一种基于Zigbee的无线传感器网络教学实验系统

本文首先简要介绍无线传感器网络的体系结构,然后给出一个基于IEEE802．15．4和Zigbee协议的无线传感器网络教学实验系统。该系统中的多个传感器节点可以组成多种不同的拓扑结构,并可以将采集到的数据通过GSM网络发送到用户终端,用户也可以通过GSM网络对远程传感器节点进行控制。该教学实验系统已被许多院校采用,亦可直接应用于其他领域。     

主动网络安全风险管理系统

针对日益严峻的网络安全威胁，文章从加强内部安全管理入手，依据BS7799信息安全管理体系标准的规范及指标，提出了一个主动网络安全风险管理系统。该系统利用信息侦察代理获得园区网的基本配置及漏洞信息，在此基础上建立潜在入侵事件扩散模型，分析模型并对网络所面临的安全风险进行定性和定量评估．最后根据评估结果执行相应的风险控制措施，使风险等级降低到可接受的水平。文章还介绍了主动安全风险管理系统的结构，入侵扩散模型以及风险评估算法的具体细节，实验结果表明该系统能够有效地协助管理员建立完善的安全风险管理体系．     

基于用户感知的3D MIMO扩容门限研究

3D MIMO是Pre5G技术之一,是Massive MIMO的初期形式。3D MIMO多部署在网络热点区域,其中容量评估是影响其效果的重要因素。为匹配用户不断增长的网络体验需求,需要制定与时俱进的网络扩容评估标准。因此,从用户实际无线环境和业务类型出发,建立感知评价模型,设计实验用例得出感知受限门限值。实验中业务模型选择视频业务和混合业务,视频感知评价采用决策树评价模型。根据测试结果,提出了一组3D MIMO扩容门限,能有效指导后期3D MIMO网络规划、优化和工程设计。     

基于多阶段攻击的网络安全风险评估方法

网络安全风险评估技术能够检测网络系统潜在的安全漏洞和脆弱性，评估网络系统的安全状况，是实现网络安全的重要技术之一．文中对基于多阶段攻击的网络安全风险评估方法进行了研究，给出了多阶段攻击的网络安全风险评估方法的评估过程，分析了该评估方法中的关键参数，构建了基于多阶段攻击的网络安全风险评估的模型，最后通过实践验证了该方法的有效性，一定程度上提高了评估结果的准确性和一致性。     

Moving Objects Detection Using Intersecting Cortical Model in Enhanced Fish-eye Image

A new method of the moving objects detection using the enhanced fish-eye lens and the intersecting cortical model (ICM) algorithm is proposed. The improved fish-eye lens is designed through controlling the entrance pupils of the lens.This lens has an ultra field of view about 183 degrees,and can image resolution.The ICM is a model based on pulse coupled neural network(PCNN) which is especially designed for image processing.It is derived from several visual cortex models and is basically the intersection of these models.The theoretical foundation of the ICM is given.An improved ICM algorithm in which some parameters are modified is used to detect moving objects specially.The experiment indicated that moving objects can be detected reliably and efficiently using ICM algorithm from the elliptical fish-eye image.It can be used in the field of traffic monitoring and other security domains.     

开放式检测监控集成教学实验平台设计

面向高校测控类专业本科实验教学需要,提出并设计了一种开放式集成教学实验平台.对其基本物理组成结构和实验功能作了介绍.该平台系统不仅能够进行单项测控实验,还可以通过网络集成环境进行综合性实验,并能根据需要组建并扩展不同种类的测控实验环境,通过各种层次的实验培养学生的动手和系统开发能力.最后通过一个用于模拟柔性制造系统检测监控的实例说明了这种实验平台的具体应用.     

Evolution towards an ATD multiservice network

Public networks will continue to evolve in order to provide additional services and to make use of emerging technologies. This evolution is being directed toward multiservice networks which allow the cheaper introduction of new services. Asynchronous time division (ATD) techniques are preferred as the basis for implementing multiservice networks, such as LANs, because they can provide full service integration, rate adaption and the statistical multiplexing of variable bit rate services. This paper outlines some gradual evolutionary paths which are directed toward a single ATD multiservice network and could provide immediate benefits. An eventual ATD network could be expected to use short fixed length packets, a mixture of datagram and virtual circuit techniques and a mixture of switch architectures in order to most economically meet the requirements of a public network. The Orwell protocol, developed within British Telecom, provides a means of meeting the performance requirements of such a network.     

