基于特定应用的可抢占与不可抢占任务调度算法

根据ASOS的特点和实际实时任务的特性,该文提出了一种建立在RM上的算法：NPT算法。它能很好地实现可抢占与不可抢占任务在单一处理器中的调度,并具有RM算法的一些良好的基本特性,还研究了这种算法的性质,给出并汪明了NPT算法的任务町调度性充分条件。此外,对NPT算法下的最坏响应时间计算也作了论述。     

多次抢占项目调度问题的混合遗传算法

研究多次抢占式资源受限的项目调度问题，假设任意时间点可作为资源抢占节点且抢占次数不受限制，建立满足多次资源抢占的线性整数规划模型并提出改进遗传算法对其进行求解。为克服遗传算法（GA）局部搜索能力缺陷，在算法中引入禁忌搜索（TS）进一步优化子代。针对性地设计了允许多次抢占的基于工作优先级编码策略以及串行调度方案生成机制。通过测试算例集实验调试算法参数，并以标准算例集（Project Scheduling Problem Library，PSPLIB）对算法进行可行性检验。实验结果表明，资源受限项目调度问题中引入多次抢占机制能有效缩减项目工期，设计的算法对问题求解效果良好。     

有中断时间代价的一致并行机抢先调度问题

提出了一种具有中断时间代价的抢先调度问题(P|ptmn(δ)|C_max):在抢先调度中,一个任务发生一次中断,其总的执行时间会增加一个δ.该问题在工程任务分配、分布式计算和网络通信等实际问题中有着广泛的应用背景.证明了这是一个NP-hard问题,给出了一个时间复杂度为O(nlogn+m)的脱线近似算法LPT-Wrap,其近似比小于等于1.40825,并分析了P|ptmn(δ)|C_max的在线特性,给出一个线性时间复杂度的在线近似算法,其竞争比为2.     

Preemptive semi-online scheduling with tightly-grouped processing times

This paper investigates a preemptive semi-online scheduling problem on m identical parallel machines where m = 2,3. It is assumed that all jobs have their processing times in between p and rp (p > 0, r≥1). The goal is to minimize the makespan. Best possible algorithms are designed for any r≥1 when m = 2,3.     

Limited carry-in technique for real-time multi-core scheduling

Schedulability analysis has been widely studied to provide offline timing guarantees for a set of real-time tasks. The so-called limited carry-in technique, which can be orthogonally incorporated into many different multi-core schedulability analysis methods, was originally introduced for Earliest Deadline First (EDF) scheduling to derive a tighter bound on the amount of interference of carry-in jobs at the expense of investigating a pseudo-polynomial number of intervals. This technique has been later adapted for Fixed-Priority (FP) scheduling to obtain the carry-in bound efficiently by examining only one interval, leading to a significant improvement in multi-core schedulability analysis. However, such a successful result has not yet been transferred to any other non-FP scheduling algorithms. Motivated by this, this paper presents a generic limited carry-in technique that is applicable to any work-conserving algorithms. Specifically, this paper derives a carry-in bound in an algorithm-independent manner and demonstrates how to apply the bound to existing non-FP schedulability analysis methods for better schedulability.     

避免模调度中cache代价的优化方法

软件流水能够加快循环的执行速度.模调度是一种被广泛采用的软件流水的启发式.为了改善存储系统,cache使用了分级机制,但这也带来了额外的存储延迟-cache代价.证明了模调度可能导致cache代价,并提出了一种可以避免模调度的cache代价的PCPMS(prevent cache penalty in modulo scheduling)算法.实验结果表明,PCPMS能够避免模调度中的cache代价,提高程序性能.     

Priority Scheduling Versus Pre-Run-Time Scheduling

Builders of real-time systems often use priority scheduling in their systems without considering alternatives. This paper examines one alternative, pre-run-time scheduling, and show that when it can be applied it has significant advantages when compared to priority scheduling schemes.     

