单调时限调度算法的可调度分析

单调时限调度通过定义Di≤Ti放宽了单调比率调度对被调度任务集的限制,使之更加近似于工程实际,但现有的单调时限调度的可调度分析的充分条件十分复杂。文章提出并证明了基于最小处理器利用率上限的单调时限调度的充分可调度条件,大大简化了单调时限调度的调度分析。     

The Non-Optimality of the Monotonic Priority Assignments for Hard Real-Time Offset Free Systems

In this paper, we study the problem of scheduling hard real-time periodic tasks with static priority pre-emptive algorithms. We consider tasks which are characterized by a period, a hard deadline, a computation time and an offset (the time of the first request), where the offsets may be chosen by the scheduling algorithm, hence the denomination offset free systems.We study the rate monotonic and the deadline monotonic priority assignments for this kind of system and we compare the offset free systems and the asynchronous systems in terms of priority assignment. Hence, we show that the rate and the deadline monotonic priority assignments are not optimal for offset free systems.     

一种面向部分可重构FPGA的混合实时调度算法

在CPU/FPGA平台上运行的实时任务通常由软/硬件子任务组成并存在优先约束关系。提出了一种软/硬件混合实时任务调度算法。在截止期限错失时刻,通过分析系统的运行情况,推导出实时任务可调度的充分条件。每个实时任务的硬件子任务分成多组,每组硬件子任务重叠配置到FPGA上。通过手工布局硬件子任务端口和总线端口,使得硬件子任务可动态的连接到系统总线上。实验表明,该算法能够满足任务的实时性,充分利用FPGA资源。     

Period sensitivity analysis and D-P domain feasibility region in dynamic priority systems

In the design of a real-time application it is fundamental to know how a change in the task parameters would affect the feasibility of the system. Relaxing the classical assumptions on static task sets with fixed periods and deadlines can give higher resource utilisation and better performance. But the changes on task parameters have to be done always maintaining feasibility. In practice, period and deadline modifications are only necessary on single tasks. Our work focuses on finding the feasibility region of deadlines and periods (called D-P feasibility region) for a single task in the context of dynamic, uniprocessor scheduling of hard real-time systems. This way, designers can choose the optimal deadline and period pairs that best fit application requirements. We provide an exact and an approximated algorithm to calculate this region. We will show that the approximated solution is very close to the exact one and it takes considerably less time.     

一种基于非抢占RM算法的可行性判决算法及应用

为中断服务例程建立了任务模型，在该模型的基础上给出了中断服务例程集使用非抢占RM调度的可行性的充分必要条件，并且基于该条件提出了一种新的非抢占RM算法的可行性判决算法。进一步地，给出了如何改进不可调度例程集的方法，并且将该方法应用到一个具体工程项目中，取得较好的效果。     

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.     

单调比率(RM)调度算法及应用

介绍了任务死线不大于其周期的任务集调度条件分析及算法实现。这种约束条件放松, 有利于周期与非周期任务混合模型调度。同时,分析了以往调度算法中单调比率调度算法约束条件, 并指明了计算时间复杂度的缺点。因而,在RM算法基础之上提出一种实时系统调度算法及实现流 程图,并对提出的现场级实时调度算法进行了对比测试。     

An Analysis of Fixed-Priority Schedulability on a Multiprocessor

A new feasibility test for preemptive scheduling of periodic or sporadic real-time tasks on a single-queue m-server system allows for arbitrary fixed task priorities and arbitrary deadlines. For the special case when deadline equals period and priorities are rate monotonic, any set of tasks with maximum individual task utilization u_max and minimum individual task utilization u_min is feasible if the total utilization does not exceed . Ted Baker received the Ph.D. in Computer Science from Cornell University in 1973. He is a Professor in the Department of Computer Science at the Florida State University, which he chaired from 1998 to 2005. After spending several years doing research in computational complexity theory, he moved on to more practical aspects of computing and has worked in the area of both Ada compilation and real-time systems for the last two decades. A group he organized at FSU in 1979 produced one of the first validated Ada cross-compilers for embedded systems. Since then, he has done research, development, and consulting related to real-time embedded computing, from basic research on scheduling and concurrency control through development of kernels and run-time system support for real-time programming languages. He has also been active in IEEE (POSIX) and ISO standards work related to real-time systems. Dr. Baker was a member of the SEI Rate Monotonic Analysis group, served as real-time area expert for the Ada 9X language mapping and revision team. He directed the FSU teams that developed several software products, including the FSU POSIX threads library, the Florist implementation of IEEE Std 1003.5b-c (the POSIX/Ada API), a set of validation tests for the 1003.5b standards, and the multitasking run-time system for the Gnu Ada (GNAT) compiler. He directed the porting of the latter to several environments, including the Java Virtual Machine and RT Linux. His current research interests are real-time multiprocessor scheduling and real-time device driver architecture.     

