一种帧间相关的弱硬实时系统的分析与研究

随着嵌入式系统的发展，实时操作系统越来越受到人们的重视，实时操作系统的一个关键问题是实时调度问题，在研究弱硬实时系统的基础上提出了一种受弱硬实时限制的帧间相关周期模型．首先对该模型的调度性进行了分析与研究，得出了一些结论，然后提出了相应的基于双距离的优先级调度算法，该算法充分利用了帧间相关的特点来提高实时任务的可调度性，最后进行了总结与展望．     

能够提供QoS保证的固定优先级调度

弱硬实时应用要求调度算法必须确保提供满足其弱硬实时QoS（Quality of Service）参数要求的服务,一种新的能够提供（m,k）-firm保证的固定优先级调度算法被提出,该算法能够根据任务的周期以及所要求的QoS参数进行调度优先级的设定,并通过将任务设置为抢占和可选来反映其紧迫程度。文中给出该算法的可调度判定不等式,并且通过对经典任务集的调度结果,验证了算法的有效性和灵活性。     

基于path RTL的弱硬实时系统

弱硬实时系统是实时系统中的一个重要研究领域.经典弱硬实时系统以任务流中任务满足或错过的个数来约束系统性能,存在着无法准确表达系统实时特性的不足,以及弱硬实时的可靠性无法证明的缺陷.通过提出弹性截止期的概念,定义基于path RTL的弱硬实时系统,有效解决了经典弱硬实时系统可靠性无法证明的难题;实现了弱硬实时系统的约束由时间特性来表达的目标;对于新兴出现的弱硬实时应用提供了完整的解决方案;同时也对经典弱硬实时系统提出了规约算法,以充分利用经典弱硬实时系统在约束规范、调度算法等方面已有研究成果.通过比较,path RTL弱硬实时系统在系统完整性、系统可靠性和应用领域等方面,比经典弱硬实时系统具有优势.     

基于裁剪的弱硬实时调度算法

针对当前弱硬实时调度算法无法保证超过窗口长度的执行序列的满足率达到一定比例的问题,基于(m~-,p)弱硬实时约束,提出了一种基于裁剪的调度算法(cut-down based scheduling,简称CDBS).由于判断(m~-,p)约束是否满足需要遍历任务的整个执行序列,因此判断复杂度很大.为此,提出一种高效的裁剪执行序列的算法,同时证明其正确性,并利用适当的数据结构,使得计算复杂度与序列长度无关,通过实验说明其降低计算复杂度的有效性.进一步与其他经典实时调度算法(EDF(earliest deadline first),DBP(distance-based priority),DWCS(dynamic window constraint schedule))进行比较,验证该算法与其他算法具有相当的性能.     

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.     

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。     

CBS算法的RTAI内核调度器设设

近年来基于双内核架构增强Linux操作系统实时性的RTAI^[1]（Real—Time Application Interface）在工业控制等硬实时领域已经得到了越来越多的应用。本文提出的调度器通过采用基于服务策略的CBS算法对RATI内核下的EDF调度器进行扩展，可以保证分配一定的CPU资源供Linux上的软实时应用，即使在有硬实时任务并发时也能得到处理器资源。实验结果证明了基于CBS算法扩展RTAI内核调度器的正确性。     

现场级硬实时网络在线调度

通过对主要周期和非周期硬实时调度算法的深入研究，提出了一种可用于调度链路数据包的在线硬实时调度系统(ARTCS)。该调度器基于单调比率调度算法：RM、风车调度算法Sr和轮询服务器调度算法，能快速判定可调度性，进而自动生成总线表，使调度算法将数据包作为周期数据包进行调度。ARTCS简单、易用，有效地利用了总线带宽。顺序执行总线表，不仅能保证硬实时的性能，而且避免了消息传输中的中断和阻塞，因而较好地满足了现场总线领域中硬实时通信系统的要求。     

