H∞ filtering of networked discrete-time systems with random packet losses

This paper studies the H_∞ filtering problem for networked discrete-time systems with random packet losses. The general multiple-input-multiple-output (MIMO) filtering system is considered. The multiple measurements are transmitted to the remote filter via distinct communication channels, and each measurement loss process is described by a two-state Markov chain. Both the mode-independent and the mode-dependent filters are considered, and the resulting filtering error system is modelled as a discrete-time Markovian system with multiple modes. A necessary and sufficient condition is derived for the filtering error system to be mean-square exponentially stable and achieve a prescribed H_∞ noise attenuation performance. The obtained condition implicitly establishes a relation between the packet loss probability and two parameters, namely, the exponential decay rate of the filtering error system and the H_∞ noise attenuation level. A convex optimization problem is formulated to design the desired filters with minimized H_∞ noise attenuation level bound. Finally, an illustrative example is given to show the effectiveness of the proposed results.     

An intelligent fault diagnosis method based on wavelet packer analysis and hybrid support vector machines

In this paper, a new intelligent method for the fault diagnosis of the rotating machinery is proposed based on wavelet packet analysis (WPA) and hybrid support machine (hybrid SVM). In fault diagnosis for mechanical systems, information about stability and mutability can be further acquired through WPA from original signal. The faulty vibration signals obtained from a rotating machinery are decomposed by WPA via Dmeyer wavelet. A new multi-class fault diagnosis algorithm based on 1-v-r SVM approach is proposed and applied to rotating machinery. The extracted features are applied to hybrid SVM for estimating fault type. Compared to conventional back-propagation network (BPN), the superiority of the hybrid SVM method is shown in the success of fault diagnosis. The test results of hybrid SVM demonstrate that the applying of energy criterion to vibration signals after WPA is a very powerful and reliable method and hence estimating fault type on rotating machinery accurately and quickly.     

Windows平台通用个人防火墙的分析与设计

定义个人防火墙系统应具备的主要功能,其核心技术是网络数据包的过滤。给出Windows系统网络协议分层体系结构,在对OSI参考模型和Windows网络体系结构对比分析的基础上给出实现包过滤的不同技术路线。对各技术路线进行评估,选择SPI作为实现方案,给出使用SPI进行包过滤的技术要点,个人防火墙系统的运行表明其具有较快的包过滤处理性能。     

全光分组交换路由器缓存需求研究

针对当前只能在一个集成光电芯片上实现容量为几十个分组的光先来先服务（FCFS）缓存,大规模的光缓存仍无法实现的问题,利用接入链路速率远小于骨干链路速率这一特性,在牺牲25％的链路利用率的条件下,讨论小缓存能否满足采用CIOQ缓存队列的全光分组交换路由器的性能需求。从理论上证明采用CIOQ缓存队列的路由器的缓存需求小于采用OQ缓存队列的缓存需求,通过分析和仿真发现,20个分组的缓存即可满性能需求。     

基于AMCC网络处理器的QoS技术

在分析QoS技术功能模块及AMCC网络处理器架构基础上,利用微码与高级语言混合编程模式设计并实现基于NP3450的网络设备数据平面软件,引入深度包分类、二次查表、三级调度及四组准入门限等机制,实现基于流的细颗粒度QoS管控。实验结果表明,该设计方案是可行的。     

无线传感器网络中的选择转发攻击检测

针对无线传感器网络中现有检测攻击方法需要节点协同或检测硬件的缺点,对选择转发攻击进行研究,提出一种基于信任度与丢包行为的检测方法。通过节点收发数据包的情况,计算节点的信任度,结合节点丢包行为评估,判断节点是否发动攻击。这种检测方法的计算与存储开销都集中于基站,且不需增加额外的检测设备。实验结果表明,这种方法较之现有检测方法,检测率更高。     

换流站阀水冷系统主泵轴承故障诊断方法研究

对换流站阀水冷系统主泵轴承的故障诊断方法进行了比较研究.采用支持向量机作为分类工具,分别利用时域特征值和小波包分解取样本熵作为样本训练,比较分类准确率,并择优用于换流站阀水冷系统主泵的轴承故障诊断.首先,利用轴承故障试验台的数据,对采用时域特征值和小波包分解取样本熵作为样本训练的分类准确率进行了比较,结果表明小波包分解取样本熵值比时域特征参数更适合用于特征故障分类.然后将小波包分解取样本熵值用于换流站阀水冷系统主泵的轴承故障诊断,结果显示分类准确率达98％,完全满足工程运用需求.     

移动自组网自私行为闭环惩罚模型设计

针对移动自组网MAC层开环模型缺乏自私行为惩罚机制的不足,设计一种包括报文信息统计、统计信息共享和判决惩罚模块的闭环改进协议PDCF。报文信息统计定义转发率、丢弃度等指标衡量节点行为,修改仿真软件内置函数实现节点行为信息的统计。统计信息共享定义行为量化等级,改进DCF预留字段和CSMA/CA机制,实现节点行为信息的全网覆盖。判决惩罚模块对节点行为建立一维马尔科夫链惩罚模型,限制节点自私行为。仿真结果表明,与DCF相比,PDCF时延、丢包率和控制开销基本不变,但稳态时自私节点比例得到有效控制,且吞吐量增加2.7Mbps,网络性能得到改善。     

Symmetric NAT的穿越问题研究

为适应越来越多的企业基于网络安全性需要而使用Symmetric NAT的趋势,给出一种采用预测端口实现信息包穿越Symmetric NAT的方法,该方法克服了目前对称型NAT穿越方式中存在的服务器负担重、延时、丢包等问题,能更好的满足企业使用对称型NAT既可节约IP又能强化网络安全的需求。     

面向新型业务的多维快速包分类算法研究*

网络中新兴的新型业务例如P2P,VoIP,Worm等日益增多,在整个网络流量中占有越来越多的比重。对这些新型业务的监测和控制要求路由器等核心设备必须有能力对数据包进行快速和准确的分类。本文从这些新型业务包分类规则库的特点着手,提出在多维多模式匹配情况下的三种包分类决策树,通过实验说明这些决策树应用在新型业务的包分类上与传统的串行决策树性能各自的差异,进而得出适合新型业务包分类的最佳算法。