Mutual Information Agreement with the Detection and Identification of Byzantine Faults in Incompletely Connected Multicomputer Systems

A method of the mutual information agreement for incompletely connected multicomputer systems is set out, which ensures the consistent (i.e. simultaneous and identical) detection and identification of faults in an admissible number of computers among all the serviceable computers of the system both by the places of symptoms of faults and their types (malfunctions, programmed malfunctions, or failures).     

Mutual Informational Coordination in Incompletely Connected Multicomputer Systems

Conditions for mutual informational coordination in incompletely connected multicomputer systems were considered. An algorithm of mutual informational coordination in such systems was presented.     

Hybrid Methods for Detection and Identification of Faults in Dynamic Systems

Since the 1960s, when automation became essential to productivity, methods for the detection and identification of faults have been proposed. Physical systems are diversified and can be mechanical, electrical, pneumatic, electronic, or a combination of these. In addition, real plants have a large number of these devices, which are for its own operation, sensoring or control. Therefore the solutions given for detection of faults are generally very specific or particular. This paper aims to describe and analyze two hybrid methods of detection and fault identification based on residue and to check whether their inclusion with other methods, combining different techniques, can produce a better fault detection and identification system. The methods use the state observers for the generation of residues, which serve for the detection and identification and the set called the bank of signatures to identify the faults. Thereafter, the methods use different approaches to diagnose the fault: the first uses the approach of the mean square error, and the second uses a decision tree.     

Detection of Mutual Inconsistency in Distributed Systems

Many distributed systems are now being developed to provide users with convenient access to data via some kind of communications network. In many cases it is desirable to keep the system functioning even when it is partitioned by network failures. A serious problem in this context is how one can support redundant copies of resources such as files (for the sake of reliability) while simultaneously monitoring their mutual consistency (the equality of multiple copies). This is difficult since network faiures can lead to inconsistency, and disrupt attempts at maintaining consistency. In fact, even the detection of inconsistent copies is a nontrivial problem. Naive methods either 1) compare the multiple copies entirely or 2) perform simple tests which will diagnose some consistent copies as inconsistent. Here a new approach, involving version vectors and origin points, is presented and shown to detect single file, multiple copy mutual inconsistency effectively. The approach has been used in the design of LOCUS, a local network operating system at UCLA.     

Discovering Network Topology in the Presence of Byzantine Faults

We pose and study the problem of Byzantine-robust topology discovery in an arbitrary asynchronous network. The problem is an abstraction of fault-tolerant routing. We formally state the weak and strong versions of the problem. The weak version requires that either each node discovers the topology of the network or at least one node detects the presence of a faulty node. The strong version requires that each node discovers the topology regardless of faults. We focus on noncryptographic solutions to these problems. We explore their bounds. We prove that the weak topology discovery problem is solvable only if the connectivity of the network exceeds the number of faults in the system. Similarly, we show that the strong version of the problem is solvable only if the network connectivity is more than twice the number of faults. We present solutions to both versions of the problem. The presented algorithms match the established graph connectivity bounds. The algorithms do not require the individual nodes to know either the diameter or the size of the network. The message complexity of both programs is low polynomial with respect to the network size. We describe how our solutions can be extended to add the property of termination, handle topology changes, and perform neighborhood discovery.     

Performance study of Byzantine Agreement Protocol with artificial neural network

Since 1982, numerous Byzantine Agreement Protocols (BAPs) have been developed to solve arbitrary faults in the Byzantine Generals Problem (BGP). A novel BAP, using an artificial neural network (ANN), was proposed by Wang and Kao. It requires message exchange rounds similar to the traditional BAP and its suitability, in the context of network size, has not been investigated. In the present study, we propose to adopt Nguyen-Widrow initialization in ANN training, which modifies message communication and limits the message exchange rounds to three rounds. This modified approach is referred to as BAP-ANN. The BAP-ANN performs better than the traditional BAP, when the network size n is greater than nine. We also evaluate the message exchange matrix (MEM) constructed during the message exchange stage. For a fixed number of faulty nodes and remainder cases of (n mod 3), the study shows that the mean epoch for ANN training decreases as the network size increases, which indicates better fault tolerance.     