入侵检测中基于检测点覆盖度的包流量模型

无线传感器网络入侵检测系统无论采用哪种框架模型和算法,对其性能评估都需借助于模拟的实验平台。在这个模拟的实验平台中,数据流量模型成为评估入侵检测系统性能客观而全面的重要因素。根据监测区域内目标检测点的覆盖度,提出了一种适用于无线传感器网络入侵检测应用的包流量模型,并通过仿真对理论分析进行了验证。仿真和实际应用表明,该流量模型为无线传感器网络的流量构建了一种数据源模型,根据实际流量负载对无线传感器网络的入侵检测系统的性能进行评估,不仅精确度较高,且易于分析。     

基于多尺度低秩模型的电力无线接入网异常流量检测方法

电力无线接入网的安全性对于电网生产至关重要,然而由于其IEC 60870-5-104规约控制数据存在着高维度的特点,且无线信道质量动态变化,难以快速、有效地检测控制数据的异常.鉴于此,本文提出了一种基于多尺度低秩的电力无线网异常流量检测器,首先构建一种规约深度分析的多尺度低秩模型,对其安全特征进行归一化和维度缩减,然后采用改进的递归特征选取和聚焦分类算法实现异常数据的检测.实验结果表明异常流量分类的准确性和维度缩减的性能.     

实时能效分析及智能评级方法

能效分级是能效测评的基础,传统的能效分级方法单一且有局限性。文中提出一种智能化的评级方法,将神经网络应用于电力用户能效分析中,建立了基于神经网络的能效评级模型,从而不用给定某个特定的显式数学表达式。系统以RBF神经网络为核心建立模型,使用正交最小二乘法学习。综合考虑电能能效、电能污染能效和经济能效,可实时有效地进行能效分析及智能评级,并给出量化节能方案。仿真及实例计算表明,电力用户实时能效评级的RBF模型操作简捷、适用性强、实时性高,且具有较强的实用价值。     

The Adaptive Road Routing Recommendation for Traffic Congestion Avoidance in Smart City

A fuzzy neural network (FNN) calculates the traffic-light system and extends or terminates the green signal according to the traffic situation at the given junction while also computing from adjacent intersections. In the presence of public transports, the system decides which signal(s) should be red and how much of an extension should be given to green signals for the priority-based vehicle. Using fuzzy logic, we propose a model with a neural network for public transport, normal cars, and motorcycles. The model controls traffic-light systems to reduce traffic congestion and help vehicles with high priority pass through. The system also monitors the density of car flows and makes real-time decisions accordingly. In order to verify the proposed design algorithm, we adapted the simulations of Simulation of Urban MObility, ns2, and green light district simulation method to our model, and further results depict the performance of the proposed FNN in handling traffic congestion and priority-based traffic. The promising results present the efficiency and the scope of the proposed multi-module architecture for future development in traffic control.     

一种低轨卫星网络的概率风险评估方法研究

可靠性分析是卫星星座设计过程中不可或缺的一环。针对低轨卫星网络的高可靠性要求,利用概率风险评估的分析方法,结合网络风险及故障树理论,提出了卫星故障树杠铃风险模型。在此模型基础上分析＂铱＂星系统网络,利用卫星工具箱获取每颗卫星对地覆盖人口数,以此为参数计算得到对网络影响较大的节点和链路,对于今后评估卫星网络风险具有一定的启发意义。     

Design of an optimal BER monitoring scheme for preventive maintenance of an ATM network

In today's telecommunication networks it is well known that unexpected failures in the physical links may cause significant loss or interruption of services. It is desirable if the deterioration of links can be recognized early and maintenance is carried out before failure occurs. Asynchronous transfer mode (ATM) networks have recently received much attention and are considered to be the prime universal networks of the future. Unfortunately, there has been very little research in the areas of preventive maintenance and performance monitoring of the ATM network. In this paper we propose a preventive maintenance monitoring scheme for an ATM network where a performance index called the bit error rate (BER) index of each service of the ATM network is continuously monitored. The BER index of each path in the ATM network is assumed to be slowly deteriorating and is modelled as a Brownian motion process with positive drift. If any of the BER indices exceeds its action limit or threshold, a repair process is initiated. The optimal action limit is derived by minimizing the modified long-run average maintenance cost. We found that the optimal action limit depends strongly on the multiservice characteristics of the ATM network and on the network topology, which relates to the virtual path (VP) bandwidth management and routing protocol used. To obtain the optimal action limit, an optimization model for VP bandwidth management is set up and the multidimensional Erlang loss model is used to determine the path selecting probabilities. Some numerical examples are given to illustrate the proposed model and the optimization results. © 1998 John Wiley & Sons, Ltd.     

