An Optimization Algorithm of Network Topology Discovery Based on SNMP Protocol

Through the analysis of network topology discovery algorithm used ICMP protocol and FDB address, a novel layer topology discovery and link layer topology discovery algorithm which is suitable for campus network environment is proposed based on SNMP protocol. This algorithm can rapidly and accurately calculate the second and third floors topology of the whole pipe network.

Estimating Topology of Discrete Dynamical Networks

In this paper,by applying Lasalle's in variance principle and some results about the trace of a matrix,we propose a method for estimating the topological structure of a discrete dynamical network based on the dynamicalevolution of the network.The network concerned can be directed or undirected,weighted or unweighted,and the localdynamics of each node can be nonidentical.The connections among the nodes can be all unknown or partially known.Finally,two examples,including a Henon map and a central network,are illustrated to verify the theoretical results.

Community discovery method with uncertainty measure of overlapping nodes based on topological potential

Community discovery of complex networks,esp.of social networks,has been a hotly debated topic in academic circles in recent years.Since actual networks usually contain some overlapping nodes that are difficult to assign to a certain community,overlapping community discovery is under great demand in practical applications.However,at present network community discovery is mainly done by non-overlapping community discovery methods,overlapping discovery methods are not common.In this context,an overlapping community discovery method is proposed hereby based on topological potential and specific algorithms are also provided.This method not only considers the spread of the uncertainty of community identity of the overlapping nodes in the network,but also realizes a quantified representation,i.e.,uncertainty measure,of the community identity of the overlapping nodes.The experiment results show that this method yields the results that are consistent with those by the classic methods and are more reasonable.

基于分布式SDN的机动通信系统拓扑发现方法

针对目前传统机动通信系统、主流软件定义网络(software defined network,SDN)的拓扑发现方法不适合基于分布式SDN的机动通信系统这一问题,遵循OpenFlow拓扑发现算法(OpenFlow discovery protocol,OFDP)移植传输控制协议/网际协议(transmission control protocol/Internet protocol,TCP/IP)相关协议到SDN网络的研究思路,对开放最短路径优先(open shortest path first,OSPF)协议进行优化,精简协议状态机、优化协议报文、增加协议功能并设计拓扑发现算法,提出一种适合基于分布式SDN的机动通信系统的拓扑发现方法,并搭建仿真实验平台进行验证。实验结果表明,优化后OSPF协议适应于分布式SDN网络,网络拓扑建链时间降低80%且重新收敛时间显著降低,建链开销平均每秒接收字节数、发送字节数分别下降了31.7%和21.5%,维持开销平均每秒收发字节数降低了45%,增加了收集信道种类等网络信息的新功能。

基于S/SP补偿拓扑的强抗偏移感应式无线电能传输系统

针对感应式电能传输(inductive power transfer,IPT)系统偏移造成输出电压不稳定和效率低下的问题,提出一种强抗偏移的S/SP补偿IPT系统,该系统在变耦合变自感和变耦合不变自感两种情况下均能保证较小的输出电压波动和较高的传输效率。首先,基于Maxwell有限元仿真,分析罐型磁心松耦合变压器的磁通分布和磁场分布特性,总结不同方向偏移的参数变化规律。然后,提出一种提高系统抗偏移能力的S/SP补偿参数设计方法,得到相应的磁耦合机构设计准则,并结合磁仿真数据,通过数值计算方式求得系统输出波动和输入阻抗角的变化规律。最后,通过实验验证文中采用罐型磁心和新型S/SP补偿拓扑实现多方向偏移下高效率、低波动无线电能传输的可行性。在额定负载下,系统沿纵向和水平方向偏移的输出电压波动分别为2.7%和3.1%,传输效率维持在90.8%~94.3%。

Brain networks modeling for studying the mechanism underlying the development of Alzheimer’s disease

Alzheimer’s disease is a primary age-related neurodegenerative disorder that can result in impaired cognitive and memory functions.Although connections between changes in brain networks of Alzheimer’s disease patients have been established,the mechanisms that drive these alterations remain incompletely understood.This study,which was conducted in 2018 at Northeastern University in China,included data from 97 participants of the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset covering genetics,imaging,and clinical data.All participants were divided into two groups:normal control(n=52;20 males and 32 females;mean age 73.90±4.72 years)and Alzheimer’s disease(n=45,23 males and 22 females;mean age 74.85±5.66).To uncover the wiring mechanisms that shaped changes in the topology of human brain networks of Alzheimer’s disease patients,we proposed a local naive Bayes brain network model based on graph theory.Our results showed that the proposed model provided an excellent fit to observe networks in all properties examined,including clustering coefficient,modularity,characteristic path length,network efficiency,betweenness,and degree distribution compared with empirical methods.This proposed model simulated the wiring changes in human brain networks between controls and Alzheimer’s disease patients.Our results demonstrate its utility in understanding relationships between brain tissue structure and cognitive or behavioral functions.The ADNI was performed in accordance with the Good Clinical Practice guidelines,US 21 CFR Part 50-Protection of Human Subjects,and Part 56-Institutional Review Boards(IRBs)/Research Good Clinical Practice guidelines Institutional Review Boards(IRBs)/Research Ethics Boards(REBs).