基于代理的Byzantine一致性协议的研究

本文在研究了国内外Byzantine协议的基础上提出了一种新的Byzantine一致性协议,即基于代理的Byzantine一致性协议。该协议按照Byzantine容错机制将所有参与运算的进程分成很多小块,每个块设有一个代理。通过代理,块内的进程向其他块的进程发送运算结果。这样,在进程发生Byzantine错误时可以先在块的内部处理,从而可以有效地减少容错的开销和时延,提高系统的安全性。     

基于互信息的多阈值系统中随机谐振现象研究

基于互信息讨论了四种典型噪声下多阈值系统中的随机谐振现象.当输入信号在阈上时,互信息随着噪声的增强而单调递减,噪声总是恶化系统的性能;而当输入信号在阈下时,互信息随着噪声的增强先递增然后再递减,适量噪声能改善多阈值系统的性能,随机谐振现象存在.随着阈值系统阈值的增大,随机谐振功效降低,最佳噪声强度逐渐增大.文中结果说明了多阈值系统中基于互信息的随机谐振现象存在.且随机谐振对噪声具有一定的鲁棒性,拓广了随机谐振在多元信号与信息处理中的应用.     

基于互信息方法的非线性多变量系统模型失配检测

在基于模型的控制技术中,例如模型预测控制(MPC),模型的质量对于控制器的设计和整定起到关键作用.所以,控制器的性能依赖于过程模型的精度,亦即受到模型失配程度的影响.针对线性系统的模型失配检测,已经有各种不同的方法见诸于相关文献,而对于非线性系统,则很少有相应的方法提出.考虑到广泛存在的系统非线性特性,采用互信息作为一种广义的相关性量化测度.利用摄动信号和模型残差的互信息量来表征过程模型失配程度而与扰动部分的模型变化无关.对于大规模的多变量系统,能够定位到子系统的模型失配对于故障诊断或者模型重新辨识起到至关重要的作用,利用一种递阶排除的分析方法来精确定位子系统的模型失配,提出利用互信息矩阵直观的量化表达多变量系统的模型失配.在两个仿真例子上的应用说明了该方法的有效性.     

MATLAB图像处理技术在针织物疵点检测中的应用

介绍了使用MATLAB的图像处理工具箱,先对扫描的织物图像进行预处理,以检测传统的织物疵点。对多种疵点检测算法进行了分析和比较,将织造过程中产生的对劈缝、浆斑、断经等3类最常见疵点成功地进行了检测识别。     

Comments on "Detection of Mutual Inconsistency in Distributed Systems"

In the above paper,¹authors have given a technique for the detection of mutual inconsistency among the copies of a file, in presence of network partitioning. This technique involves maintaining a "version vector" with each file in a partition. Here, we show that it is impossible to maintain the version vectors when arbitrary reconfigurations can occur after a network partitioning.     

Systems of Strings with High Mutual Complexity

Consider a binary string x ₀ of Kolmogorov complexity K(x ₀) n. The question is whether there exist two strings x ₁ and x ₂ such that the approximate equalities K(x _i x _j ) n and K(x _i x _j , x _k ) n hold for all 0 i, j, k 2, i j k, i k. We prove that the answer is positive if we require the equalities to hold up to an additive term O(log K(x ₀)). It becomes negative in the case of better accuracy, namely, O(log n).     

基于多尺度互信息量的数字视频帧篡改检测

针对单镜头视频时域篡改问题,提出一个以内容相似性为基础的视频篡改被动盲检测算法。通过高斯金字塔变换获得视频帧的3种尺度视觉内容,根据信息论定义相邻两帧的归一化平均互信息,采用线性组合构建多尺度归一化互信息描述子,实现相邻两帧多尺度视觉内容相似性的度量。利用局部离群点检测算法计算视觉内容相似性异常度,使用阈值法检测视频篡改位置。实验结果表明,该算法不仅能有效地检测出视频帧删除、复制以及插入3种篡改的位置,而且适用于不同编码格式视频间和同源的篡改。在检准度和检全率上优于现有的时域篡改检测算法。     