基于改进型统一调度算法改善任务集的可调度性

实时系统要求任务在最差情况下能在其截止时间前获得结果,若超过了其截止时间,也会认为是错误的行为,所以改进任务可调度性分析、提高任务集可调度性尤其重要。统一调度能结合固定优先级调度的优点,防止不必要的抢占,降低资源额外销耗,能够提高任务集合的可调度性;但其任务的可调度性分析方法过于粗糙,影响任务最差响应时间分析的结果,降低了任务集的可调度性。针对存在的问题,基于统一调度,增加任务运行阶段数,重新建立任务模型,并提出通过分配任务抢占阈值、调整运行阶段的抢占阈值与长度,优化任务可容忍阻塞,改善任务集可调度性的算法。最后,实验表明,与统一调度算法及其他算法相比,所提出的调度算法能够有效改善任务集的可调度性。     

可靠性代价驱动的实时任务调度算法

1 概述分布式系统越来越广泛地用于重要的实时系统应用程序中,关键问题在于必须保证每个任务在其截止时间之前完成。在许多实时调度算法中调度性是需要最大化的功能目标之一。为了使实时调度算法更实用,必须考虑任务优先权限制。文[11]中提出将离线分析和在线保证结合使用的方案。文[12]提出了一个分布式实时系统中的最佳任务调度算法。上述算法都是为同构分布式系统设计的,均假定系统中的处理器都是一样的,所以不能直接应用于异构分布式系     

基于动态抢占阈值的实时调度

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。     

Cache-Conscious Data Cube Computation on a Modern Processor

As the speed gap between main memory and modern processors continues to widen,the cache behavior becomes more important for main memory database systems(MMDBs).Indexing technique is a key component of MMDBs. Unfortunately,the predominant indexes—B~+-trees and T-trees—have been shown to utilize cache poorly,which triggers the development of many cache-conscious indexes,such as CSB~+-trees and pB~+-trees.Most of these cache-conscious indexes are variants of conventional B~+-trees,and have better cache perf...     

Resource Constraints for Preemptive Job-shop Scheduling

This paper presents an experimental study of constraint propagation algorithms for preemptive scheduling. We propose generalizations of non-preemptive constraint propagation techniques (based on timetables, on disjunctive constraints, and on edge-finding) to preemptive and mixed problems, i.e., problems in which some activities can be interrupted and some cannot. Another approach relies on incremental flow-based techniques. We theoretically compare these approaches and present an experimental comparison based on a branch and bound procedure for the preemptive variant of the job-shop scheduling problem. We show that both edge-finding and flow-based techniques allow the resolution of hard problem instances, including the preemptive variant of the famous FT10.     

Improved Task and Resource Partitioning Under the Resource-Oriented Partitioned Scheduling

Coordinated partitioning and resource sharing have attracted considerable research interest in the field of real-time multiprocessor systems. However, finding an optimal partition is widely known as NP-hard, even for independent tasks. A recently proposed resource-oriented partitioned (ROP) fixed-priority scheduling that partitions tasks and shared resources respectively has been shown to achieve a non-trivial speedup factor guarantee, which promotes the research of coordinated scheduling to a new level. Despite the theoretical elegance, the schedulability performance of ROP scheduling is restricted by the heuristic partitioning methods used in the original study. In this paper, we address the partitioning problem for tasks and shared resources under the ROP scheduling. A unified schedulability analysis framework for the ROP scheduling is proposed in the first place. A sophisticated partitioning approach based on integer linear programming (ILP) is then proposed based on the unified analysis. Empirical results show that the proposed methods improve the schedulability of ROP scheduling significantly, and the runtime complexity for searching a solution is reduced prominently compared with other ILP-based approaches as well.

     

在构件化嵌入式操作系统中应用抢占阈值调度

现有基于构件的嵌入式实时软件开发过程着重于从结构的角度分解系统成若干构件,以及重用构件。实践证明,该开发过程还应从运行角度将构件映射成任务,并选择适当的实时调度算法。为此,根据目前的工程实践提出一种实时构件模型,包含将构件映射成任务的方式。描述了当前构件化嵌入式操作系统可以使用的4种调度算法,并比较这些算法的性能特点。提出抢占阈值(preemptionthreshold)调度模型更适合构件化嵌入式实时系统,仿真实验的结果证明了该结论。比较结果和结论对构件化嵌入式实时系统的设计和开发有一定的参考价值。     