基于Linux的多核实时任务调度算法改进

嵌入式实时系统通常被实现为多任务系统,以满足多个外部输入的响应时间的最后期限约束。Linux内核中已经实现了基于EDF(Earliest Deadline First)调度算法的DL调度器,使得实时任务能在截止期限内运行完成。但对于多核处理器,由于实时任务在EDF算法下会出现Dhall效应,论文对 Linux内核中实时任务调度算法进行了改进。在EDF算法的基础上,实现LLF(Least Laxity First)调度算法并对其加以改进,通过降低任务上下文切换频率以及减少松弛度的计算来减小调度过程中的颠簸现象。实验证明该方法既避免了Dhall效应,又减少了任务上下文切换带来的系统开销,并使得任务能在截止期限内完成调度,取得了较好的调度性能。     

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.     

一种改进的RM可调度性判定算法

固定优先级任务可调度性判定是实时系统调度理论研究的核心问题之一.目前已有的各种判定方法可归结为两大类:多项式时间调度判定和确切性判定.多项式时间调度判定通常采用调度充分条件来进行,为此,许多理想条件下基于RM(rate monotonic)调度算法的CPU利用率最小上界被提了出来.确切性判定利用RM调度的充要条件,保证任何任务集均可被判定,并且判定结果是确切的.但是由于时间复杂度较差,确切性判定方法难以实现在线分析.提出了一种改进的RM可调度性判定方法(improved schedulability test algorithm,简称ISTA).首先介绍了任务调度空间这一概念,并提出了二叉树表示,然后进一步提出了相关的剪枝理论.在此基础上,研究了任务之间可调度性的相关性及其对判定任务集可调度性的影响,提出并证明了相关的定理.最后基于提出的定理,给出了一种改进的伪多项式时间可调度性判定算法,并与已有的判定方法进行了比较.仿真结果表明,该算法平均性能作为任务集内任务个数的函数具有显著提高.     

单调速率及其扩展算法的可调度性判定

任务可调度性判定是实时系统调度理论研究的核心问题.单调速率(RM)算法是实时调度的重要算法,自其提出以来已被广泛研究.然而到目前为止,尚缺乏专题性的文章来系统而深入地探讨RM及其扩展算法的可调度性判定,以及各种现实条件和实现方式(包括任务调度的时间开销和任务同步问题等)对可调度性的影响.围绕RM算法下的可调度性判定问题,由浅入深,系统性地讨论各种不同假设和实现方式对可调度性的影响,具体为下述3大类问题：（1）理想的RM算法下的可调度性判定的CPU利用率最小上界最小及可调度的充分必要条件;（2）考虑调度时间开销情况下的可调度性判定条件;（3）优先级反转协议及其对可调度性的影响.给除了具体实例来叙述上述问题,并从算法复杂度和可检测率两方面比较各种算法的优劣。     

T–L plane-based real-time scheduling for homogeneous multiprocessors

We consider optimal real-time scheduling of periodic tasks on multiprocessors—i.e., satisfying all task deadlines, when the total utilization demand does not exceed the utilization capacity of the processors. We introduce a novel abstraction for reasoning about task execution behavior on multiprocessors, called T–L plane and present T–L plane-based real-time scheduling algorithms. We show that scheduling for multiprocessors can be viewed as scheduling on repeatedly occurring T–L planes, and feasibly scheduling on a single T–L plane results in an optimal schedule. Within a single T–L plane, we analytically show a sufficient condition to provide a feasible schedule. Based on these, we provide two examples of T–L plane-based real-time scheduling algorithms, including non-work-conserving and work-conserving approaches. Further, we establish that the algorithms have bounded overhead. Our simulation results validate our analysis of the algorithm overhead. In addition, we experimentally show that our approaches have a reduced number of task migrations among processors when compared with a previous algorithm.     

Utilization Bounds for EDF Scheduling on Real-Time Multiprocessor Systems

The utilization bound for earliest deadline first (EDF) scheduling is extended from uniprocessors to homogeneous multiprocessor systems with partitioning strategies. First results are provided for a basic task model, which includes periodic and independent tasks with deadlines equal to periods. Since the multiprocessor utilization bounds depend on the allocation algorithm, different allocation algorithms have been considered, ranging from simple heuristics to optimal allocation algorithms. As multiprocessor utilization bounds for EDF scheduling depend strongly on task sizes, all these bounds have been obtained as a function of a parameter which takes task sizes into account. Theoretically, the utilization bounds for multiprocessor EDF scheduling can be considered a partial solution to the bin-packing problem, which is known to be NP-complete. The basic task model is extended to include resource sharing, release jitter, deadlines less than periods, aperiodic tasks, non-preemptive sections, context switches, and mode changes.     