基于最大互信息区域跟踪的人体行为检测算法

人体行为检测问题不仅需要判断行为的类别,而且需要估计行为发生的时间和位置,有重要的现实应用意义. 人体行为检测的主要难点在于参数空间维度高以及背景运动干扰. 针对上述难点,本文提出了一种基于最大互信息区域跟踪的人体行为检测算法. 该算法将行为区域定义为最大互信息矩形区域,采用稠密轨迹作为底层特征,利用随机森林学习轨迹特征与行为类别的互信息函数,利用轨迹的时间连续性对行为区域进行大时间跨度的预测和跟踪. 实验结果表明,该算法不仅能够有效地识别不同类别的行为,而且能够适应现实场景中背景运动的干扰,从而准确地检测和跟踪行为区域.     

Networked Estimation of Multi‐Agent Systems Subject to Faults and Unreliable Information

In this paper, a novel framework for networked estimation of multi‐agent systems subject to presence of actuator faults is proposed. This framework is developed based on the notion of sub‐observers where within a group of sub‐observers each sub‐observer estimates certain states that are conditioned on a given input, output, and other state information. We model the overall estimation process by a weighted estimation (WE) digraph. By selecting an appropriate path in the WE digraph, an assigned supervisor can select and configure a set of sub‐observers to successfully estimate all the system states. In the presence of large intermittent disturbances, noise, and faults certain sub‐observers may become invalid, and consequently the supervisor reconfigures the set of sub‐observers by selecting a new path in the estimation digraph such that the impacts of these uncertainties are confined to only the local estimators. This will prevent the propagation of uncertainties on the estimation performance of the entire multi‐agent system. Simulation results provided for a five satellite formation flight system in deep space confirm the validity and applicability of our proposed analytical work.     

基于交互信息量和联合熵的镜头检测算法

镜头检测在视频检索中起着关键作用。文章提出了一种基于信息论的镜头检测方法,该方法使用相邻帧间的交互信息量检测突变,使用相邻帧间的联合熵检测淡入/淡出镜头。试验表明:该方法简单、有效,且识别的准确率较高。     

融合显著特征和互信息熵的SLAM闭环检测算法

针对移动机器人SLAM闭环检测存在的闭环错误判定问题,提出了一种融合显著特征和互信息熵的闭环检测算法.首先,通过帧间位姿变化和信息熵差异得到关键帧,利用词袋模型逆向索引查询关键帧获取闭环候选帧.然后,引入图像颜色与深度信息计算当前关键帧与闭环候选帧的显著特征生成显著图.最后,将显著图均匀划分四块,计算两匹配关键帧显著图对应块的互信息熵,由每块对应互信息熵生成一个表征两幅图像相似度的四维向量,通过四维向量将满足互信息熵条件的闭环帧进行几何验证,判断是否产生闭环.实验结果表明,该算法能够降低机器人累积误差,生成全局一致的地图,同时满足实时性要求.     

不确定时滞系统增益型故障的检测与估计

针对一类不确定连续线性定常时滞系统,提出了一种执行器、传感器增益故障的鲁棒检测与估计策略。该类系统含有多状态与输出时滞,状态和输出方程上同时作用有非结构有界未知扰动。在Trunov和Polycarpou方法的基础上,设计了一种新的时滞系统自适应观测器用于检测并估计突变或缓变的增益故障。与Wang等针对线性无时滞不合输出扰动系统的工作相比,该结论更具一般性。理论分析表明,该方法对于未知扰动鲁棒,能够保证故障的估计,状态与输出估计偏差一致有界。数值仿真验证了方法的有效性。     

一种结合互信息和模板匹配的配准方法

传统的互信息法直接对大图进行互信息配准,容易出现局部极值并产生误匹配现象,针对该问题,提出一种将互信息与模板匹配相结合的配准方法,采用互信息为相似度准则进行图像的模板匹配,得到候选的匹配子图,通过待配准大图其余部分与模板和子图的空间关系,得到配准后的大图,分别计算按照各个候选子图配准情况下的待配准图的互信息,得到最大的互信息所对应的子图,确定最终的配准结果。实验结果表明,该方法在对灰度差较大的图像进行配准时,能够获得良好的效果。