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双语推荐：物理拓扑发现

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随着计算机网络应用的蓬勃发展,以太网变得越来越复杂,为了方便管理,拓扑自动发现变得越来越重要.物理拓扑主要是对链路层和物理层的设备的发现,设备间的连接关系.该文提出一种用于获取物理拓扑的方法.
With the flourishing development of computer network applications, Ethernet is becoming more and more complex, in order to manage it easily, automatic topology discovery is becoming increasingly important. The physical topology is mainly the connection relation between the discovery of the link layer and the physical layer device. In this paper, raise a method used to obtain the physical topology.

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确的网络物理拓扑信息对许多网络管理任务起着至关重要的作用，而实际网络中可能存在不易被发现的“哑”设备，这给网络拓扑发现带来了很大难度，传统的拓扑发现算法不能全面发现网络设备。针对这种情况，提出一个大型的异构多子以太网物理拓扑发现算法。算法首先利用通用的 MIB 信息，得到任意两个节点间的直接连接，然后选择具有最小可能连接数的节点，使用扩展规则使所有的 RSs 完整。实验结果表明，不需要修改任何硬件或软件资源，能够发现“哑”设备，保证拓扑发现与给定输入库兼容。该算法在地址转发表不完整的情况下，能够高效、全面、正确地发现网络的物理拓扑结构。
The exact network topology information is very important for many network management tasks,and some "dumb"devices may be not found in the network,so it is very difficult to conduct the network topology discovery because the classical topology discovery algorithm can not fully discover net-work devices.For this situation,a physical topology discovery algorithm of large heterogeneous multi -subnet ethernet networks is presented in this paper.Firstly,it discovers all direct connections between any two MIB -enabled nodes by the general information of MIB,and then selects two nodes with mini-mum number of potential connections to use the extension rules for complete RS.The experimental results show that this algorithm does not require any hardware or software modifications and can discover the"dumb"devices and guarantee discovering the topology which is compatible with the given input library. In the case of incomplete address forwarding table,it can discover physical layer topolo

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物理拓扑信息对于众多网络管理任务是非常重要的,而传统的拓扑工作或者只注重于网络层,或者只提供交换机到交换机的连接关系,不能满足网络管理的需要。本文提出了基于SNMP MIB信息库的物理拓扑发现算法,该算法针对异构多子网网络特点,采用归类栈、逐点高效遍历结点的方法,使拓扑发现不但在覆盖范围、效率和准确度上有提高,而且对网络中哑设备的分类也提供了一种新方法。
Knowledge of the physical topology is essential to a number of network management tasks . Former work only focused on Layer -3 topology discovery or only provided the connection between switch and switch.Obviously, this can''t meet the needs of network management tasks .The algorithm of physical topology discovery presented in this paper relies on standard SNMP MIB information and meets the environment for heterogeneous multi -subnet.It adopts classified stack and method of traversing nodes point by point efficiently.All of above makes the algorithm not only step on a new level in the coverage of topology discovery , efficiency and accuracy, but also provide a new way in classifying dumb devices .

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根据城域网网管软件开发过程中的设计经验，本文阐述了一种基于路由接口地址空间和SNMP异步扫描的网络物理拓扑快速发现的方法，并在具体项目中予以实现和应用，解决了拓扑发现过程中面临的设备搜索的完整性、拓扑发现的速度和拓扑判定的准确性三个主要问题，并取得了良好的效果。
According to the experience of metropolitan area network(MAN) management software design and development, this paper proposes for quick discovery of metropolitan area network physical topology based on SNMP asynchronous scan. The method has been applied to project and solved problems on the integrity of the device search, the topology discovery speed, the accuracy of topology identification during topology discovery, which has got good effection in project application.