User-oriented QoS in packet video delivery

We focus on packet video delivery, with an emphasis on the quality of service perceived by the end user. A video signal passes through several subsystems, such as the source coder, the network (ATM or Internet), and the decoder. Each of these can impair the information, either by data loss or by introducing delay. We describe how each of the subsystems can be tuned to optimize the quality of the delivered signal, for a given available bit rate in the network. The assessment of end-user quality is not trivial. We present research results, which rely on a model of the human visual system     

Modeling and identification of parallel nonlinear systems:structural classification and parameter estimation methods

Structural classification and parameter estimation (SCPE) methods are used for studying single-input single-output (SISO) parallel linear-nonlinear-linear (LNL), linear-nonlinear (LN), and nonlinear-linear (NL) system models from input-output (I-O) measurements. The uniqueness of the I-O mappings of some model structures is discussed. The uniqueness of I-O mappings of different models tells us in what conditions given model structures can be differentiated from one another. Parameter uniqueness of the I-O mapping of a given structural model is also discussed, which tells us in what conditions a given model's parameters can be uniquely estimated from I-O measurements. These methods are then generalized so that they can be used to study single-input multi-output (SIMO), multi-input single-output (MISO), as well as multi-input multi-output (MIMO) nonlinear system models. Parameter estimation of the two-input single-output nonlinear system model, which was left unsolved previously, can now be obtained using the newly derived algorithms. Applications of SCPE methods for modeling visual cortical neurons, system fault detection, modeling and identification of communication networks, biological systems, and natural and artificial neural networks are also discussed. The feasibility of these methods is demonstrated using simulated examples. SCPE methods presented in this paper can be further developed to study more complicated block-structured models, and will therefore have future potential for modeling and identifying highly complex multi-input multi-output nonlinear systems     

基于突变理论的网络异常行为分析方法

给出了把异常数据流从网络数据流中按区间分离出来的方法,基于分离出来的每个时间序列异常数据流集，给出了网络异常行为突变模型设计、参数估计和检验等方法。为了推断未来网络异常行为出现情况。给出基于RBF网络的模型外推方法。根据外推得到的突变模型,可以方便地计算有关网络异常行为的各种参数和评估指标。     

CMG-based anthropomorphic test device for human rider behavior reproduction for two-wheeled self-balancing personal mobility

With the expansion of the self-balancing personal mobility (SBPM) market, an increasing number of accidents have been reported in recent years, while the relevant safety regulations have not been established yet. Safety and dynamic stability of the SBPM is critical for their operation, and they must be evaluated for them. SBPMs are operated by a human rider even for the evaluation tests, so the objectivity and the repeatability of the tests cannot be ensured. Also, there could even be a safety issue with the test rider. To solve this problem, we propose an anthropomorphic test device (ATD), which is a type of dummy robot. The ATD reproduces the human rider's dynamic behavior using a control moment gyroscope (CMG), so it can drive the SBPM instead of a human rider for the evaluation tests. Just like a human rider controls the SBPM by the disturbance torque made by the posture (i.e. the center of gravity) change, the CMG-based ATD reproduces the dynamic behavior of the SBPM by creating the same disturbance torque using the CMG. A detailed working principle and the design of the CMG-based ATD is introduced in this paper. For the validation of the CMG-based ATD's human rider behavior reproduction performance, the dynamic behavior of the SBPM measured from the actual human ride is compared with the data from the computer simulations.     

双耦合线巴伦设计

基于微带耦合线的四端口网络模型,提出了一种双耦合线巴伦,根据最小反射系数准则,推导出巴伦应满足的阻抗方程,并给出不同带宽所要求的耦合线奇偶模阻抗.最后给出ADS仿真结果及实验结果.     

公安复杂网络节点重要度研究

公安信息网是警务信息化工作的技术支撑,为了达到准确合理评估公安信息网稳定运行的风险度,需要对组成网络的各节点重要度进行评估分析。总结了在复杂网络环境下网络节点重要度常规计算方法并进行了相应分析,通过确立节点重要度关联指标体系,采用以度中心性和聚集中心性为核心参数的评估算法,对某型公安网络节点进行重要度计算评估实验,实验所得节点重要度值基本上反映了网络节点在整体拓扑结构中的地位,可以为复杂网络的建设及管理运维提供相应的工程借鉴和参考意义。     

宽带战术通信系统架构设计与实现

针对未来战术通信向高速、宽带、移动和网络化方向发展,提出了利用LTE技术构建宽带战术通信系统的网络架构和设计思想。通过高速传输技术、高效多天线技术和无线接入技术,以及频率下移、综合集成技术,建立了一套一体化车载式基站系统,描述了网络架构、实体和基本设计策略,给出了系统主要设计指标。通过实例验证：通信距离可达20 km,通信距离显著提高,此时数据吞吐量可达47 Mbit/s,比现役提升近百倍,证明了系统架构设计的有效性和可行性,真正实现了战术通信系统跨越式发展。