一种静态优先级保序饱和分配算法

在通信、雷达、导航以及各种消费类电子产品等领域,嵌入式实时调度已逐渐成为电子电气系统的控制核心,成本与性价比都是设计者需要考虑的重要内容.实际应用中,系统能够支持的优先级教目是有限的,当任务数目多于系统优先级数目时,RM,DM等优先级非受限最优算法尽管已经不再适用,但是仍然可以作为任务的自然优先级来辅助系统设计.利用自然优先级先验知识,提出一种保序饱和分配算法,用于任意截止期模型的最优保序分配.进一步的研究表明,当所有任务周期不小于其相对截止时间时,DM保序饱和分配是最少优先级分配.本算法复杂度低,可调度的判定总次数等于任务总数,远低于AGP和LNPA.     

Sporadic task scheduling with overload conditions

Hard real-time task scheduling in a dynamic environment has been an important area of research, posing difficult problems. In an overloaded system where periodic and sporadic tasks have computational demands that are greater than the CPU time in that interval, the scheduler faces the question of which tasks must really make their deadlines. Assuming that periodic tasks have priority over sporadic ones, we end up with a system where some sporadic tasks may not make their deadlines. It is known that through the assignment of priorities to tasks based on the earliest deadline policy, there is no way to predict which sporadic task will miss the deadline and which will not. In order to prevent important sporadic tasks from missing their deadlines, we assign each task an importance function that is used by the scheduling algorithm. Generally, the summation of important function values must be maximized to allow the most important tasks to meet their timing constraints. We present two novel scheduling algorithms that try to maximize this summation. We show that these algorithms have better performance compared to related algorithms regarding complexity and benefit optimization.     

分布式控制系统中多种混合任务的容错调度

分布式控制系统中存在有强实时、软实时和非实时等多种实时性的任务,其中强实时任务必须在其时限前完成,否则会出现灾难性后果,因此必须为分布式控制系统提供一定的容错能力。首先给出了用于调度多种实时性任务的单处理器调度算法——双优先级队列调度算法,并分析算法的可调度性条件。针对分布式控制系统,考虑基版本与副版本的执行时间不同时,结合版本复制技术和单处理器调度算法提出了一种新的容错调度算法。分析了算法的可调度行,给出了可任务集的可调度条件判断方法和基版本任务时限的设置方法。在此基础上,采用启发式静态任务分配算法,保证各处理器的负载均衡。本算法在保证任务容错可调度的条件下,可提高系统中各处理器的利用率,仿真结果表明该算法是有效的。     

静态实时中间件的优先级映射问题

使用截止期单调(DM)调度算法和分布式优先级冲顶资源访问控制协议(DPCP)的实时CORBA系统中,当节点的本地优先级个数不足时,必须将多个全局优先级映射成一个本地优先级.这需要:①判定映射后任务可调度性的充分必要条件;②减少时间复杂度的映射算法.为此,推导出判定条件,确定了DGPM映射算法.该算法在保证系统可调度的前提下分配任务,或者证明映射后系统不可调度.证明了DGPM算法能调度其他直序列优先级映射算法可调度的任务和GCS集合.判定条件和算法在实际项目中得到了应用.     

多特征参数的任务模糊调度算法

针对任务具有特征参数多和特征参数不确定性的特点,提出了一种基于模糊理论的任务调度算法。利用模糊集合来描述任务的不确定性特征;使用多层模糊综合评判和最大隶属度原理来综合考虑任务的多个特征参数并确定任务的优先级;采用动态构建多层评判模型的调度策略来减小任务优先级评判的失效率。仿真表明,该算法提高了任务调度的成功率,降低了任务截止期的错失率和任务优先级评判的失效率。该方法可应用于优先等级有限的实时系统任务动态调度中。     

On-line scheduling of scalable real-time tasks on multiprocessor systems

The computation time of scalable tasks depends on the number of processors allocated to them in multiprocessor systems. As more processors are allocated to a scalable task, the overall computation time of the task decreases but the total amount of processors’ time devoted to the execution of the task, called workload, increases due to parallel execution overhead. In this paper, we propose a task scheduling algorithm that utilizes the property of scalable tasks for on-line and real-time scheduling. In the proposed algorithm, the total workload of all scheduled tasks is reduced by managing processors allocated to the tasks as few as possible without missing their deadlines. As a result, the processors in the system have less load to execute the scheduled tasks and can execute more newly arriving tasks before their deadlines. Simulation results show that the proposed algorithm performs significantly better than the conventional algorithm based on a fixed number of processors to execute each task.