基于NetFPGA的网络数据流量采集器

为解决基于软件的流量采集方法无法在高速网络环境下准确测量的问题,提出了一种基于NetFPGA的网络数据流量采集器,以达到实时在线的流量统计和采集功能。该系统采用模块化的架构设计,通过硬件实现功能的方式提高网络测量精度。实验结果表明,该系统能准确统计出网络中93%以上流量。     

An Intra-Server Interconnect Fabric for Heterogeneous Computing

With the increasing diversity of application needs and computing units, the server with heterogeneous pro- cessors is more and more widespread. However, conventional SMP/ccNUMA server architecture introduces communication bottleneck between heterogeneous processors and only uses heterogeneous processors as coprocessors, which limits the efficiency and flexibility of using heterogeneous processors. To solve this problem, this paper proposes an intra-server inter- connect fabric that supports both intra-server peer-to-peer interconnection and I/O resource sharing among heterogeneous processors. By connecting processors and I/O devices with the proposed fabric, heterogeneous processors can perform direct communication with each other and run in stand-alone mode with shared intra-server resources. We design the proposed fabric by extending the de-facto system I/O bus protocol PCIe （Peripheral Computer Interconnect Express） and implement it with a single chip cZodiac. By making full use of PCIe＇s original advantages, the interconnection and the I/O sharing mechanism are light weight and efficient. Evaluations that have been carried out on both the FPGA （Field Programmable Gate Array） prototype and the cycle-accurate simulator demonstrate that our design is feasible and scalable. In addition, our design is suitable for not only the heterogeneous server but also the high density server.     

基于ZigBee技术的医院供水管网水质监控系统

针对医院供水管网水质问题,设计了基于ZigBee无线传感器网络的水质实时监控系统。监控系统由末端的不同传感器采集水温、pH值、电导率水质参数,通过ZigBee无线网络传送给网关,网关实现ZigBee和TcP/IP协议间的转换后,将数据传送给监控中心进行存储、分析和处理,监控中心可发送命令控制整个网络。该方案不仅可以实现本地和远程水质实时监控,而且很容易应用于其他环境下的水质实时监控。     

Inductive Model Generation for Text Classification Using a Bipartite Heterogeneous Network

Algorithms for numeric data classification have been applied for text classification. Usually the vector space model is used to represent text collections. The characteristics of this representation such as sparsity and high dimensionality sometimes impair the quality of general-purpose classifiers. Networks can be used to represent text collections, avoiding the high sparsity and allowing to model relationships among different objects that compose a text collection. Such network- based representations can improve the quality of the classification results. One of the simplest ways to represent textual collections by a network is through a bipartite heterogeneous network, which is composed of objects that represent the documents connected to objects that represent the terms. Heterogeneous bipartite networks do not require computation of similarities or relations among the objects and can be used to model any type of text collection. Due to the advantages of representing text collections through bipartite heterogeneous networks, in this article we present a text classifier which builds a classification model using the structure of a bipartite heterogeneous network. Such an algorithm, referred to as IMBHN （Inductive Model Based on Bipartite Heterogeneous Network）, induces a classification model assigning weights to objects that represent the terms for each class of the text collection. An empirical evaluation using a large amount of text collections from different domains shows that the proposed IMBHN algorithm produces significantly better results than k-NN, C4.5, SVM, and Naive Bayes algorithms.     

基于场景重构与报警聚合的网络取证分析技术

提出一种包含报警标准化、去冗余、场景重构和报警聚合的网络取证分析方法. 通过去除失败攻击的报警, 减少了对证据分析的干扰. 在场景重构中, 通过反向关联, 减少了不必要的证据, 同时通过对孤立报警的补充, 保证了证据链的完整性. 在报警聚合中, 提出了聚合同一攻击步骤的不同报警的方法, 以抽象层和具体层两个层次重构入侵场景. 最后通过实验验证了所提出方法的有效性.     

基于UKF 和神经网络的一类非线性系统状态估计

在模型未知的情况下,估计过程的重要变量尤为重要.鉴于此,采用不敏卡尔曼滤波(UKF)与神经网络相结合的方法,解决一类未知模型非线性系统的状态估计问题.采用动态神经网络对非线性系统进行建模,利用UKF对状态和权值进行同时更新,从而达到神经网络逼近真实模型,估计值跟随真实值的目的.通过两个仿真实例表明了所提出的方法具有良好的估计效果,并且状态在输出中的比重越大,其估计精度越高.     

Amphiphilic segmented polymer networks based on poly(2-alkyl-2-oxazoline) and poly(methyl methacrylate)

Amphiphilic segmented polymer networks (SPNs) have been prepared by free radical copolymerization of methyl methacrylate with α,ω-bisacrylate terminated poly(2-methyl-2-oxazoline) and poly(2-ethyl-2-oxazoline). DSC and DMTA analysis demonstrated the influence of the copolymer composition, the molecular weight and nature of the poly(2-alkyl-2-oxazoline)s and the polymerization conditions on the final phase morphology of the networks. A comparative phase morphology study of the polymer blends and SPNs revealed the more compatible phase morphology of the networks. The compatibility could be further increased by UV-induced network formation. The investigation of the solvent uptake in different solvents clearly demonstrated the amphiphilic nature of the SPNs.     

基于带缓冲的双通道开关技术的网络隔离器设计

在对网络隔离技术进行分析的基础上,研究利用网络隔离技术来解决网络安全问题。目前的网络隔离产品大多是采用基于硬件的开关控制,受限于现有硬件技术条件,并且厂家要根据不同用户要求而开发生产针对特定应用的网闸,不能方便地同时支持多种应用。提出了一种改进的安全隔离网闸实现方案。重点是模块化和软件方式实现开关技术,采用独立的软件开关控制和模块化设计,解决了现有物理隔离网闸产品在硬件开关控制和所支持应用上的限制,这种采用软件实现开关功能的方式避免基于现有硬件技术的可用性和寿命时间的限制。     

主动磁悬浮轴承的神经网络自适应稳定性控制

针对主动磁悬浮轴承本质非线性和开环不稳定的系统特征,设计了一种BP神经网络自适应PID控制器。该控制器采用改进的BP神经网络PID控制算法,通过BP神经网络的自学习和权值调整寻找最优的PID参数,克服了常规PID控制参数整定困难的缺陷,实现了系统的自适应控制。通过MATLAB/Simulink环境和S-Function模块建立了主动磁悬浮轴承控制系统模型,并进行了系统仿真实验,结果表明,BP神经网络自适应PID控制系统响应速度更快,具有更好的动态性能和稳态性能。     

VxWorks系统下的UDP通信在实时系统中的应用

首先简要介绍了某一实时武器系统的网络组成,以及网络通信的基本结构。实时系统采用嵌入式操作系统VxWorks和TCP/IP网络通信协议。讨论了TCP协议与UDP协议各自适用的场合和优缺点。通过比较,系统采用了VxWorks系统下的UDP通信。接着介绍了Socket网络编程,并针对客户端/服务器通信模式的优缺点,给出了此实时系统的客户端与服务器的设计思路与步骤。最后给出了部分代码作为示例说明。