实时调度算法分类研究

调度是实时系统的一个研究热点。一个调度算法的好坏决定着实时任务能否在规定的时限内完成。本文对实时调度进行了讨论;研究了经典静态调度算法中的速率单调调度算法,并提出了对该算法的改进;分析了动态调度中的最早截止期最优先算法;最后,对实时调度研究策略方向进行了展望。     

RTLinux实时调度算法的改进与实现

为提高RTLinux的实时调度性能,分析了RTLinux的工作原理,针对其现有调度算法的不足,提出了改进的最小裕度优先算法,有效减少了颠簸现象,提高了算法性能.深入分析了RTLinux下ILLF调度器的实现,提高了CPU的使用率,增强了系统调度性能,并通过程序验证和调度器仿真,验证了算法的可行性和有效性.     

基于RM与EDF的实时混合调度算法研究

通过对实时系统中静态调度算法RM和动态调度算法EDF的研究与分析,针对两种调度算法在实际应用中的问题,提出了一种基于阈值δ的混合调度算法,将RM与EDF调度算法相结合,并从数学角度描述了混合调度算法的可调度性与实时任务的周期、执行时间等属性之间的关系,给出了混合调度算法可调度性的充分必要条件。最后用实验验证了混合调度算法的有效性。     

实时中间件动态调度算法的研究及应用

文章建立了实时中间件OPC服务器的实时调度模型,设计了处理混合任务的动态调度算法(基于EDF)和实现方式,分析了算法的可调度性和非周期任务的响应性能及参数设计,并给出了相应的调度结果。     

基于反馈控制的实时调度算法设计与实现

传统的实时调度算法在运行环境不可预测的嵌入式操作系统中应用时,要求系统预留大量的CPU资源,而且在稳定性和精确性等方面存在不足.文章为解决这些问题提出了基于反馈控制的实时调度算法,仿真表明该算法相对传统算法而言,提高了系统的CPU利用率,并降低了任务的截止期限错过率.     

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。     

基于组合优先级的自适应实时调度算法研究

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.     

模糊反馈控制实时调度算法

为了解决模糊不确定任务集在不可预测环境下的动态抢占调度问题,应用模糊规则和模糊调度理论,提出一个基于模糊反馈控制的调度算法,并建立相应的调度架构.该架构由基本调度器和模糊反馈控制两部分组成.用模糊调度算法作为基本调度器的调度算法,将任务集按不同优先级等级进行划分,优先级等级高的任务优先调度,从而使得更多的重要任务得到调度;模糊控制器与任务流调节策略一起构成模糊反馈控制部分.仿真结果表明,模糊反     

多特征协调的实时调度算法

目前大多数实时调度算法都依据单一的特征参数确定任务优先级,本文提出一种基于多特征协调的实时调度算法,对特定高优先级任务优先处理,并且对其他任务的调度不产生任何影响。同时,在系统超载的时候,有效避免了EDF算法性能的急剧下降。实验结果表明,该算法有效地保证了特定任务的调度优先级,相对于EDF算法性能有明显改进。     

网络化运动控制系统的经典调度算法应用研究

网络化运动控制系统作为一类特殊的实时系统,其系统的性能与资源（处理器、网络）的调度密切相关,将实时调度理论应用于网络化运动控制系统非常必要。在对用于单处理器的经典实时调度算法（RM和EDF）以及网络调度的研究现状进行综述的基础上,对网络调度和任务调度的异同点及网络调度的实现方法和应用技术进行了研究。最后,对RM和EDF两类调度算法在网络化运动控制系统中的应用及调度优化问题进行了仿真研究。     

Cache-conscious off-line real-time scheduling for multi-core platforms: algorithms and implementation

Real-Time Systems - Most schedulability analysis techniques for multi-core architectures assume a single worst-case execution time (WCET) per task, which is valid in all execution conditions. This...     

Value-based scheduling in real-time database systems

In a real-time database system, an application may assign avalue to a transaction to reflect the return it expects to receive if the transaction commits before its deadline. Most research on real-time database systems has focused on systems where all transactions are assigned the same value, the performance goal being to minimize the number of missed deadlines. When transactions are assigned different values, the goal of the system shifts to maximizing the sum of the values of those transactions that commit by their deadlines. Minimizing the number of missed deadlines becomes a secondary concern. In this article, we address the problem of establishing a priority ordering among transactions characterized by both values and deadlines that results in maximizing the realized value. Of particular interest is the tradeoff established between these values and deadlines in constructing the priority ordering. Using a detailed simulation model, we evaluate the performance of several priority mappings that make this tradeoff in different, but fixed, ways. In addition, a bucket priority mechanism that allows the relative importannce of values and deadlines to be controlled is introduced and studied. The notion of associating a penalty with transactions whose deadlines are not met is also briefly considered.When this work was done he was with the Computer Sciences Department, University of Wisconsin-Madison.     

