithm is shown to successfully schedule some task systems for which EDF may fail to meet all deadlines.     

The EDL Server for Scheduling Periodic and Soft Aperiodic Tasks with Resource Constraints

In this paper, we are concerned with the problem of serving soft aperiodic tasks on a uniprocessor system where periodic tasks are scheduled on a dynamic-priority, preemptive basis and exclusively access to critical sections. Scheduling of tasks is handled by the Dynamic Priority Ceiling Protocol working with an Earliest Deadline scheduler. Our analysis determines the maximum processing time which may be stolen from periodic tasks without jeopardizing both their timing constraints and resource consistency. It provides the basis for an on-line scheduling algorithm, the EDL Server, to deal with the minimization of response times for soft aperiodic tasks.     

基于多处理机的混合实时任务容错调度

提出了一种混合实时任务容错调度算法．该算法采用Rate Monotonic(RM)算法完成周期任务的静态调度;采用预订处理机时间方法和Earlier Deadline First(EDF)算法动态调度非周期任务;采用主／副版本备份技术确保系统的容错能力．通过充分利用周期任务的剩余处理机时间调度非周期任务和主动备份与被动备份相结合的方法有效地减少了处理机数．仿真结果证明了算法的有效性．     

面向多处理器的实时周期任务容错调度算法研究

主副版本策略是多处理器系统实时任务调度中处理容错问题的一种重要方式.根据分布式控制系统的特点,本文提出一种改进的FTRMBF算法-PR-FTRMBF,以提高系统周期任务的可调度性.在FTRMBF等已有的调度算法中,当没有处理器分配给当前副版本时,将为副版本分配新的处理器;本文提出的改进算法则以回溯的方式重新分配主版本.在保证系统实时性能和容错能力的前提下,节省了处理器数目.仿真实验表明,与FTRMBF算法相比,改进算法显著提高了系统任务的可调度性.     

Dynamic Real-time Scheduling of Firm Periodic Tasks with Hard and Soft Aperiodic Tasks

In this paper, we address the problem of the dynamic scheduling of skippable periodic task sets (i.e., period tasks allowing occasional skips of instances), together with aperiodic tasks. Scheduling of tasks is handled thanks to the merging of two existing approaches: the Skip-Over task model and the EDL (Earliest Deadline as Late as possible) aperiodic task server. The objective is to provide two on-line scheduling algorithms, namely EDL-RTO and EDL-BWP, in order to minimize the average response time of soft aperiodic requests, while ensuring that the QoS (Quality of Service) of periodic tasks will never be less than a specified bound. We also extend our results to the acceptance of sporadic tasks (i.e., aperiodic tasks with deadlines). We show that these novel scheduling algorithms have better performance compared to related algorithms regarding aperiodic response time and acceptance ratio. Audrey Marchand guaduated in Computer Engineering at the Ecole polytechnique of the University of Nantes (France), in 2002. She is currently a PhD student at the University of Nantes. Her research interests include real-time scheduling theory, aperiodic service mechanisms, quality of service guarantees in soft real-time systems, and Linux-based real-time operating systems and applications. Maryline Chetto received the degree of Docteur de 3ème cycle in control engineering and the degree of Habilitée à Diriger des Recherches in Computer Science from the University of Nantes, France, in 1984 and 1993, respectively. From 1984 to 1985, she held the position of Assistant professor of Computer Science at the University of Rennes, while her research was with the Institut de Recherche en Informatique et Systèmes Aléatoires, Rennes. In 1986, she returned to Nantes and is currently a professor with the Institute of Technology of the University of Nantes. She is conducting her research at IRCCyN. Her main research interests include scheduling and fault-tolerance technologies for real-time applications. She has published more than 60 journal articles and conference papers in the area of real-time operating systems. She is the leader of a French national R&D project, namely Cleopatre, supported by the French government, which aims to provide free open source real-time solutions.     

实时周期任务的非占先式能耗感知调度

针对实时周期性任务集在变电压处理器上的非占先式能耗感知调度问题,在简单遗传算法基础上,提出了一种通过构造特定的遗传过程以自然地满足时序和能耗约束的启发式算法．与贪婪算法相比,该算法在提高系统性能方面具有明显的优势,而且能耗利用效率随着能耗约束值的减小而增大,说明算法具有良好的能耗感知特性．     