Defense Against Software-Defined Network Topology Poisoning Attacks

Software-Defined Network(SDN)represents a new network paradigm.Unlike conventional networks,SDNs separate control planes and data planes.The function of a data plane is enabled using switches,whereas that of a control plane is facilitated by a controller.The controller learns network topologies and makes traffic forwarding decisions.However,some serious vulnerabilities are gradually exposed in the topology management services of current SDN controller designs.These vulnerabilities mainly exist in host tracking and link discovery services.Attackers can exploit these weak points to poison the network topology information in SDN controllers.In this study,a novel solution is proposed to defend against topology poisoning attacks.By analyzing the existing topology attack principles and threat models,this work constructs legal conditions for host migration to detect host hijacking attacks.The checking of the Link Layer Discovery Protocol(LLDP)source and integrity is designed to defend against link fabrication attacks.A relay-type link fabrication attack detection method based on entropy is also designed.Results show that the proposed solution can effectively detect existing topological attacks and provide complete and comprehensive topological security protection.

Prediction and Analysis of Society’s Networks

According to the information theory model, I use the qualitative analysis to explain the information flows through the media channel become news. Besides, I make use of a pyramid model to expound the relationship among each media. I combine the information theory model into the prediction process, taking advantage of curve fitting and listing out different ratios of media capacities. Finally I get the small relative error between the fitting result and the reality. Based on the ELM model, I classify the information in two ways on the basis of the four specific factors. By taking the influence degree of public opinion into account, I quantify the factors with different ratios to determine how they could be used in information spreading.

基于SNMP的拓扑增强识别算法

网络拓扑发现对于许多关键网络管理任务来说至关重要.然而,随着网络规模的不断增大,网络结构的愈发复杂,之前的基于SNMP的网络拓扑发现算法存在难以有效识别子网类型和多IP设备,拓扑效率、准确率低等问题.针对上述问题,本文提出了基于SNMP的拓扑增强识别(SNMP-based topology enhanced identification,SNMPTEI)算法.首先,启发式地确定子网IP地址并对其发送探针,根据探测结果来判断子网类型,在确定子网类型后及时终止探针注入防止网络负载过大;其次通过MIB-II记录的系统信息设置设备指纹,结合设备类型识别算法对终端主机IP进行设备指纹鉴定,以达到识别多IP设备的目的.实验结果表明,此方法在仿真网络中可有效识别子网和多IP设备,同时降低了网络负载,探测准确率达到了96.43%.

双负载磁谐振S-LCL无线充电系统频率分叉分析

磁耦合无线充电系统在过耦合情况下会出现频率分叉现象,从而导致频率谐振点系统性能大幅降低。针对无线充电系统存在的频率分叉现象,目前已有文献大多都基于SS结构等基本拓扑进行研究,而缺少对S-LCL等复杂谐振结构频率分叉现象的研究,因此选择对双负载磁谐振S-LCL无线充电系统的频率分叉进行研究。首先分析了双负载系统输出特性随工作频率的变化情况。然后,利用谐振频率下的阻抗特征推导出双负载系统可以规避频率分叉现象的条件以及分叉谐振频率的表达式。仿真分析了耦合系数与负载阻值对双负载磁谐振S-LCL无线充电系统频率分叉临界点和输出特性的影响,得到了规避频率分叉现象的负载与耦合系数的取值范围。最后,搭建Matlab仿真模型和物理平台对所得结论进行验证。

基于B/S架构的企业资产数据一致性校验系统

针对传统校验系统在运行中存在准确率低、耗时长的缺点,提出基于B/S架构的企业资产数据一致性校验系统设计。将B/S架构模式应用到了企业资产数据一致性校验系统体系结构设计和企业资产数据一致性校验系统网络拓扑设计中,完成了系统的硬件设计;通过预处理企业资产数据,设计了企业资产数据的一致性校验流程,完成了企业资产数据的软件设计,实现了企业资产数据的一致性校验。实验结果表明,所提出的校验系统不仅可以解决校验准确率问题,还可以提高企业资产数据的校验效率。

