提高软非周期任务响应性能的调度算法

实时环境中常常既包含硬周期任务,又包含软非周期任务,引入一种改进软非周期实时任务响应时间的算法.已有的解决混合任务调度问题的方法都是基于速率单调（Rate Monotonic）策略的,其中从周期任务“挪用时间”的算法被证明优于其他所有算法.但是,速率单调算法限制了处理器的使用率,从而使周期任务的可“挪用”时间受到限制.最后期限驱动（Deadline Driven）策略DD可使潜在的处理器利用率达到100%.新算法正是在周期任务的调度中适当加入了DD策略,从而使非周期任务的响应时间得以缩短.仿真实验的结果表明,这种算法的性能优于已有的所有算法,而由它所带来的额外开销却不算很高.     

一种实时系统中的多任务可预测调度算法

通过研究实时系统中可能出现的任务类型，提出了一种实时系统任务模型和基于这个模型的多任务调度算法，分析了该算法下所有周期任务和非周期任务可调度的条件。该算法结合了DMS(Dcadlinc Monotonic Scheduling)和DD(Deadline Driven)算法，在保证系统中周期任务执行的前提下,也使非周期任务获得了，较好的响应时间。     

Aperiodic servers in a deadline scheduling environment

A real-time system may have tasks with soft deadlines, as well as hard deadlines. While earliest-deadline-first scheduling is effective for hard-deadline tasks, applying it to soft-deadline tasks may waste schedulable processor capacity or sacrifice average response time. Better average response time may be obtained, while still guaranteeing hard deadlines, with an aperiodic server. Three scheduling algorithms for aperiodic servers are described, and schedulability tests are derived for them. A simulation provides performance data for these three algorithms on random aperiodic tasks. The performances of the deadline aperiodic servers are compared with those of several alternatives, including background service, a deadline polling server, and rate-monotonic servers, and with estimates based on the M/M/1 queueing model. This adds to the evidence in support of deadline scheduling,versus fixed priority scheduling.     

强实时环境下调度非周期任务的时限寻优方法

文章提出了强实时环境下调度弱时限非周期任务的时限寻优方法（ＤＯＡ）,该方法在保证周期任务和偶发性任务满足时限要求的前提下,使非周期任务的响应时间达到最优。它还可根据实时应用的需要对算法的执行性能和计算复杂度进行折衷调整。仿真实验表明,ＤＯＡ与现有的动态调度算法相比,使非周期任务响应时间更短,同时它收敛快,额外开销小,计算复杂度低,实现方便,因此是强实时环境下对周期任务与非周期任务进行混合调度的一种较好的方法。     

引入虚拟特征参数的混合实时任务调度及应用

提出了在实时环境下周期任务与非周期任务混合调度的一种新方法。引入非周期实时任务虚拟截止期、虚拟周期的特征参数,综合考虑各实时任务的多特征参数进行优先级设计,克服了单独考虑任务的个别参数以及忽略非周期任务自身特征的调度策略的局限性及调度风险,且能够尽可能地加快非周期任务的响应速度,提高系统整体的调度性能。将该方法在RT-Linux实时环境中实现,并针对无人飞艇的自动驾驶仪进行了任务实例的可调度性测试,证明了该调度策略的可行性。     

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.     

面向物联网终端的任务相关性调度策略

对于具有相关性的任务,调度顺序不合理将影响任务的执行时间和实时性。结合物联网终端任务间依赖关系复杂的特点提出了一种利用任务相关性的调度策略。该策略设计了以作业轮询组为主体的任务模型,根据任务时限建立了优先级因子矩阵作为任务调度的凭据,对于周期任务,在每个任务执行完毕后生成,以任务相关性为参数的增量矩阵用以动态修改任务优先级,使前驱任务能优先执行;对于非周期任务采用了构建临时作业轮询组的方式进行抢占调度。测试结果表明,该策略能够有效减少具有相关性的周期任务集执行时间和调度失败次数,缩短非周期任务响应时间。     

实时系统中的非定期任务调度算法综述

非定期任务调度是实时系统中的一个重要研究内容，综述了实时系统中非定期任务调度算法的研究与进展，按照这些算法的特征分为基于服务器的算法与基于空闲时间的算法两大类别，并着重对每个类别中的不同算法的特征与性能进行了分析，通过对这些算法的比较与分析，希望为实时系统的研究与开发者提供有意义的参考，最后还给出了非定期任务调度进一步研究的思路与建议。     

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．     

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     

云环境下周期和非周期混合实时任务双容错调度算法

云环境中的处理机故障已成为云计算不可忽视的问题,容错成为设计和发展云计算系统的关键需求。针对一些容错调度算法在任务调度过程中调度效率低下以及任务类型单一的问题,提出一种处理机和任务主副版本分组的容错调度方法;并给出了副版本可重叠执行的判定方法,以及任务最坏响应时间的计算公式。通过实验和分析表明,和以前算法相比,将处理机分成两组分别执行任务主版本和任务副版本,减少了任务调度所需进行可调度测试的时间,增加了副版本重叠执行的机会,减少了所需的处理机个数,对提高系统处理机的利用率和容错调度的效率具有重要的意义。     