NFRL:一种分布系统的实时容错调度算法

在硬实时系统的应用中,如果硬实时任务不能在规定的时限完成,将会产生人员伤亡, 失等严重后果,为了保证在系统出错的情况下,硬实时任务仍然在能戴止时限之前完成,必须研究实时容错技术。本文从实时容错调度算法的角度出发,提出一种基于分布式系统的实时容错调度算法,并研究了该算法的时间复杂度,同时给出一个实例说明该容错调度算法的调度过程。这种容错调算法称为“无容错需求后调度算法（ＮＦＲＬ）,该实时容错调度算法     

分时EDF算法及其在多媒体操作系统中的应用

提出了一种新的CPU调度算法－－分时EDF（Earliest Deadine First)算法,该算法能保证硬实时任务不丢失死线,并易于在分时系统中实现。以分时EDF算法为基础,提出一种新的CPU层次调度算法－－HRFSFQ,该算法用于多媒体操作系统时能保证各类任务的QoS。最后通过大量实验证明了上述算法的有效性和正确性。     

Scheduling algorithms based on weakly hard real-time constraints

The problem of scheduling weakly hard real-time tasks is addressed in this paper.The paper first analyzes the characters of μ-pattern and weakly hard real-time constraints,then,presents two scheduling algorithms,Meet Any Algorithm and Meet Row Algorithm,for weakly hard real-time systems.Different from traditional algorithms used to guarantee deadlines,MeetAny Algorithm and Meet Row Algorithm can guarantee both deadlines and constraints.Meet Any Algorithm and Meet Row Algorithm try to find out the probabilities of tasks breaking constraints and increase task‘s priority in advance,but not till the last moment.Simulation results show that these two algorithms are better than other scheduling algorithms dealing with constraints and can largely decrease worst-case computation time of real-time tasks.     

端到端(p,k)约束流的实时通讯

端到端系统的实时服务保证问题是当前广泛研究的问题。由于许多端到端应用可以容忍部分报文丢失,因此将窗口约束引入到端到端系统实时服务保证中,但是现有的端到端实时调度算法仅从固定窗口约束出发来保证实时服务,导致其在重度过载情况下性能下降显著。从基于可变窗口的（p,k）约束的角度出发保证实时数据流通过一系列服务器达到目的地的实时服务质量,提出了多跳K窗口约束调度（Multi—hop K—Window Constraint Scheduling,M—KWCS）算法,使其在重度过载下服务质量退化缓慢。实验表明M—KWCS算法在重度过载情况下的性能优于其它各类算法。     

Joint Algorithm of Message Fragmentation and No-Wait Scheduling for Time-Sensitive Networks

Time-sensitive networks(TSNs)support not only traditional best-effort communications but also deterministic communications,which send each packet at a deterministic time so that the data transmissions of networked control systems can be precisely scheduled to guarantee hard real-time constraints.No-wait scheduling is suitable for such TSNs and generates the schedules of deterministic communications with the minimal network resources so that all of the remaining resources can be used to improve the throughput of best-effort communications.However,due to inappropriate message fragmentation,the realtime performance of no-wait scheduling algorithms is reduced.Therefore,in this paper,joint algorithms of message fragmentation and no-wait scheduling are proposed.First,a specification for the joint problem based on optimization modulo theories is proposed so that off-the-shelf solvers can be used to find optimal solutions.Second,to improve the scalability of our algorithm,the worst-case delay of messages is analyzed,and then,based on the analysis,a heuristic algorithm is proposed to construct low-delay schedules.Finally,we conduct extensive test cases to evaluate our proposed algorithms.The evaluation results indicate that,compared to existing algorithms,the proposed joint algorithm improves schedulability by up to 50%.     

