一种任务优先级的综合设计方法

提出了一种基于优先级表设计的调度算法.将任务的相对截止期和空闲时间这两个特征参数结合起来,综合设计任务的优先级表,使得截止期越早或空闲时间越短,任务的优先级越高,而且任务的优先级由相对截止期和空闲时间惟一确定.对于任意一个任务,可通过对设计的优先级表进行二元多点插值获得相应任务的惟一优先级.与传统的EDF和LSF算法进行仿真比较,仿真结果表明,通过优先级表设计方法来确定任务的优先级,提高了任务调度的成功率,降低了任务截止期的错失率.该方法可应用于实时系统中实时任务的动态调度中.     

一种严格按比例派发服务的混合实时调度算法

在混合实时系统中,调度器必须既保证所有硬实时任务严格按照其时间约束在截止期内完成,又要尽可能地提高软实时任务和非实时任务的服务质量.提出了一种严格按比例派发服务器算法(RPDS),并以此为基础构建了一种层次式调度框架.RPDS将处理器时间流分成连续的小段,并在每一小段中强制为非硬实时任务分配一个时间片.实验结果表明,RPDS可以合理地为各种类型应用分配处理器时间,并且降低了实时任务的截止期错失率.     

基于多传感器的控制系统实时调度算法

将简单反馈控制与任务准入/回归、可达/夭折等策略相结合,设计新的动态调度框架。在此基础上,综合截止期、关键度和最坏执行时间3种特征参数,提出基于反馈控制的混合策略调度算法,该算法也适用于对任务的其他多种特征参数的综合。从截止期错失率、错失任务平均关键度和CPU有效利用率3个方面,分析算法的性能。实验结果表明,该算法在混合任务和动态负载下与最早截止期优先和最高价值优先算法相比具有更好的性能。     

多特征参数的任务模糊调度算法

针对任务具有特征参数多和特征参数不确定性的特点,提出了一种基于模糊理论的任务调度算法。利用模糊集合来描述任务的不确定性特征;使用多层模糊综合评判和最大隶属度原理来综合考虑任务的多个特征参数并确定任务的优先级;采用动态构建多层评判模型的调度策略来减小任务优先级评判的失效率。仿真表明,该算法提高了任务调度的成功率,降低了任务截止期的错失率和任务优先级评判的失效率。该方法可应用于优先等级有限的实时系统任务动态调度中。     

副版本不可抢占的全局容错调度算法

容错是硬实时系统的关键能力,容错调度算法可以在有错误发生的情况下满足任务的实时性需求.在主副版本机制的容错调度算法中,主版本出错后留给副版本运行的时间窗口小,副版本容易错失截止期.针对副版本需要快速响应的问题,提出副版本不可抢占的全局容错调度算法FTGS-NPB（fault-tolerant global scheduling with non-preemptive backups）,赋予副版本全局最高优先级,使副版本在主版本出错后可以立刻获得处理器资源,并且在运行过程中不会被其他任务抢占.这样,副版本可以在最短时间内响应.分别基于截止期分析和响应时间分析建立了FTGS-NPB的可调度性测试,并分析了两种可调度性测试分别适用于不同的优先级分配算法.仿真实验结果表明,FTGS-NPB可以有效地减少实现容错的代价.     

基于检查点机制的容错实时调度算法CP-PRA

时间冗余作为容错的重要手段被广泛应用于安全关键实时系统中。传统容错调度算法为失败任务的重运行(Re-execute)预留了大量的空闲时间，但是重运行的使用会降低系统的资源利用率。提出了一种基于检查点机制的容错调度算法CP-PRA，通过降低错误恢复需要的时间，可以有效地提高系统的资源利用率。给出了该算法的可调度奈件，并证明了其算法的正确性。     

一种混合优先级的防危调度算法

为增强实时系统任务过载时的防危性,提出一种混合优先级的防危调度算法,其优先级由相对截止期优先级和相对松弛度优先级组成,通过相对松弛度预测任务的可完成性,并采用完全抢占方式防止处理器资源的竞争抖动。仿真结果表明,该算法可充分利用处理器资源,能在发生瞬时过载时有效降低任务的截止期错失率。     