EDF统一调度硬实时周期任务和偶发任务的可调度性判定算法

现有的硬实时周期任务和非周期任务的混合调度方法都没有保证非周期任务的实时性,所以不适合调度具有强实时要求的偶发任务.通过分析和计算EDF算法调度偶发任务所占用的空闲时间和挪用时间,以及调度后对空闲时间和最大可挪用时间的影响,提出一种采用EDF算法统一调度硬实时周期任务和偶发任务时的可调度性充分判定算法.最后用仿真实验得出了该算法在不同系统负载下的判定准确率和偶发任务的平均响应时间.     

MINIMIZING SERVICE DELAY OF APERIODIC TASKS IN DYNAMIC‐PRIORITY NON‐PREEMPTIVE HARD REAL‐TIME SYSTEMS

A scheduling technique is presented to minimize service delay of aperiodic tasks in hard real‐time systems that employ dynamic‐priority scheduling and do not allow task preemption. In a real‐time scheduling process, the execution of periodic tasks can be deferred as long as this does not cause other tasks to violate their time constraints. However, aperiodic tasks that usually have urgent missions should complete execution as early as possible. In this paper, it is assumed that aperiodic tasks also have time constraints. Thus, the problem of deciding whether an aperiodic task with an unpredictable arrival time can be scheduled successfully or not is difficult to solve because delaying periodic tasks may cause them to fail to meet their time constraints. We present a dynamic scheduling technique to solve this problem which makes use of the symmetric property of a schedule. The maximum possible idle slot is always reserved at every scheduling point so that aperiodic tasks can be serviced immediately if the reserved idle slot is big enough to service them. The proposed technique also maximizes utilization of idle slots by reserving them for the longest possible time span.     

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.     

An optimal algorithm for scheduling soft aperiodic tasks indynamic-priority preemptive systems

The paper addresses the problem of jointly scheduling tasks with both hard and soft real time constraints. We present a new analysis applicable to systems scheduled using a priority preemptive dispatcher, with priorities assigned dynamically according to the EDF policy. Further, we present a new efficient online algorithm (the acceptor algorithm) for servicing aperiodic work load. The acceptor transforms a soft aperiodic task into a hard one by assigning a deadline. Once transformed, aperiodic tasks are handled in exactly the same way as periodic tasks with hard deadlines. The proposed algorithm is shown to be optimal in terms of providing the shortest aperiodic response time among fixed and dynamic priority schedulers. It always guarantees the proper execution of periodic hard tasks. The approach is composed of two parts: an offline analysis and a run time scheduler. The offline algorithm runs in pseudopolynomial time O(mn), where n is the number of hard periodic tasks and m is the hyperperiod/min deadline     

长释放时间间隔优先的混合任务调度算法

针对混合任务实时调度的需求和MUF算法的局限性,提出了一种长释放时间间隔优先的混合任务实时调度算法LRIF,该算法除了可对周期性硬实时任务提供调度保证外,同时还可确保非周期性软实时任务的可调度率。论文还提出了LRIF调度算法的可调度性分析方法,并讨论了LRIF调度算法的实现方法。     

应用于实时系统的RMS算法的改进

本文阐述了以PLC为核心的HGJD001实验台电气控制系统，并采用上位计算机实现对实验台运行状态的通讯监测。     

Algorithms and optimality of scheduling soft aperiodic requests in fixed-priority preemptive systems

In this paper, we investigate the problem of scheduling soft aperiodic requests in systems where periodic tasks are scheduled on a fixed-priority, preemptive basis. First, we show that given any queueing discipline for the aperiodic requests, no scheduling algorithm can minimize the response time of every aperiodic request and guarantee that the deadlines of the periodic tasks are met when the periodic tasks are scheduled on a fixed-priority, preemptive basis. We then develop two algorithms: Algorithm is locally optimal in that it minimizes the response time of the aperiodic request at the head of the aperiodic service queue. Algorithm is globally optimal in that it completes the current backlog of work in the aperiodic service queue as early as possible.     

主从结构交换式以太网中实时消息调度研究

为使交换式以太网能满足实时通信的要求,针对FTT SE网络调度模型,提出了一种同时适用于周期性和非周期性实时消息的链路可调度性判定方法。在证明了消息链路调度优化问题MLSOP为NP complete的同时,针对周期性实时消息的链路调度优化给出了启发式算法LSHA。最后,对于周期性和非周期性实时消息分别设计了基于EDF的调度算法。仿真实验表明,在提高网络链路带宽利用率和减小消息平均延时方面,该算法均较FTT SE有明显的优势。