一种新型实时调度算法研究

在许多片上特定应用系统中，任务多且切换频繁，任务切换开销大，有时甚至严重影响系统的可调度性．研究了动态可抢占门限调度算法，它通过初始门限值、动态门限值的计算和优化线程分配，实现了在处理器高利用率下，有效降低任务切换开销的目的，并相应地减少了对内存的需求．动态可抢占门限调度算法是将静态抢占门限算法与动态调度算法有机地结合在一起。完成了由静态到动态无缝转换．     

容错优先级可提升的抢占阈值容错调度算法

基于软件容错模型,提出了允许容错优先级提升的抢占阈值容错调度算法(extended fault-tolerantfixed-priority with preemption threshold,简称FT-FPPT*).该算法能够在抢占式容错调度算法(fault-tolerantfixed-priority preemptive,简称FT-FPP)和抢占阈值容错调度算法(fault-tolerant fixed-priority with preemptionthreshold,简称FT-FPPT)无法提高系统容错能力的情况下,进一步提高系统的容错能力.为了获得系统中任务优先级分配的最佳策略,基于任务最坏响应时间的可调度性分析,提出了一种最优的优先级配置搜索算法(priorityassignment search algorithm,简称PASA).经过深入分析和实验证明,与FT-FPPT算法相比,FT-FPPT*算法能够有效地提高硬实时系统的容错能力.     

Fault-Tolerant Real-Time Scheduling

We use competitive analysis to study how best to use redundancy to achieve fault-tolerance in online real-time scheduling. We show that the optimal way to use spatial redundancy depends on a complex interaction of the benefits, execution times, release times, and latest start times of the jobs. We give a randomized online algorithm whose competitive ratio is O( logΦ log Delta ( log ² n log m/ log log m)) for transient faults. Here n is the number of jobs, m is the number of processors, Φ is the ratio of the maximum value density of a job to the minimum value density of a job, and Δ is the ratio of the longest possible execution time to the shortest possible execution time. We show that this bound is close to optimal by giving an Ω(( log ΔΦ/ log log m) ( log m log log m) ² ) lower bound on the competitive ratio of any randomized algorithm. In the case of permanent faults, there is a randomized online algorithm that has a competitive ratio of O( log Phi log Δ (log m/log log m)). We also show a lower bound of Ω((log ΔΦ/ log log m) ( log m/log log m)) on the competitive ratio for interval scheduling with permanent faults. Received October 1997; revised January 1999.     

基于辅助队列的硬实时混合任务节能调度算法

节能调度是当今实时系统研究的一个重要领域,其中混合实时任务节能调度技术研究刚刚起步.OLDVS算法是非常简洁的硬实时系统在线节能调度算法,但存在以下不足:不适应任务执行的动态变化,不能有效利用动态松弛时间,过于保守以致节能效果并不理想.据此,提出一种新的基于辅助队列的硬实时混合任务节能调度算法(OLDVS-AQ).通过引入一个额外的数据结构即辅助队列(Assisted Queue,AQ)来计算任务的最大完成时间,能够更有效地利用动态松弛时间进一步降低能耗.证明了该算法的可调度性,仿真实验结果表明,OLDVS-AQ算法始终优于OLDVS算法.平均提高约10%的节能效果.     

Cache Aware Pre-Runtime Scheduling

We present a novel pre-runtime scheduling method for uniprocessors which precisely takes the effects of task switching on the processor cache into consideration. Tasks are modelled as a sequence of non preemptable segments with precedence constraints. The cache behavior of each task segment is statically determined by abstract interpretation. For the sake of efficiency, the scheduling algorithm uses a heuristically guided search strategy. Each time a new task segment is added to a partial schedule, its worst case execution time is calculated based on the cache state at the end of the preceding partial schedule.     

云计算中一种多DAG工作流可抢占式调度策略

为解决多用户工作流调度过程中的公平性问题,提高资源利用率,满足不同用户DAG工作流的不同QoS需求,提出了抢占式多DAG工作流动态调度模型。该算法将DAG工作流按照QoS需求进行优先级划分,采用高优先级作业优先占有资源的原则调度作业。相同优先级DAG工作流的任务依据带有启发性信息的slowdown进行资源抢占,进一步提高了作业调度的公平性;对于不同优先级的作业调度,提出了基于阈值的回填算法,该算法在保证作业调度公平的同时提高了资源利用率。