硬实时系统中基于软件容错模型的容错调度算法

在硬实时系统中,由于任务超时完成将会导致灾难性后果,因此硬实时系统必须具有实时性和可靠性保障.软件容错模型是提高硬实时系统容错能力的一种有效方法.针对硬实时系统中容错优先级两种分配策略存在的不足,基于软件容错模型提出了一种容错优先级可提升的双重优先级分配策略.该方法通过为替代版本分配双重优先级,不仅能够提高硬实时系统的容错能力,同时还能够显著减少任务间的抢占次数.为了获得双重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,首先提出了一种最大的双重优先级配置搜索算法(MDPCSA).然后结合MDPCSA算法,提出了一种最优的双重优先级配置搜索算法(ODPCSA).仿真实验表明,与两种分配策略相比,在提高系统容错能力和降低抢占开销方面更为有效.     

一种基于多处理机的容错实时任务调度算法

容错是实时系统的重要要求,在实时系统中,若一个实时任务没在规定的时间期限内完成,则认为系统出现错误,针对多处理机实时系统提出了一种容错调度算法．算法采用了任务的主从备份技术和Ｆｉｒｓｔ－ｆｉｔ启发式方法,通过为可能因处理机故障而执行失败的实时任务预留重新运行的时间来实现容错功能;并通过对预留时间段的重叠利用和无错时预留时间的回收分配,来提高处理机的利用率和系统对任务的接收率．模拟结果表明算法是有效     

多处理机系统的一种实时容错调度算法

实时容错调度算法是实时系统容错研究中的重要问题.提出了一种多处理机系统的实时任务容错调度算法.该算法结合了基版本/副版本(Primary/Backup)方法和三模冗余(TMR)方法,以保证在一个节点机失效时,任务可以在其截止时限内完成.     

A Framework for Software Fault Tolerance in Real-Time Systems

Real-time systems often have very high reliability requirements and are therefore prime candidates for the inclusion of fault tolerance techniques. In order to provide tolerance to software faults, some form of state restoration is usually advocated as a means of recovery. State restoration can be expensive and the cost is exacerbated for systems which utilize concurrent processes. The concurrency present in most real-time systems and the further difficulties introduced by timing constraints suggest that providing tolerance for software faults may be inordinately expensive or complex. We believe that this need not be the case, and propose a straightforward pragmatic approach to software fault tolerance'which is believed to be applicable to many real-time systems. The approach takes advantage of the structure of real-time systems to simplify error recovery, and a classification scheme for errors is introduced. Responses to each type of error are proposed which allow service to be maintained.     

Sensor fault tolerant control using sliding mode observers

Previous work has considered the use of sliding mode observers for fault detection and isolation (FDI) in uncertain linear systems whereby the unknown faults are reconstructed by appropriate processing of the so-called equivalent output error injection. The paper builds on this work and considers such a scheme within the broader context of fault tolerant control. Specifically, by correcting the faulty measurement by an estimate of the fault obtained from the sliding mode FDI scheme, good closed-loop performance is still maintained. An example of such a scheme, which has been implemented in real-time on a laboratory dc motor rig, is described.     

基于Multi-agent的实时系统运行故障监控研究

软件密集型装备中常常包含着许多担负监测和控制作用的嵌入式实时系统,它们常常属于安全关键或者任务关键系统(safety-critical/mission-critical system)。为了能够有效解决该类系统中的软件故障检测、诊断与修复任务,本文提出了基于Multi-agent的实时系统运行故障监控框架,旨在利用在多agent的协作构建运行故障监控系统来在系统运行当中验证系统是否满足时序逻辑描述的性质规约,并采用具体的算法进行故障定位和修复。     

基于无线传感网络的机床热误差智能检测系统设计

针对目前机床热误差检测系统结构复杂、布线麻烦、安装困难等问题,设计了基于无线传感网络的机床热误差智能检测系统,采用嵌入式、无线传感技术对机床温度场、热变形等信号进行实时采集、处理和监测,实现多地显示和故障报警等功能。     

