Conditional diagnosability and strong diagnosability of shuffle-cubes under the comparison model

The growing size of multiprocessor systems increases the vulnerability to component failures. It is crucial to locate and replace faulty processors to maintain the system's high reliability. Processor fault diagnosis is essential to the reliability of a multiprocessor system and the diagnosabilities of many well-known networks (such as hierarchical hypercubes and crossed cubes [S. Zhou, L. Lin and J.-M. Xu, Conditional fault diagnosis of hierarchical hypercubes, Int. J. Comput. Math. 89(16) (2012), pp. 2152–2164 and S. Zhou, The conditional diagnosability of crossed cubes under the comparison model, Int. J. Comput. Math. 87(15) (2010), pp. 3387–3396]) have been investigated in the literature. A system is t-diagnosable if all faulty nodes can be identified without replacement when the number of faults does not exceed t, where t is some positive integer. Furthermore, a system is strongly t-diagnosable if it is t-diagnosable and can achieve (t+1)-diagnosability except for the case where a node's neighbours are all faulty. In addition, conditional diagnosability has been widely accepted as a new measure of diagnosability by assuming that any fault-set cannot contain all neighbours of any node in a multiprocessor system. In this paper, we determine the conditional diagnosability and strong diagnosability of an n-dimensional shuffle-cube SQ_n, a variant of hypercube for multiprocessor systems, under the comparison model. We show that the conditional diagnosability of shuffle-cube SQ_n (n=4k+2 and k≥2) is 3n?9, and SQ_n is strongly n-diagnosable under the comparison model.     

Strong matching preclusion for two-dimensional torus networks

The torus network is one of the most popular interconnection networks for massively parallel computing systems. The strong matching preclusion number of a graph is the minimum number of vertices and edges whose deletion results in a graph that has neither perfect matchings nor almost perfect matchings. In this paper, we establish the strong matching preclusion number and classify all optimal solutions for the two-dimensional torus network with an odd number of vertices.     

Fault tolerant approach for biosignal-based robot control

This paper proposes a fault tolerant framework for biosignal-based robot control with multiple sensor electrodes. In this approach, to cope with sensor faults, a reliable joint torque estimation model is selected from a group of estimation models based on sensor failure classifiers. The correlation among the electromyography (EMG) signal streams is used as input feature vectors for fault detection. To validate our proposed method, we artificially disconnect an EMG electrode or detach one side of an EMG probe from the skin surface during elbow-joint torque estimation experiments with five participants. When one EMG sensor electrode experiences one of the problems, the experimental results show that the joint torque can be estimated with significantly fewer errors using our proposed approach than a joint torque estimation method without sensor fault detection or than a method with a conventional sensor fault detection algorithm. Furthermore, we controlled a mannequin-arm-attached one-DOF exoskeleton based on the estimated torque profiles by generating movements with the estimated torque derived from the selected model.     

一种改进的实时嵌入式系统容错优化方法

容错技术中硬件冗余会产生较高的设计和生产成本.针对该问题,提出一种改进的实时嵌入式系统容错优化方法,基于检查点容错技术综合分析系统故障性能、硬实时任务时间约束和软实时任务的效用函数值.以设计的容错模型为基础,计算系统故障概率保证其在故障最大概率值内,给出硬任务截止时间确定可调度性,并应用改进的禁忌搜索算法获得软任务效用函数最佳值,算法有2种简单的邻节点结构,其禁忌准则遵循邻节点方法禁忌,优化效率明显改善.实验结果表明,该方法可进行故障分析等综合分析,并能迅速获得最大效用函数值.     

航空电子全双工交换式以太网故障注入方法研究

航空电子全双工交换式以太网(AFDX)是成功应用于新一代大型飞机的新型航空数据总线.针对AFDX适航性及网络容错性能研究的需要,开展了有关AFDX网络故障注入方法的研究.在AFDX实验系统上,通过软件方法进行动态故障注入,测试AFDX网络对注入故障的响应,验证了AFDX网络的可靠性、健壮性及容错性能,并为进一步研究AFDX网络性能及故障诊断提供了大量测试数据,对深入开展AFDX适航技术研究打下了基础.     

不完备XML信息系统的粗糙集模型

随着XML成为网络信息表示和交换的标准以及不确定数据的广泛存在,不确定XML数据库管理技术成为了当今研究的热点。首先,允许XML文档叶子节点的信息值为丢失的或遗漏的空值,提出不完备的XML信息系统;其次,提出节点的相容关系、限制相容关系以及阈值相容关系等概念,基于粗糙集理论分别定义这3种关系对应的粗糙集模型;最后,通过实例分析表明,限制相容关系模型能克服相容关系模型分类粗糙的缺点,阈值相容关系模型通过合理地设置阈值可达到更好的分类效果,从而提高了对XML数据的预测、分类的精确度。     

改进的对象间差异度的限制容差关系模型

不完备信息系统不能直接用经典的粗糙集理论来处理,为此,容差关系、非对称相似关系、限制容差关系、限制非对称相似关系、对象间差异度的限制非对称相似关系等扩充的粗糙集模型被相继提出。通过分析这些模型的优点和不足之处,定义了新的对象间差异度,提出了一种改进的对象间差异度的限制容差关系模型,实例结果表明基于所提出模型的划分更精确,更符合实际。     

无线传感器网络中故障容忍算法研究

针对无线传感器维护困难,改善故障容忍能力的问题,提出了一种基于故障容忍度的自适应容错拓扑控制算法。首先,阐述了节点故障容忍度衡量指标,其次,详细分析了算法的各个阶段,最后通过仿真实验与常用算法对比,结果表明,基于故障容忍度的自适应容错拓扑控制算法具有更好的控制效果,极大地提高了使用效率。     

装配公差综合领域本体知识库的构建

为了减少机械产品设计过程中的不确定性,解决装配公差信息在异构CAX系统中共享性差和传递不畅的问题,利用本体丰富的语义知识和语法结构,通过分析装配公差综合领域相关知识,采用网络本体语言OWL定义其中的概念和关系,并采用语义网规则语言SWRL定义其中的约束条件和分配经验。将基于OWL的结构化知识转换成事实、基于SWRL的约束化知识转换成规则,并在推理引擎的基础上构建装配公差综合领域本体知识库。同时开发了基于本体的装配公差综合原型系统,实现了装配公差类型和装配公差值的自动生成。