Stability and Performance of List Scheduling With External Process Delays

Non-preemptive static priority list scheduling is a simple, low-overhead approach to scheduling precedence-constrained tasks in real-time multiprocessor systems. However, it is vulnerable to anomalous timing behavior caused by variations in task durations. Specifically, reducing the duration of one task can delay the starting time of another task. This phenomenon, called Scheduling Instability, can make it difficult or impossible to guarantee real-time deadlines. Several heuristic solutions to handle scheduling instability have been reported. This paper addresses three main limitations in the state of the art in schedule stabilization. First, each stabilization technique only applies to a narrowly defined class of systems. To alleviate this constraint, we present an Extended Scheduling Model encompassing a wide range of assumptions about the scheduling environment, and address the stability problem under this model. Second, existing stabilization methods are heuristics based on a partial understanding of the causes of instability. We therefore derive a set of General Instability Conditions which are both necessary and sufficient for instability to occur. Third, solutions to scheduling instability range from trivial constraints on the run-time dispatcher through complex transformations of the precedence graph. We present scheduling simulation results comparing the average performance of several inherently stable run-time dispatchers of widely varying levels of complexity. Results show that for representative real-time workloads, simple low-overhead dispatchers perform nearly as well as a complex minimally stabilized dispatcher. Thus, complex schedule stabilization methods may be unnecessary, or even detrimental, due to their high computational overhead.     

异构分布式系统中实时周期任务的容错调度算法

提出一个基于抢占性实时周期任务的可靠性调度模型,该模型与现有可靠性模型相比充分考虑了单处理机故障容错情况下的系统可靠性,因而更加接近现实和精确.在此基础上,提出一个基于异构分布式系统的实时容错调度算法IRDFTAHS,IRDFTAHS算法以提高系统的可靠性为目标来进行任务的分配,从而在不增加硬件代价的前提条件下通过调度增加了系统的可靠性.该算法同时支持主动和被动两种方式的副版本,使得容错调度算法具有更大的灵活性.最后,通过仿真实验对IRDFTAHS和现有的调度算法在几个方面进行比较.实验结果表明,IRDFTAHS算法的综合性能优于现有算法.     

A New Approach for Scheduling of Parallelizable Tasks in Real-Time Multiprocessor Systems

In a parallelizable task model, a task can be parallelized and the component tasks can be executed concurrently on multiple processors. We use this parallelism in tasks to meet their deadlines and also obtain better processor utilisation compared to non-parallelized tasks. Non-preemptive parallelizable task scheduling combines the advantages of higher schedulability and lower scheduling overhead offered by the preemptive and non-preemptive task scheduling models, respectively. We propose a new approach to maximize the benefits from task parallelization. It involves checking the schedulability of periodic tasks (if necessary, by parallelizing them) off-line and run-time scheduling of the schedulable periodic tasks together with dynamically arriving aperiodic tasks. To avoid the run-time anomaly that may occur when the actual computation time of a task is less than its worst case computation time, we propose efficient run-time mechanisms.We have carried out extensive simulation to study the effectiveness of the proposed approach by comparing the schedulability offered by it with that of dynamic scheduling using Earliest Deadline First (EDF), and by comparing its storage efficiency with that of the static table-driven approach. We found that the schedulability offered by parallelizable task scheduling is always higher than that of the EDF algorithm for a wide variety of task parameters and the storage overhead incurred by it is less than 3.6% of the static table-driven approach even under heavy task loads.     

Real-Time Supervisory Control of a Processor for Non-Preemptive Execution of Periodic Tasks

In this article, a method for scheduling a processor for non-preemptive execution of periodic tasks is presented. This method is based on the formal framework of supervisory control of timed discrete-event systems. It is shown that, with this method, the problem of determining schedulability and the problem of finding a scheduling algorithm are dual since a solution to the former necessarily implies a solution to the latter and vice versa. Furthermore, the solution to the latter thus obtained is complete in the sense that it contains all safe sequences of task execution with the guarantee that no deadline is missed. Examples are described to illustrate this method. Implication of the results and computational complexity associated with this method are discussed.     

开销敏感的多处理器最优节能实时调度算法

嵌入式多处理器系统的能耗问题变得日益重要,如何减少能耗同时满足实时约束成为多处理器系统节能实时调度中的一个重要问题.目前绝大多数研究基于关键速度降低处理器的频率以减少动态能耗,采用关闭处理器的方法减少静态能耗.虽然这种方法可以实现节能,但是不能保证最小化能耗.而现有最优的节能实时调度未考虑处理器状态切换的时间和能量开销,因此在切换开销不可忽视的实际平台中不再是最优的.文中针对具有独立动态电压频率调节和动态功耗管理功能的多处理器系统,考虑处理器切换开销,提出一种基于帧任务模型的最优节能实时调度算法.该算法根据关键速度来判断系统负载情况,确定具有最低能耗值的活跃处理器个数,然后根据状态切换开销来确定最优调度序列.该算法允许实时任务在处理器之间任意迁移,计算复杂度小,易于实现.数学分析证明了该算法的最优性.     