SDN全网拓扑发现及链路时延测量方法研究

当前SND被广泛应用到流量工程、安全监测等领域,为了进一步提升SND应用的可靠性,对这一技术应用过程中表现出的技术难点进行研究。文章考虑到SND整体应用过程相对复杂,主要介绍了全网拓扑发现方法与链路时延测量方法。研究发现:NSGA—Ⅱ节点选择算法可以有效平衡测量节点与测量路径间的制约关系,为网络链路延时测量节点问题的解决提供有效的支持。通过在当前网络体系发展过程中,能够通过快速、完整获取网络结构,并对相关性能进行统计收集的方式,为SND研究发展提供助力,满足当前人们对网络体系可持续发展的实际需要。

基于SNMP的网络拓扑发现算法

网络拓扑发现是网络管理中一项非常重要的技术。鉴于现在越来越多的网络设备都支持SNMP协议,提出了基于SNMP的网络层拓扑发现和链路层拓扑发现算法。网络层的拓扑发现算法有效的解决了路由器的多IP地址问题。对于链路层的拓扑发现,通过结合基于网桥转发表和基于网桥生成树两种算法的优点,提出了一种新的链路层拓扑发现算法。该算法能够快速准确地计算出整个被管网络的二层和三层拓扑结构,而且适用范围广泛。

基于SNMP协议的网络拓扑发现算法

网络拓扑发现对于现代网络管理是一个重要的课题,尤其是第2层网络拓扑发现是一个难题.针对这一难题,基于大多数网络设备都支持的SNMP协议,提出了一个快捷、高效的算法,并对该算法进行了详细的描述,用该算法进行了真实环境的测试,测试结果和真实网络情况完全吻合,说明了此算法是一个有效的拓扑发现算法.

基于SNMP的网络拓扑发现研究与实现

介绍了SNMP(简单网络管理协议)及MIB-Ⅱ规范,详细地描述了基于SNMP的网络拓扑发现技术的实现原理。针对现有基于SNMP的网络拓扑自动发现算法复杂度较高的缺点,提出了更为有效的网络拓扑实现算法,合理利用二叉排序树和判断相邻路由器IP等方法来减少重复访问路由器次数,从而使算法复杂度从可访问路由器的3次幂降为2次幂,并指出这是基于SNMP的网络拓扑发现最低可能阶次。提高了网络管理的效率和质量,对开发和改进网络管理系统有较大的实用价值。

SNMP网络管理平台NetInsight的设计与实现

介绍了一个实用SNMP网络管理平台NetInsight的设计与实现,其特点在于简单实用,并在某些方面具有自己的特色与创新.首先给出了NetInsight的系统结构;然后分别介绍了NetInsight提供的高效的拓扑发现工具、SNMPMIB的通用数据库实现、通用的性能管理工具以及智能的告警管理工具;最后是对该网管平台的评价和下一步的工作.

基于SNMP的网络层拓扑发现算法研究与改进

目的:研究并改进现有网络层拓扑发现算法,解决其在路由信息无法完整反映所有路由链路时网络拓扑发现不完整的问题。方法:结合自主研发的综合业务管理系统软件,分析策略路由会导致现有算法无法完整发现网络拓扑的原因,利用设备类型进行判断并使用IP地址表对现有算法进行改进。结果:提出了一种路由、交换设备和计算机的识别方法,并实现基于路由信息表和IP地址表相结合的网络层拓扑发现算法。结论:实验证明新算法在路由信息不能完整反映所有路由设备之间的连接时能完整地发现网络拓扑,具有一定的应用和推广价值。

基于OSPF协议的网络拓扑发现技术的实现

现有的网络拓扑发现算法大多是基于ICMP和SNMP协议的,在拓扑发现的准确性、完整性、实时性以及性能方面,都或多或少地存在一些缺陷.提出利用OSPF协议实现网络拓扑发现的算法,给出了实现方法和实验结果,这种基于OSPF协议的网络拓扑发现技术可以很好地弥补现有网络拓扑发现技术的不足,具有广阔的应用前景.

一种基于SNMP的链路层拓扑发现算法

为提高链路层网络拓扑发现效率,提出一种基于简单网络管理协议的拓扑发现算法。将交换机间的连接网络用树形结构表示,自顶向下逐层确定每个交换机的连接关系。通过修改连接关系的判定条件,并结合线程池和哈希查找技术,提高拓扑发现的效率。实验结果表明,该算法能快速准确地获得完整的网络拓扑结构。

一种基于SNMP协议的网络拓扑发现改进算法

本文对现有的几种主要的网络拓扑发现方法进行了研究分析,提出一种基于SNMP协议的改进算法。该算法可以发现指定深度网络的所有路由设备及其子网,解决了网络拓扑发现中不完整的问题。仿真实验结果表明,该算法能够快速准确地发现网络拓扑结构,具有可行性和有效性。