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With traditional open-loop scheduling of network resources, the quality-of-control (QoC) of networked control systems (NCSs) may degrade significantly in the presence of limited bandwidth and variable workload. The goal of this work is to maximize the overall QoC of NCSs through dynamically allocating available network bandwidth. Based on codesign of control and scheduling, an integrated feedback scheduler is developed to enable flexible QoC management in dynamic environments. It encompasses a cascaded feedback scheduling module for sampling period adjustment and a direct feedback scheduling module for priority modification. The inherent characteristics of priority-driven control networks make it feasible to implement the proposed feedback scheduler in real-world systems. Extensive simulations show that the proposed approach leads to significant QoC improvement over the traditional open-loop scheduling scheme under both underloaded and overloaded network conditions. 相似文献
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In this note, we revisit the problem of scheduling stabilizing control tasks on embedded processors. We start from the paradigm that a real-time scheduler could be regarded as a feedback controller that decides which task is executed at any given instant. This controller has for objective guaranteeing that (control unrelated) software tasks meet their deadlines and that stabilizing control tasks asymptotically stabilize the plant. We investigate a simple event-triggered scheduler based on this feedback paradigm and show how it leads to guaranteed performance thus relaxing the more traditional periodic execution requirements. 相似文献
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随着家庭网络中的多媒体服务器和实时数据库服务器这类应用对实时的灵活性的要求不断增加,传统实时基于最长执行时间(WCET)的调度算法已经不能满足它们对性能优化的要求.因此,产生了一些软实时的调度算法来解决这些问题.提出了一种由反馈环节控制的实时调度算法,该算法用于调度能使用不精确计算模型描述的进程.算法可以在各种负载条件下,通过在调度过程中引入的反馈控制,在计算精度和计算时间上直接取得折衷,将进程错过时限的比例控制在预定范围内. 相似文献
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I/O调度算法对磁盘阵列(RAID)性能具有至关重要的影响。虽然已有很多典型的I/O调度算法在一定负载情况下可获得较好的性能,但很难有哪一种算法在各种负载情况下均能获得很好的性能。本文提出了一种智能RAID控制模型,结合C4.5决策树和AdaBoost算法实现负载自动分类,根据负载变化和性能反馈情况动态调整I/O调度策略,实现面向应用需求的自治调度。模拟实验结果表明,自适应调度算法具有较好的适应性,在各种负载情况下优于现有的I/O调度算法,尤其适用于多线程混合负载环境的I/O性能优化。 相似文献
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针对嵌入式实时系统在系统负载模型不确定的情况下系统的实时任务错过率过高以及调度稳定性差的问题,提出了一个基于反馈控制的调度模型.该模型主要由改进的多级队列调度器和3个控制器(准入控制器、执行等级控制器、比例积分微分(PID)控制器)组成.任务的错过率偏差反馈到PID控制器,产生相应的调整量并作用于其他两个控制器,对实时任务的执行等级进行调整, 经过调整的任务被调度器调度执行.在对模型中每个部件进行了一些结构调整和改进设计之后,将该调度模型应用于嵌入式可配置操作系统(eCos)中.实验结果表明,该模型降低了任务的时限错过率,同时解决了系统频频超载的问题. 相似文献
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Thomas A. Wagner Anita Raja Victor R. Lesser 《Autonomous Agents and Multi-Agent Systems》2006,13(3):235-292
Open environments are characterized by their uncertainty and non-determinism. Agents need to adapt their task processing to available resources, deadlines, the goal criteria specified by the clients as well their current problem solving context in order to survive in these environments. If there were no resource constraints, then an optimal Markov Decision Process based policy would obviously be the best way for complex problem solving agents to make scheduling decisions. However in many agent systems, these scheduling decisions have to be made on-line or in soft real-time, making the off-line policy computationally infeasible in open environments. The hybrid planner/scheduler used to control Task Analysis, Environment Modeling, and Simulation (TÆMS) agents is the Design-to-Criteria (DTC) agent scheduler. Design-to-Criteria scheduling is the soft real-time process of custom building a plan/schedule to meet an agent’s current objectives which are expressed as dynamic goal criteria (including real-time deadlines), using task models that describe alternate ways to achieve tasks and subtasks. Recent advances in Design-to-Criteria control include the addition of uncertainty to the TÆMS computational task models analyzed by the scheduler and the incorporation of uncertainty in the scheduling process. As we show, the use of uncertainty in TÆMS and Design-to-Criteria enables agents to make better control decisions in uncertain environments. Design-to-Criteria uses a heuristic approach for on-line scheduling of medium granularity tasks.It approximates the analysis used to generate an optimal policy by heuristically reasoning about the implications of uncertainty in task execution. The addition of uncertainty has also spawned a post-scheduling contingency analysis step for situations in which an agent must produce a result by a given deadline (deadline critical situations) and where the added computational cost is worth the expense. We describe the uncertainty representation in TÆMS and how it improves task models and the scheduling process, and provide empirical examples of reasoning about uncertainty in action. We also evaluate the performance of our heuristic-based approach to agent control using the performance of the policy generated by an optimal controller as the benchmark. 相似文献
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Many embedded systems are constrained by limits on power consumption, which are reflected in the design and implementation
for conserving their energy utilization. Dynamic voltage scaling (DVS) has become a promising method for embedded systems
to exploit multiple voltage and frequency levels and to prolong their battery life. However, pure DVS techniques do not perform
well for systems with dynamic workloads where the job execution times vary significantly. In this paper, we present a novel
approach combining feedback control with DVS schemes targeting hard real-time systems with dynamic workloads. Our method relies
strictly on operating system support by integrating a DVS scheduler and a feedback controller within the earliest-deadline-first
(EDF) scheduling algorithm. Each task is divided into two portions. The objective within the first portion is to exploit frequency
scaling for the average execution time. Static and dynamic slack is accumulated for each task with slack-passing and preemption
handling schemes. The objective within the second portion is to meet the hard real-time deadline requirements up to the worst-case
execution time following a last-chance approach. Feedback control techniques make the system capable of selecting the right
frequency and voltage settings for the first portion, as well as guaranteeing hard real-time requirements for the overall
task. A feedback control model is given to describe our feedback DVS scheduler, which is used to analyze the system's stability.
