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.     

基于确定周期性任务的进程管理及可调度性分析

文中讨论了基于确定周期性任务的实时进程管理,对确定周期性任务采用调度器生成的管理方式,通过截止期递增分类法将非性任务分为两类,分别采用中断内抢占调度和信号调度,提出了改进的最大紧急度优先算法,分析了目标系统的可调度性,给出了春可调度的充要条件。     

Scheduling processes with release times, deadlines, precedence andexclusion relations

An algorithm that finds an optimal schedule on a single processor for a given set of processes is presented. Each process starts executing after its release time and completes its computation before its deadline and a given set of precedence relations and exclusion relations defined on ordered pairs of process segments are satisfied. This algorithm can be applied to the important and previously unsolved problem of automated pre-run-time scheduling of processes with arbitrary precedence and exclusion in hard-real-time systems     

A Feasibility Decision Algorithm for Rate Monotonic and Deadline Monotonic Scheduling

Rate monotonic and deadline monotonic scheduling are commonly used for periodic real-time task systems. This paper discusses a feasibility decision for a given real-time task system when the system is scheduled by rate monotonic and deadline monotonic scheduling. The time complexity of existing feasibility decision algorithms depends on both the number of tasks and maximum periods or deadlines when the periods and deadlines are integers. This paper presents a new necessary and sufficient condition for a given task system to be feasible and proposes a new feasibility decision algorithm based on that condition. The time complexity of this algorithm depends solely on the number of tasks. This condition can also be applied as a sufficient condition for a task system using priority inheritance protocols to be feasible with rate monotonic and deadline monotonic scheduling.     

Dynamic Dispatching of Cyclic Real-Time Tasks with Relative Timing Constraints

In some hard real-time systems, relative timing constraints may be imposed on task executions, in addition to the release time and deadline constraints. Relative timing constraints such as separation or relative deadline constraints may be given between start or finish times of tasks (Gerber et al., 1995; Han and Lin, 1989; Han et al., 1992; Han and Lin, 1992; Han et al., 1996).One approach in real-time scheduling is to find a total order on a set of N tasks in a scheduling window, and cyclically use this order at run time to execute tasks. However, in the presence of relative timing constraints, if the task execution times are nondeterministic with defined lower and upper bounds, it is not always possible to statically assign task start times at pre-runtime for a given task ordering (Gerber et al., 1995).We develop a technique called dynamic cyclic dispatching as an extension of a parametric dispatching mechanism in (Gerber et al., 1995). An ordered set of N tasks is assumed to be given in a scheduling window and this schedule(ordering) is cyclically repeated at runtime in consecutive scheduling windows. Relative timing constraints between tasks may be defined across scheduling window boundaries as well as within one scheduling window. A task set is defined to be dispatchable if there exists any way in which the tasks can be dispatched with all their timing constraints satisfied. An off-line algorithm is presented to check the dispatchability of a task set and to obtain parametric lower and upper bound functions for task start times if the task set is dispatchable. These parametric bound functions are evaluated at runtime to obtain a valid time interval during which a task can be started. The complexity of this off-line component is shown to be O(n ² N ³) where n is the number of tasks in a scheduling window that have relative timing constraints with tasks in the next scheduling window. An online algorithm can evaluate these bounds in O(N) time.Unlike static approaches which assign fixed start times to tasks in the scheduling window, our approach allows us to flexibly manage the slack times at runtime without sacrificing the dispatchability of tasks. Also, a wider class of relative timing constraints can be imposed to the task set compared to the traditional approaches.     

Non-Preemptive Real-Time Scheduling of Multimedia Tasks

Motivated by the special characteristics of multimedia tasks, we consider non-preemptive scheduling of tasks where there exists no (or very limited) information concerning the tasks before they are released. We present impossibility results and analyze algorithms for non-preemptive scheduling in single processor and multiprocessor systems. To evaluate our algorithm we assume that system obtains a value that is proportional to the processing time of the task whenever a task is completed by its deadline. Competitive analysis is used, where the goal is to keep the total value obtained by an on-line algorithm bounded by a function of the total value obtained by an off-line algorithm. In particular, one set of our results considers the competitive ratio of scheduling algorithm when the length of the tasks is not greater than C_max (and not smaller than C_min ). We show that the performance of a scheduling algorithm is improved dramatically when the release time of the tasks is O(C_max) prior to their deadline; achieving a competitive ratio that is close to one.     

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     

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     

Deadline division-based heuristic for cost optimization in workflow scheduling

Cost optimization for workflow applications described by Directed Acyclic Graph (DAG) with deadline constraints is a fundamental and intractable problem on Grids. In this paper, an effective and efficient heuristic called DET (Deadline Early Tree) is proposed. An early feasible schedule for a workflow application is defined as an Early Tree. According to the Early Tree, all tasks are grouped and the Critical Path is given. For critical activities, the optimal cost solution under the deadline constraint can be obtained by a dynamic programming strategy, and the whole deadline is segmented into time windows according to the slack time float. For non-critical activities, an iterative procedure is proposed to maximize time windows while maintaining the precedence constraints among activities. In terms of the time window allocations, a local optimization method is developed to minimize execution costs. The two local cost optimization methods can lead to a global near-optimal solution. Experimental results show that DET outperforms two other recent leveling algorithms. Moreover, the deadline division strategy adopted by DET can be applied to all feasible deadlines.     