Design of a novel knowledge-based fault detection and isolation scheme

In this paper, a real-time fault detection and isolation (FDI) scheme for dynamical systems is developed, by integrating the signal processing technique with neural network design. Wavelet analysis is applied to capture the fault-induced transients of the measured signals in real-time, and the decomposed signals are pre-processed to extract details about a fault. A Regional Self-Organizing feature Map (R-SOM) neural network is synthesized to classify the fault types. The R-SOM neural network adopts two regions adjustment in the learning algorithm, thus it has high precision in clustering and matching, especially when the noise, disturbance and other uncertainties exist in the systems. As a result, the proposed FDI scheme is robust and accurate. The design is implemented on a stirred tank system and satisfactory online testing results are obtained.     

Stabilizing Pre-Run-Time Schedules With the Help of Grace Time

This paper discusses the stability of a feasible pre-run-time schedule for a transient overload introduced by processes re-execution during an error recovery action. It shows that the stability of a schedule strictly tuned to meet hard deadlines is very small, invalidating thus backward error recovery. However, the stability of the schedule always increases when a real-time process is considered as having a nominal and a hard deadline separated by a non-zero grace time. This is true for sets of processes having arbitrary precedence and exclusion constraints, and executed on a single or multiprocessor based architecture. Grace time is not just the key element for the realistic estimation of the timing constraints of real-time error processing techniques. It also allows backward error recovery to be included in very efficient pre-run-time scheduled systems when the conditions stated in this paper are satisfied. This is a very important conclusion, as it shows that fault-tolerant hard real-time systems do not have to be extremely expensive and complex.     

Error detection and diagnosis for fault tolerance in distributed systems

The early error detection and the understanding of the nature and conditions of an error occurrence can be useful to make an effective and efficient recovery in distributed systems. Various distributed system extensions were introduced for the implementation of fault tolerance in distributed software systems. These extensions rely mainly on the exchange of contextual information appended to every transmitted application specific message. Ideally, this information should be used for checkpointing, error detection, diagnosis and recovery should a transient failure occur later during the distributed program execution. In this paper, we present a generalized extension suitable for fault-tolerant distributed systems such as communication software systems and its detection capabilities are shown. Our extension is based on the execution of message validity test prior to the transmission of messages and the piggybacking of contextual information to facilitate the detection and diagnosis of transient faults in the distributed system.     

基于CNN-LSTM-PSO的私有云故障检测

有效对私有云系统进行故障检测对于保障IT系统稳定性及开展可靠性信息活动具有重要的实际意义。为此从私有云系统的历史趋势数据出发,将卷积网络(CNN)和长短期记忆(LSTM)循环神经网络结合,提出了基于粒子群优化算法(PSO)的CNN-LSTM-PSO的混合模型,实现对私有云的故障检测。采用X11算法等技术对数据进行预处理,使用CNN网络提取监控指标时序数据的相关特征信息,并通过训练LSTM网络参数建立CNN-LSTM预测模型,设计了PSO算法对预测模型进行参数选优,减小预测误差,并以高斯正态分布确定阈值范围,实现故障的精准检测。通过和传统单一预测模型以及现有的一些组合预测模型的对比,CNN-LSTM-PSO模型预测后结果的均方根误差、平均绝对误差和平均百分比误差都低于其余模型。实验结果验证了模型在预测效果上具备更高的精度和更快的预测速度,在私有云的故障检测中精确性和实时性都具有良好效果。     

Fault-tolerant computing: fundamental concepts

The basic concepts of fault-tolerant computing are reviewed, focusing on hardware. Failures, faults, and errors in digital systems are examined, and measures of dependability, which dictate and evaluate fault-tolerance strategies for different classes of applications, are defined. The elements of fault-tolerance strategies are identified, and various strategies are reviewed. They are: error detection, masking, and correction; error detection and correction codes; self-checking logic; module replication for error detection and masking; protocol and timing checks; fault containment; reconfiguration and repair; and system recovery