Simulation experiments demonstrate the ability of our algorithm to save up to 29% more energy than previous work for task
sets with different dynamic workload characteristics.
This work was supported in part by NSF grants CCR-0208581, CCR-0310860 and CCR-0312695.
Preliminary versions of parts of this work appeared in the ACM SIGPLAN Joint Conference Languages, Compilers, and Tools for
Embedded Systems (LCTES'02) and Software and Compilers for Embedded Systems (SCOPES'02) (Dudani et al., 2002), in the Workshop
on Compilers and Operating Systems for Low Power 2002 (Zhu and Mueller, 2002) and in the IEEE Real-Time Embedded Technology
and Applications Symposium 2004 (Zhu and Mueller, 2004a). 相似文献
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A scheduling architecture for real-time control tasks is proposed. The scheduler uses feedback from execution-time measurements and feedforward from workload changes to adjust the sampling periods of the control tasks so that the combined performance of the controllers is optimized. The performance of each controller is described by a cost function. Based on the solution to the optimal resource allocation problem, explicit solutions are derived for linear and quadratic approximations of the cost functions. It is shown that a linear rescaling of the nominal sampling frequencies is optimal for both of these approximations. An extensive inverted pendulum example is presented, where the performance obtained with open-loop, feedback, combined feedback and feedforward scheduling, and earliest-deadline first scheduling are compared. The performance under earliest-deadline first scheduling is explained by studying the behavior of periodic tasks under overload conditions. It is shown that the average values of the sampling periods equal the nominal periods, rescaled by the processor utilization. 相似文献
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Model predictive control (MPC) could not be reliably applied to real-time control systems because its computation time is not well defined. Implemented as anytime algorithm, MPC task allows computation time to be traded for control performance, thus obtaining the predictability in time. Optimal feedback scheduling (FS-CBS) of a set of MPC tasks is presented to maximize the global control performance subject to limited processor time. Each MPC task is assigned with a constant bandwidth server (CBS), whose reserved processor time is adjusted dynamically. The constraints in the FS- CBS guarantee scheduler of the total task set and stability of each component. The FS-CBS is shown robust against the variation of execution time of MPC tasks at runtime. Simulation results illustrate its effectiveness. 相似文献
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Tengli Wang Chuan Zhou Hui Lu Junda He Jian Guo 《International Journal of Control, Automation and Systems》2018,16(1):197-206
A novel co-design scheme of hybrid scheduling strategy, adaptive logarithmic quantizer and dynamic robust H-infinity output feedback controller for a class of networked control system (NCS)with communication constraints and time delay is proposed. The hybrid scheduling scheme integrates dead zone scheduling and Try Once Discard (TOD) scheduling so as to get the stronger adaptability and flexibility than the single scheduling. In this scheme, dead zone scheduling which updates the threshold according to mode-dependent control strategy is used for single node of NCS to reduce the network bandwidth utilization while TOD scheduling is used for the whole node of NCS in order to meet the requirements of communication constraints and guarantee the overall system performance.We develop the integrated design for the hybrid scheduling strategy, adaptive quantizer and dynamic robust output feedback controller to maintain asymptotic stability of the closed-loop NCS by using the multiple-Lyapunov function and switched system theory. The proposed method can improve the the quality of service (QoS) meanwhile ensure the quality of control (QoC) of overall systems, which make a better trade-off between network utilization and control performance. An simulation example demonstrates the efficiency of the proposed method. 相似文献
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Energy consumption is a critical design issue in embedded systems, especially in battery-operated systems. Maintaining high
performance while extending the battery life is an interesting challenge for system designers. Dynamic voltage scaling and
dynamic frequency scaling allow us to adjust supply voltage and processor frequency to adapt to the workload demand for better
energy management. Because of the high complexity involved, most solutions depend on heuristics for online power-aware real-time
scheduling or offline time-consuming scheduling. In this paper, we discuss how we can apply pinwheel model to power-aware
real-time scheduling so that task information, including start times, finish times, preemption times, etc, can be efficiently
derived using pinwheel model. System predictability is thus increased and under better control on power-awareness. However,
job execution time may be only a small portion of its worst case execution time and can only be determined at runtime. We
implement a profiling tool to insert codes for collecting runtime information of real-time tasks. Worst case execution time
is updated online for scheduler to perform better rescheduling according to actual execution. Simulations have shown that
at most 50% energy can be saved by the proposed scheduling algorithm. Moreover, at most additional 33% energy can be saved
when the profiling technique is applied.
This paper is an extended version of the paper Power-Aware Real-Time Scheduling using Pinwheel Model and Profiling Technique
that appeared in the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications. 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