Linux核心调度机制的实时改造及应用研究

针对网络多媒体系统的实时应用需求，本文对Linux2．4核心的调度机制进行了改造。通过将弱硬实时调度算法、挪用调度算法、反馈调度算法继承到Linux核心调度机制中，提高了核心的实时性能；最后通过实际应用检验了改造后的Linux系统在处理网络多媒体数据时的实时性能。     

A pre-run-time scheduling algorithm for object-based distributed real-time systems

The most important goal in hard real-time systems is to guarantee that all timing constraints are satisfied. Even though object-based techniques (which contain reusable software components) are used to manage the complexity in the software development process of such systems, execution efficiency may have to be sacrificed, due to the large number of procedure calls and contention for accessing software components. These issues are addressed by the following parallelizing techniques: (a) converting potentially inefficient procedure calls to a source of concurrency via asynchronous remote procedure calls (ARPC) (b) replicating (or cloning) software components to reduce the contention. The existing object-based scheduling algorithms construct an initial schedule and apply incremental parallelization techniques to modify the initial schedule till a feasible schedule is generated. But these algorithms are applicable for scheduling only multiple independent tasks. This paper describes a pre-run-time scheduling algorithm for a set of periodic object-based tasks having precedence constraints among them. The algorithm allocates the components of object-based periodic real-time tasks to the sites of a distributed system based on a clustering heuristic which takes into account the ARPC parallelism and load balancing, and schedules them on respective sites. The algorithm also finds a schedule for communication channel(s). Further, it clones the components of object-based periodic tasks, if contention occurs in accessing them. In addition to the above (periodicity and precedence) constraints, the tasks handled by our algorithm can have resource constraints among them. The experimental evaluation of the algorithm shows that the combination of the proposed clustering heuristic and cloning enhances schedulability.     

基于平滑调度的弱硬实时系统约束规范

约束规范是弱硬实时系统研究的基础。从弱硬实时系统的定义出发,提出了一个新的约束规范,它能够有效实现平滑调度。给出并证明了弱硬实时系统约束规范严格性比较的一个重要定理。业已证明,该约束规范具有良好的性能和较好的适用范围。     

Real-time task scheduling by multiobjective genetic algorithm

Real-time tasks are characterized by computational activities with timing constraints and classified into two categories: a hard real-time task and a soft real-time task. In hard real-time tasks, tardiness can be catastrophic. The goal of hard real-time tasks scheduling algorithms is to meet all tasks’ deadlines, in other words, to keep the feasibility of scheduling through admission control. However, in the case of soft real-time tasks, slight violation of deadlines is not so critical.In this paper, we propose a new scheduling algorithm for soft real-time tasks using multiobjective genetic algorithm (moGA) on multiprocessors system. It is assumed that tasks have precedence relations among them and are executed on homogeneous multiprocessor environment.The objective of the proposed scheduling algorithm is to minimize the total tardiness and total number of processors used. For these objectives, this paper combines adaptive weight approach (AWA) that utilizes some useful information from the current population to readjust weights for obtaining a search pressure toward a positive ideal point. The effectiveness of the proposed algorithm is shown through simulation studies.     

一种能量收集嵌入式系统自适应调度算法

能量收集嵌入式系统(energy harvesting embedded system,简称EHES)的任务调度算法需要考虑能量收集单元的能量输出、能量存储单元的能量水平和能量消耗单元的能耗.实时任务在满足能量约束的条件下,才可能满足时间约束.在这个背景下,传统固定优先级调度算法不再适用于EHES.提出一种基于分组的自适应任务调度算法,它能根据能量收集单元由于能量输出的不确定性而造成的非能量约束情况和能量约束情况,自适应地选择任务调度算法.在非能量约束的情况下,减少任务抢占次数,增强任务的可调度性;在能量约束情况下,减少电池模式切换次数,提高能量存储单元的平均能量水平,从而降低系统能量约束.在一个可进行大范围任务集合仿真的实验环境下对提出的算法进行验证,并将基于分组的自适应调度算法与现有的两个经典算法进行了对比.