Planning virtual infrastructures for time critical applications with multiple deadline constraints

Executing time critical applications within cloud environments while satisfying execution deadlines and response time requirements is challenging due to the difficulty of securing guaranteed performance from the underlying virtual infrastructure. Cost-effective solutions for hosting such applications in the Cloud require careful selection of cloud resources and efficient scheduling of individual tasks. Existing solutions for provisioning infrastructures for time constrained applications are typically based on a single global deadline. Many time critical applications however have multiple internal time constraints when responding to new input. In this paper we propose a cloud infrastructure planning algorithm that accounts for multiple overlapping internal deadlines on sets of tasks within an application workflow. In order to better compare with existing work, we adapted the IC-PCP algorithm and then compared it with our own algorithm using a large set of workflows generated at different scales with different execution profiles and deadlines. Our results show that the proposed algorithm can satisfy all overlapping deadline constraints where possible given the resources available, and do so with consistently lower host cost in comparison with IC-PCP.     

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。     

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.     

DBC性价比资源调度算法

传统的DBC（Deadline and Budget Constrained）调度算法,比如时间最优调度算法、代价最优调度算法都是在时间（deadline）和代价（budget）的约束下,满足时间或代价单方面的QoS需求的极端情况。针对这一不足,提出了一种基于DBC的性价比资源调度算法,综合考虑了时间和代价的QoS需求,目的在于提高任务的完成量以及任务完成的性价比,并通过推理论证和仿真实验验证了该算法的有效性和优越性。     

Multiprocessor scheduling of processes with release times,deadlines, precedence, and exclusion relations

The author presents a scheduling algorithm that solves the problem of finding a feasible nonpreemptive schedule whenever one exists on M identical processors for a given set of processes such that each process starts executing after its release time and completes its computation before its deadline. A given set of precedence relations and a given set of exclusion relations defined on ordered pairs of process segments are satisfied. This algorithm can be applied to the important problem of automated pre-run-time scheduling of processes with arbitrary precedence and exclusion relations on multiprocessors in hard-real-time systems     

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。     

Feasible processor allocation in a Hard-Real-Time environment

Consider the problem of scheduling a set of preemptible tasks in one or more processor systems. The task system consists of a set of independent tasks or a task set with precedence relations. Each task is characterized by execution time and deadline. This article presents scheduling algorithms that guarantee all time constraints. These algorithms are so easy to implement that they can be used in real-time operating systems. An overview is given for the different feasible scheduling algorithms of some task and processor systems.     

Approximation Algorithms for Time-Constrained Scheduling on Line Networks

We consider the problem of time-constrained scheduling of packets in a communication network. Each packet has, in addition to its source and its destination, a release time and a deadline. The goal of an algorithm is to maximize the number of packets that arrive to their destinations by their respective deadlines, given the network constraints.     

一种多重约束下确保成功率的云工作流调度方法

为提高多重约束下的调度成功率,提出一种满足期限和预算双重约束的云工作流调度算法。将可行工作流调度方案求解分解为工作流结构分层、预算分配、期限分配、任务选择和实例选择。工作流结构分层将所有工作流任务划分层次形成包任务,以提高并行执行程度;预算分配对整体预算在层次间进行分割;期限分配将全局期限在不同层次间分割;任务选择基于任务最早开始时间确定优先级,得到任务调度次序;实例选择根据时间和代价均衡因子,获取任务执行最佳实例。仿真结果证明,该算法在调度成功率、同步优化工作流执行时间与执行代价上相较对比算法更好。     

Laxity dynamics and LLF schedulability analysis on multiprocessor platforms

LLF (Least Laxity First) scheduling, which assigns a higher priority to a task with a smaller laxity, has been known as an optimal preemptive scheduling algorithm on a single processor platform. However, little work has been made to illuminate its characteristics upon multiprocessor platforms. In this paper, we identify the dynamics of laxity from the system??s viewpoint and translate the dynamics into LLF multiprocessor schedulability analysis. More specifically, we first characterize laxity properties under LLF scheduling, focusing on laxity dynamics associated with a deadline miss. These laxity dynamics describe a lower bound, which leads to the deadline miss, on the number of tasks of certain laxity values at certain time instants. This lower bound is significant because it represents invariants for highly dynamic system parameters (laxity values). Since the laxity of a task is dependent of the amount of interference of higher-priority tasks, we can then derive a set of conditions to check whether a given task system can go into the laxity dynamics towards a deadline miss. This way, to the author??s best knowledge, we propose the first LLF multiprocessor schedulability test based on its own laxity properties. We also develop an improved schedulability test that exploits slack values. We mathematically prove that the proposed LLF tests dominate the state-of-the-art EDZL tests. We also present simulation results to evaluate schedulability performance of both the original and improved LLF tests in a quantitative manner.     

适用于实例密集型云工作流的调度算法

工作流调度算法仅适用于单个复杂工作流实例,而不适用于实例密集型云工作流实例,为此,提出了基于实例密集型的云工作流调度算法(MCUD)。MCUD算法先对待处理的一组工作流实例进行分类,再对分类后的同类工作流实例采用一种新的分配方法将用户指定的总最后期限分配到各任务;同时,在调度的过程中动态地调整后续任务的子最后期限。MCUD算法对同类工作流实例中的任务分配不同子最后期限,减小了资源竞争,提高了资源的利用率。仿真实验表明,MCUD相比于其他算法,在满足总的最后期限的前提下更进一步地降低了执行成本和执行时间。