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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. 相似文献
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针对最早截止时刻优先(earliest deadline first,EDF)调度算法队头阻塞任务导致资源利用率和配置端口复用率低下的问题,提出一种队头阻塞优化的EDF实时调度算法.通过定义无效阻塞任务并引入无效阻塞任务丢弃策略,提前判定和丢弃无法调度成功的任务,以利于后续任务调度;通过定义队头阻塞任务最早布局成功时刻... 相似文献
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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. 相似文献
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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。 相似文献
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基于动态抢占阈值的实时调度 总被引:8,自引:0,他引:8
具有抢占阈值的调度算法集非抢占调度和纯抢占调度的特点,既减少了由于过多的随意抢占造成的CPU资源浪费,又保证了一定的任务截止期错失率及CPU资源利用率。已有的工作基本集中于讨论任务集完全给定,任务数、任务的优先级及任务的抢占阈值在调度前已完全确定,而且要求不同的任务具有不同的优先级,提出的具有抢占阈值的调度算法,完全放松了对这些条件的限制,即任务的个数不确定,任务的优先级及其抢占阈值在调度过程中可以动态地变化。最后以常用的LSF调度策略为例,结合动态的抢占阈值进行仿真,仿真结果表明,对于不确定的任务集、任务优先级和抢占阈值,利用具有抢占阈值的动态调度算法,降低了任务截止期错失率、提高了CPU的有效使用率。 相似文献
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针对在共享集群中进行任务调度时,无法兼顾任务的响应速度与任务完成时间的问题,提出一种基于截止时间的自适应调度算法。该算法以用户提交的截止时间为依据,根据任务的执行进度自适应地分配适当的计算资源。不同于传统调度方式里由用户提交固定资源参数,该算法在资源约束的情况下会对优先级高的任务进行抢占式调度以保证服务质量(QoS),并在抢占过程结束后额外分配资源补偿被抢占的任务。在Spark平台进行的任务调度实验结果显示,与另一种资源协调者(YARN)框架下的调度算法相比,所提算法能严格地控制短任务的响应速度,并使长作业的任务完成时间缩短35%。 相似文献
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We consider schemes for enacting task share changes—a process called reweighting—on real-time multiprocessor platforms. Our particular focus is reweighting schemes that are deployed in environments in which tasks may frequently request significant share changes. Prior work has shown that fair scheduling algorithms are capable of reweighting tasks with minimal allocation error and that partitioning-based scheduling algorithms can reweight tasks with better average-case performance, but greater error. However, preemption and migration overheads can be high in fair schemes. In this paper, we consider the question of whether non-fair, earliest-deadline-first ( $\mathsf{EDF}$ ) global scheduling techniques can improve the accuracy of reweighting relative to partitioning-based schemes and provide improved average-case performance relative to fair-scheduled systems. Our conclusion is that, for soft real-time systems, global $\mathsf{EDF}$ schemes provide a good mix of accuracy and average-case performance. 相似文献
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模糊动态抢占调度算法 总被引:3,自引:0,他引:3
针对不确定任务特征,提出应用模糊理论进行动态抢占调度,用语言模糊集来描述任务的不确定特征和不同的优先级等级,利用最大隶属度原理确定任务的优先级等级,采用优先调度高优先级等级任务的调度策略提高重要任务的调度成功率,实现具有不确定任务特征的抢占调度,与传统的EDF和LSF算法相比较,仿真表明,所提算法能够提高重要任务的调度成功率,并降低重要任务的截止期错失率;同时,任务间的平均切换次数大大小于LSF的平均切换次数,而与EDF保持相当,该方法可应用于计算机控制系统的控制任务调度,并借鉴于其它具有不确定任务特征或具有有限优先级等级的实时调度问题研究中。 相似文献
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提出了一种基于优先级表设计的调度算法.将任务的相对截止期和空闲时间这两个特征参数结合起来,综合设计任务的优先级表,使得截止期越早或空闲时间越短,任务的优先级越高,而且任务的优先级由相对截止期和空闲时间惟一确定.对于任意一个任务,可通过对设计的优先级表进行二元多点插值获得相应任务的惟一优先级.与传统的EDF和LSF算法进行仿真比较,仿真结果表明,通过优先级表设计方法来确定任务的优先级,提高了任务调度的成功率,降低了任务截止期的错失率.该方法可应用于实时系统中实时任务的动态调度中. 相似文献
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《Advances in Engineering Software》1999,30(1):1-11
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. 相似文献
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讨论了综合考虑任务的截止期和价值两个特征参数的优先级表设计方法,提出了EDV(earliest deadline value)与VED(value earliest deadline)两种不同的基于优先级表的实时任务调度算法,并且利用多重链表给出了这两种算法的实现,包括任务接收策略与任务完成/夭折策略的算法实现.这种优先级表设计方法及其基于多重链表的实现方法也适用于对任务的其他两种甚至3种不同特征参数之间的综合.基于累积实现价值率、加权截止期保证率与差分截止期保证率3个方面,分析了VED算法与EDV算法的性能,实验结果表明,在所有负载条件下VED算法与EDV算法相对于EDF(earliest deadline first)算法与HVF(highest value first)算法都有很大的性能改进. 相似文献
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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 总被引:1,自引:0,他引:1
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. 相似文献
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Ripoll I. Crespo A. Garcia-Fornes A. 《IEEE transactions on pattern analysis and machine intelligence》1997,23(6):388-400
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 相似文献
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在嵌入式实时操作系统中,由单个特征参数作为实时任务优先级的调度依据,并不能较好地描述系统中任务的关键性和紧迫性.提出一种基于组合优先级的自适应实时调度算法(SREDF),综合任务的截止期和CPU运行期设计任务的优先级,使截止期越早且CPU运行期越短的任务拥有最高优先级.处理器能有效地调度相同截止期的实时任务,并提前分析和预测任务能否完成.实验表明,该算法降低了任务调度的截止期错失率(MDP),并提高了任务调度的速度和效率. 相似文献
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Energy efficiency is a major concern in modern high performance computing (HPC) systems and a power-aware scheduling approach is a promising way to achieve that. While there are a number of studies in power-aware scheduling by means of dynamic power management (DPM) and/or dynamic voltage and frequency scaling (DVFS) techniques, most of them only consider scheduling at a steady state. However, HPC applications like scientific visualization often need deadline constraints to guarantee timely completion. In this paper we present power-aware scheduling algorithms with deadline constraints for heterogeneous systems. We formulate the problem by extending the traditional multiprocessor scheduling and design approximation algorithms with analysis on the worst-case performance. We also present a pricing scheme for tasks in the way that the price of a task varies as its energy usage as well as largely depending on the tightness of its deadline. Last we extend the proposed algorithm to the control dependence graph and the online case which is more realistic. Through the extensive experiments, we demonstrate that the proposed algorithm achieves near-optimal energy efficiency, on average 16.4% better for synthetic workload and 12.9% better for realistic workload than the EDD (Earliest Due Date)-based algorithm; The extended online algorithm also outperforms the EDF (Earliest Deadline First)-based algorithm with an average up to 26% of energy saving and 22% of deadline satisfaction. It is experimentally shown as well that the pricing scheme provides a flexible trade-off between deadline tightness and price. 相似文献