控制系统中实时任务的动态优化调度算法

提出一种新的调度算法——带有非周期服务器的EDF调度算法.分析了所有任务的可调度性,给出了可调度条件,并给出一种新的周期性任务模型以及主优先级和辅助优先级的概念.它们在保证任务可调度的前提下,对周期性任务的采样频率和控制延时进行优化.仿真结果表明,该算法可以提高周期性任务的采样频率,并降低控制延时,即能优化系统的性能.     

控制系统中一种新的周期性任务模型及其优化调度算法

分析了控制系统中的周期任务特性 ,给出了控制系统周期性任务的一种新任务模型 - -周期性任务分解模型 ,它将系统中的控制回路分解为几个子任务 .给出适合此任务模型的调度算法——双优先级调度算法 ,引入了辅助优先级 .该算法能够控制子任务执行顺序和降低控制输入输出延迟 .分析了任务集的可调度性 ,给出了任务集可调度的充分必要条件 .最后讨论了系统性能优化的问题 ,给出了系统性能优化的调度算法     

OPC实时任务系统动态调度算法的研究与设计

本文基于已有的OPCServer实时任务模型,设计了处理混合任务集的动态调度算法(基于截止期优先)和实现方式。该算法实现了对混合任集可调度性的判断,可以完成有硬实时性要求的非周期性任务和周期性任务的调度,并给出了相应的调度结果。     

非抢占式EDF算法下周期性任务的最小相对截止期计算*

现有的求解周期性任务最小相对截止期的方法均假定任务集是采取抢占式EDF调度算法,并不适用于当任务为基于非抢占式EDF调度算法的场合,如实时通信领域。在分析了非抢占式EDF调度算法的可调度性判定条件基础上,提出了基于非抢占式EDF调度算法下周期性任务最小相对截止期的计算算法。算法通过逐渐增加任务的相对截止期直到使任务集变为可调度的方式,实现某个任务相对截止期的最小化。仿真实验表明该算法具有较好的计算复杂度。     

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。     

不可抢占式EDF调度算法的可调度性分析

现有的不可抢占式EDF调度算法的可调度性分析判定条件限定实时任务的截止期必须等于其周期,限制了它的使用范围。论文突破这一限制,提出了更具一般性的可调度性分析判定充要条件。通过对可调度性判定充要条件的分析,提出了基于不可抢占式EDF调度算法的周期性实时系统可调度性分析算法。     

控制系统中周期性任务的静态优化调度算法

分析了控制系统中的周期任务特性，给出了控制系统中周期性任务模型。分析了RMS调度算法任务下的可调度性，给出了求任务响应时间的算法。提出任务调度中系统优化应满足的条件。最后，给出了求优化采样频率的算法和控制系统的静态优化调度算法。     

基于单调速率调度算法的μC/OS-II多任务周期的设计

嵌入式实时操作系统μC/OS-II对于多任务调度采用让就绪表中优先级最高的任务总是处于运行状态,这种策略在周期性多任务的调度中存在着缺陷,可能使得任务的周期设计不当导致任务不能被调度。通过引入单调速率调度算法,在对多个任务设计任务周期时予以分析,确定每个任务都能被调度。     

基于RM调度算法的μC/OS-II多任务周期的设计

嵌入式实时操作系统μC/OS II对于多任务调度采用让就绪表中优先级最高的任务总是处于运行状态，这种策略在周期性多任务的调度中存在着缺陷，可能使得任务的周期设计不当导致任务不能被调度。通过引入单调速率调度算法，在对多个任务设计任务周期时予以分析，确定每个任务都能被调度。     

基于概率的实时任务可调度性分析方法

实时任务可调度分析是保证实时系统正确性的重要手段之一,目前现有的基于周期性任务模型的确定性分析方法比较保守,不适合于多媒体,通讯等软实时系统的可调度性分析,本文提出一个基于概率的分析方法,以概率的形式对系统中实时任务的可调度性进行分析。     

Genetic algorithms for single machine scheduling with time-dependent deterioration and rate-modifying activities

In this paper, the integration of two emerging classes of scheduling problems, the class of scheduling problems with time-dependent deterioration and the class of scheduling problems with rate-modifying activities, are addressed. The scheduling problems have been studied independently. However, the integration of these classes is motivated by human operators of tasks who have fatigue while carrying out the operation of a series of tasks. This situation is also applicable to machines that experience performance degradation over time due to mal-position or mal-alignment of jobs, abrasion of tools, and scraps of operations, etc. It requires maintenance in order to sustain acceptable production rates. We consider the single machine scheduling problem with time-dependent deterioration and multiple RMAs. A mathematical model for an optimal solution to minimize the makespan is derived and genetic algorithms are proposed. The performance of the genetic algorithms is evaluated using randomly generated examples.     