Performance evaluation of two new disk scheduling algorithms for real-time systems

In this paper, we present two new disk scheduling algorithms for real-time systems. The two algorithms, called SSEDO (Shortest Seek and Earliest Deadline by Ordering) and SSEDV (Shortest Seek and Earliest Deadline by Value), combine deadline information and disk service time information in different ways. The basic idea behind these new algorithms is to give the disk I/O request with the earliest deadline a high priority, but if a request with a larger deadline is very close to the current disk arm position, then it may be assigned the highest priority. The performance of the SSEDO and SSEDV algorithms is compared with three other proposed real-time disk scheduling algorithms ED, P-SCAN, and FD-SCAN, as well as four conventional algorithms SSTF, SCAN, C-SCAN, and FCFS. An important aspect of the performance study is that the evaluation is not done in isolation with respect to the disk, but as part of an integrated collection of protocols necessary to support a real-time transaction system. The transaction system model is validated on an actual real-time transaction system testbed, called RT-CARAT. The performance results show that SSEDV outperforms SSEDO; that both of these new algorithms can improve performance of up to 38% over previously-known real-time disk scheduling algorithms; and that all of these real-time scheduling algorithms are significantly better than nonreal-time algorithms in the sense of minimizing the transaction loss ratio.This work is supported, in part, by the Office of Naval Research under contract N00014-87-K-796, by NSF under contract IRI-8908693, and by an NSF equipment grant CERDCR 8500332.     

Time-constrained project scheduling

We propose a new approach for scheduling with strict deadlines and apply this approach to the Time-Constrained Project Scheduling Problem (TCPSP). To be able to meet these deadlines, it is possible to work in overtime or hire additional capacity in regular time or overtime. For this problem, we develop a two stage heuristic. The key of the approach lies in the first stage in which we construct partial schedules. In these partial schedules, jobs may be scheduled for a shorter duration than required. The second stage uses an ILP formulation of the problem to turn a partial schedule into a feasible schedule, and to perform a neighborhood search. The developed heuristic is quite flexible and, therefore, suitable for practice. We present experimental results on modified RCPSP benchmark instances. The two stage heuristic solves many instances to optimality, and if we substantially decrease the deadline, the rise in cost is only small.     

Efficient scheduling algorithms for real-time multiprocessorsystems

Efficient scheduling algorithms based on heuristic functions are developed for scheduling a set of tasks on a multiprocessor system. The tasks are characterized by worst-case computation times, deadlines, and resources requirements. Starting with an empty partial schedule, each step of the search extends the current partial schedule by including one of the tasks yet to be scheduled. The heuristic functions used in the algorithm actively direct the search for a feasible schedule, i.e. they help choose the task that extends the current partial schedule. Two scheduling algorithms are evaluated by simulation. To extend the current partial schedule, one of the algorithms considers, at each step of the search, all the tasks that are yet to be scheduled as candidates. The second focuses its attention on a small subset of tasks with the shortest deadlines. The second algorithm is shown to be very effective when the maximum allowable scheduling overhead is fixed. This algorithm is hence appropriate for dynamic scheduling in real-time systems     

实时协同的调度算法研究

研究了目前流行的实时调度技术,归纳总结了不同调度技术下的典型调度算法,介绍了实时调度算法的调度规则、调度特点、适用场合以及需要解决的问题,分析了典型商业实时操作系统中的调度技术,提出了增强操作系统实时性能需要解决的技术问题,为将优秀的实时调度算法应用在实时操作系统中奠定了理论基础。     

模糊数据流实时任务调度算法

针对数据流系统中实时查询任务的特点,提出了基于模糊综合评判的动态优先级调度算法。用语言模糊集描述任务的不确定性因素和不同的优先等级,利用最大隶属度原理确定任务的优先等级。算法充分考虑了任务的持续周期性、任务之间存在依赖关系与共享滑动窗口的特点对任务优先级的影响。从累积实现价值率、差分截止期保证率和CPU切换频率3个方面测试了算法的性能,实验表明所提出算法相对于HVF算法、LSF算法、模糊动态抢占调度算法都有很大的改进。     

Implications of classical scheduling results for real-time systems

Knowledge of complexity, fundamental limits and performance bounds-well known for many scheduling problems-helps real time designers choose a good design and algorithm and avoid poor ones. The scheduling problem has so many dimensions that it has no accepted taxonomy. We divide scheduling theory between uniprocessor and multiprocessor results. In the uniprocessor section, we begin with independent tasks and then consider shared resources and overload. In the multiprocessor section, we divide the work between static and dynamic algorithms     

Parallel median filtering algorithms and their real-time implementation

The article presents a brief survey of parallel median filtering algorithms with their running time characteristics. Some real-time hardware implementations of the algorithms are described.Translated from Kibernetika, No. 5, pp. 105–109, September–October, 1989.