Generalized Multiframe Tasks

A new model for sporadic task systems is introduced. This model— the generalized multiframe task model—further generalizes both the conventional sporadic-tasks model, and the more recent multiframe model of Mok and Chen. A framework for determining feasibility for a wide variety of task systems is established; this framework is applied to this task model to obtain a feasibility-testing algorithm that runs in time pseudo-polynomial in the size of the input for all systems of such tasks whose densities are bounded by a constant less than one.     

Non-preemptive scheduling to maximize the minimum global inter-completion time

Temporal load-balancing—“spreading out” the executions of tasks over time—is desirable in many applications. A form of temporal load-balancing is discussed, scheduling to maximize minimum minimum global inter-completion time (MGICT-scheduling). It is shown that MGICT-scheduling is, in general, NP-hard. A number of restricted classes of task systems are identified, which can be efficiently MGICT-scheduled. The technique is applied to a Defense Network System. Simulation results indicate that the proposed strategy achieves higher communication performance in multiprocessor systems. Specifically, our strategy significantly reduces average message delay and percentage of delayed messages.     

用广度优先算法处理并行调度中的任务运行滞后问题

针对分布式系统中多任务系统并行调度的运行滞后问题,本文提出采用广度优先算法进行动态调整的方法。文中给出部分仿真结果及简要分析。     

采用配置完成优先策略的可重构任务调度算法

如何隐藏和减少配置时间是相依性可重构任务调度的关键问题.提出一种采用配置完成优先策略的相依性可重构任务调度算法,通过基于预配置优先级的列表调度算法,实现将后续任务的配置时间隐藏于前驱任务的运行时间中,并采用基于配置完成优先策略的配置重用机制,减少了任务调度后的配置过程,从而在总体上缩短了相依性任务集合的运行时间.仿真结果表明,该调度算法能有效避免调度死锁,并可减少相依性可重构任务的整体运行时间.     

一种有到达时问的多处理器混合流水车间调度的遗传算法

有到达时间的多处理器混合流水车间调度问题在实时机器视觉系统等领域有广泛的应用.这一问题是NP-困难的.鉴于以上原因,给出一种遗传算法.对不同的交叉算子和变异算子以及涉及的参数的不同取值进行试验,并对试验的结果进行分析和讨论,从而给出最好的参数组合.     

基于动态优先级策略的最优软非周期任务调度算法

周期任务与非周期任务的混合调度是实时调度研究的一个重要方向 通过定义“调度”和“逆调度” ,对实时周期任务集在使用EDF算法调度时的可挪用时间进行分析 ,求出了周期任务集在使用EDF调度时的最大可挪用时间 在此基础上 ,提出用于缩短非周期任务响应时间和周转时间的调度算法———ISA(idlestealingalgorithm) ISA算法充分使用最大可挪用时间 ,在保证周期任务满足最后期限的同时能取得非周期任务的最优响应时间和周转时间 证明了ISA算法的最优性 ,并使用仿真实验进行了性能验证     

A Genetic Algorithm for Hybrid Flow-shop Scheduling with Multiprocessor Tasks

The hybrid flow-shop scheduling problem with multiprocessor tasks finds its applications in real-time machine-vision systems among others. Motivated by this application and the computational complexity of the problem, we propose a genetic algorithm in this paper. We first describe the implementation details, which include a new crossover operator. We then perform a preliminary test to set the best values of the control parameters, namely the population size, crossover rate and mutation rate. Next, given these values, we carry out an extensive computational experiment to evaluate the performance of four versions of the proposed genetic algorithm in terms of the percentage deviation of the solution from the lower bound value. The results of the experiments demonstrate that the genetic algorithm performs the best when the new crossover operator is used along with the insertion mutation. This genetic algorithm also outperforms the tabu search algorithm proposed in the literature for the same problem.     

基于异构型结点的任务均衡调度研究

该文以实现时间最短为目标,全面考虑影响任务集实现开销的各种因素,建立了异构型结点集中带偏序关系的任务集的均衡调度模型及其随机搜索算法。调度模型将任务集实现过程分成：执行、传递和等待,强调执行和传递的并行性,降低因等待而发生的费用。算法在统计意义下为多项式时间复杂度。这一模型在工作时限要求较高的领域应用前景广泛。     

一种改进的启发式网格任务调度算法

网格任务调度算法是影响网格成功与否的关键技术之一。网格计算中,一个好的任务调度算法不但要考虑所有任务的makespan,使其值尽量小,同样要考虑到整个系统机器间的负载平衡问题。文章对异构计算环境下的元任务调度算法进行了分析,针对Min-min算法可能引发的负载不平衡问题,结合网格计算环境的特点,提出了一种适用于网格计算环境中的任务调度算法。