物联网环境下多并发任务分簇调度方法仿真

为全面缓解由网络任务拥堵造成的调度均衡失控问题,提出物联网环境下的多并发任务分簇调度方法。在多并发网络处理架构中,设置具有关联能力的智能任务检测电表,并以电表中的显示数值为依据设计无线任务传输模块,完成多并发任务处理的物联网环境构建。在此基础上,确定任务目标参量,通过提取TDS分簇算子的方式,扩展多并发调度系数,实现物联网环境下多并发任务分簇调度方法的顺利应用。仿真结果显示,应用QoS、DoS、AoS方法后,网络任务的拥堵现状均不能得到有效缓解,且调度均衡参数的最大值与预期标准数值也始终存在较大物理误差,而随着多并发任务分簇调度方法的应用,网络任务拥堵量不断下降,调度均衡参数的实际值也开始出现大幅回升,固有调度均衡失控问题得到有效解决。     

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。     

天基预警系统传感器调度方法

对天基预警系统调度问题进行了研究。在分析预警任务过程与特性的基础上,提出一种基于关键点的任务分解方法,以简化多任务多资源间的复杂可视关系并降低单任务的资源占用量。针对子任务调度问题,提出一种基于复合优先权的求解算法。仿真结果表明提出的任务分解方法和调度算法能够在给定时间内求得理想的调度方案。     

一种新的异构实时分布式系统的容错调度算法

一般来说,异构分布式实时系统中任务的周期并不完全相同且任务的时限不等于它们的周期,同时系统中还有一些无容错需求的任务.因此现有的任务调度算法一般不能满足这些要求.针对这类系统,在结合基版本/副版本技术和EDF算法的基础上,给出了一种新的容错调度算法.该算法由两部分组成：任务分配调度算法和单处理器调度算法.对于单处理器调度算法,本文采用了EDF算法;在此基础上,给出一种启发式静态任务分配算法.分析了系统的可调度性,给出了任务可调度条件和基版本/副版本时限的设置方法.仿真结果表明,这种算法是有效的.     

Development of scheduling strategies with Genetic Fuzzy systems

This paper presents a methodology for automatically generating online scheduling strategies for a complex objective defined by a machine provider. To this end, we assume independent parallel jobs and multiple identical machines. The scheduling algorithm is based on a rule system. This rule system classifies all possible scheduling states and assigns a corresponding scheduling strategy. Each state is described by several parameters. The rule system is established in two different ways. In the first approach, an iterative method is applied, that assigns a standard scheduling strategy to all situation classes. Here, the situation classes are fixed and cannot be modified. Afterwards, for each situation class, the best strategy is extracted individually. In the second approach, a Symbiotic Evolution varies the parameter of Gaussian membership functions to establish the different situation classes and also assigns the appropriate scheduling strategies. Finally, both rule systems will be compared by using real workload traces and different possible complex objective functions.     

Analysis of fork-join program response times on multiprocessors

Models for two processor sharing policies called task scheduling processor sharing and job scheduling processor sharing are developed and analyzed. The first policy schedules each task independently and allows parallel execution of an individual program, whereas the second policy schedules each job as a unit, thereby not allowing parallel execution of an individual program. It is found that task scheduling performs better than job scheduling for most system parameter values. The performance of the task scheduling processor sharing is compared to a first come first serve policy. First come first serve performs better than processor sharing over a wide range of system parameters. Processor sharing performs best when the task service time variability is high. The performance of processor sharing and first come first serve is studied with two classes of jobs, and for when a specific number of processors is statically assigned to each of the classes     

Performance of local search heuristics on scheduling a class of pipelined multiprocessor tasks

This paper presents the evaluation of the solution quality of heuristic algorithms developed for scheduling multiprocessor tasks for a class of multiprocessor architectures designed to exploit temporal and spatial parallelism simultaneously. More specifically, we deal with multi-level or partitionable architectures where MIMD parallelism and multiprogramming support are the two main characteristics of the system. We investigate scheduling a number of pipelined multiprocessor tasks with arbitrary processing times and arbitrary processor requirements in this system. The scheduling problem consists of two interrelated sub-problems, which are finding a sequence of pipelined multiprocessor tasks on a processor and finding a proper mapping of tasks to the processors that are already being sequenced. For the solution of the second problem, various techniques are available. However, the problem remains of generating a feasible sequence for the pipelined operations. We employed three well-known local search heuristic algorithms that are known to be robust methods applicable to various optimization problems. These are Simulated Annealing, Tabu Search, and Genetic Algorithms. We then conduct computational experiments and evaluate the reduction achieved in completion time by each heuristic. We have also compared the results with well-known simple list-based heuristics.     

卫星的智能规划与调度

以对地观测卫星为例，分析卫星的结构功能和飞行任务的特点，并在此基础上建立卫星智能规划与调度系统。规划与调度系统由卫星模型和推理机组成，其中模型描述卫星结构功能和各种约束条件，推理机分析并解决这些约束条件，形成一个没有冲突的飞行计划。规划与调度系统还具有修正计划的能力，能满足任务删除、更改和新任务插入等需求。     

Fault-tolerance through scheduling of aperiodic tasks in hardreal-time multiprocessor systems

Real time systems are being increasingly used in several applications which are time critical in nature. Fault tolerance is an important requirement of such systems, due to the catastrophic consequences of not tolerating faults. We study a scheme that provides fault tolerance through scheduling in real time multiprocessor systems. We schedule multiple copies of dynamic, aperiodic, nonpreemptive tasks in the system, and use two techniques that we call deallocation and overloading to achieve high acceptance ratio (percentage of arriving tasks scheduled by the system). The paper compares the performance of our scheme with that of other fault tolerant scheduling schemes, and determines how much each of deallocation and overloading affects the acceptance ratio of tasks. The paper also provides a technique that can help real time system designers determine the number of processors required to provide fault tolerance in dynamic systems. Lastly, a formal model is developed for the analysis of systems with uniform tasks