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随着互联网技术以及计算机技术的发展,网络安全越来越受到人们的重视。在现实当中,可以用复杂网络的思想解释和研究很多真实的网络,而社区结构正是复杂网络的一个很重要的特征。因此,提出一种基于社区结构的网络布局算法,利用附在网络社区发现算法划分网络当中的节点,并且抽象社区为一个节点,每个节点之间相互关联,形成一个网络。而社区中心点的位置采用物理类比的方法来确定,运用条件择优方式完成网络拓扑的布局优化。这种物理布局算法相比传统的布局算法而言更加安全高效,结构也更加清晰。
With the development of Internet and computer technology, network security attracts people''s attention. In reality, you can use the network to explain complex ideas and analyse the actual network, and complex network is a very important fea-ture of community structure . Therefore, a network layout algorithm is proposed based on the community structure using the on-line communities attached to the network discovery algorithm dividing the nodes, and abstracts the community as a node , and the correlation between each node form sa network.The algorithm uses physical analogy method to determine the community center point and the conditions merit accomplishinglayout optimization of the network topology. Compared with the traditional layout algorithm,this physical layout algorithm is better at security, efficiency and structure.

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针对短波IP网络中物理连接存在生命周期和接收节点选择方式不同对网络拓扑结构和性能产生的影响,提出了一种基于边生命周期和接收节点多种选择方式的随机图模型。模型中节点之间边生命周期服从正态分布,而新边建立的节点选择方式按照随机选择、度值择优选择和度值反择优选择的方式,用来模拟短波IP网络不同的通信过程。理论分析和仿真也发现,接收节点选择方式的不同将会对网络的度分布、平均最短距离、网络总的度值和节点最大度值及聚集系数都产生影响,而小的连接生命周期将显著减少网络中总的度值和节点的最大度值,减少对物理层资源的占用,提升网络的效能。
In HF IP network, the life cycle of physical connection and the different selection method of the receiving node will have an impact on the network topology and performance. A random graphics model is proposed based on the edge life cycle and different received node selection methods. The life cycle of the edge obeys the normal distribution. What is more, three node selection methods are presented including random selection,preferred selection based on the node degree or the bottom of the node degree. Theoreti-cal analysis and simulation demonstrate that differences of the receiving node selection method will affect the network degree distribution, the average shortest length, the total value of network degree, the maxi-mum degree for a node and the clustering coefficient. At the same time,reducing the edge life cycle will decrease the total degree of the network and the value of maximum degree of a node,and also optimize the physical resource utilization and increase network efficienc

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通过挖掘中医理论的科学内涵,发现中医证候内蕴点集拓扑结构。运用这一理论和方法,可以使证候高阶多维的非线性结构,降阶降维成为一阶一维线性结构,从而展现出证候复杂多变的全貌;可以开展证候的发生规律研究,呈现出证候动态演化过程中子集合的衍生规律,以及证候不同子集合主症与次症的变化规律,来阐释中医证候判定诊断标准的科学内涵;可以开展中医证候的结构表征研究,实现证候"数学结构—物理结构—生物结构"的3个层面客观量化表征;可以对中医辨证论治过程的结构进行研究,实现证候不同形式的理法方药精准对应;通过计算机仿真技术,可以建立中医证候治法与方药的仿真数据平台;运用临证数据,通过文献梳理对比,可以实现单一证候、复合证候及其证候群理法方药知识的创新;可以开展中医证候疗效评价研究,明确中医证候疗效评价在多层面多维度的指标体系,促进辨证论治水平的大幅度提高,为中医学理论的现代语言诠释提供新的概念。
Based on the theory of topological structure within the syndrome of tradition Chinese medicine (TCM), the high order multiple dimensions and nonlinear structure of syndrome can be cracked. And the panorama of complex and changeable syndrome can be showed. The dynamic evolving law of sub-sets of syndromes and the changing rule of the main signs and symptoms with the secondary signs and symptoms can be interpreted. Therefore, the evolving law of sub-sets of syndromes and the accurate corresponding law of prescriptions and medicines can be realized. And the scientific connotation of dynamic evolving rule of syndrome can be revealed. Studying on the occurrence regularity of syndrome, the structure characterization of TCM syndrome can be carried out. And the "mathematical structure-physical structure-biological structure" can be revealed. Along with the mass new specific forms of syn-dromes to be cracked, the simulation data platform of therapeutic methods with prescriptions and m

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