一种基于两级存储结构的网络流量测量算法

为了准确而完备地测量高速骨干网中各条流的流量,需要容量大且速度快的存储器来保存所有流的状态信息,因而代价极高。该文提出了一种基于两级存储结构的网络流量测量算法。两级存储结构由容量小但速度快的一级存储器和容量大但速度慢的二级存储器构成。考虑到网络流量分布的Quasi-Zipf法则,测量算法尽量将大流量流的状态信息保存在一级存储器中,将小流量流的状态信息保存在二级存储器中,较好地解决了存储器容量和速度之间的矛盾。仿真结果表明,与抽样测量相比,该算法具有较小、较平均的测量误差。 关键词：     

军事电子网络对抗中网络流量异常识别

由于军事电子网络对抗中的流量具有海量、高速的特征,且异常流量具有较强的特征隐蔽性,因此,采用传统算法进行异常流量识别往往均有耗时大、有效识别率低的缺陷.为此,提出基于主分量分析与多时间序列数据挖掘算法相结合的军事电子网络对抗中网络流量异常识别方法.针对各维熵值时间序列之间具有关联性的特点,利用支持向量机算法进行多维流量数据分类,为异常流量的识别提供数据支持,依据主分量分析法对维数进行缩减,对信息熵值异常子空间与正常子空间进行有效分离,实现军事电子网络对抗中网络异常流量的有效识别.实验结果表明,采用改进算法进行军事电子网络对抗中网络流量异常识别,能够有效提高异常流量识别率及识别准确性,有效的保障了军事电子网络的安全性,具有显著的优越性.     

利用流控设备管理和优化校园网流量

由于P2P技术迅猛发展,中国药科大学校园网出口拥塞严重,迅雷和网络视频占用了大量带宽,导致校园网用户的正常应用无法保障。为了解决此问题,中国药科大学在校园网出口部署了流控设备,对出口流量进行优化和管理,有效的检测和防止非关键应用对网络带宽资源的大量消耗,保证关键应用的带宽使用,校园网出口流量得到了有效的管理和控制。     

网络流量异常检测及分析的研究

网络流量异常检测及分析是网络异常监视及响应应用的基础,是网络及安全管理领域的重要研究内容.本文探讨了网络流量数据类型、网络流量异常种类;从流量异常检测的范围、流量异常分析的深度、在线和离线异常检测方式等方面归纳了流量异常检测的研究内容;综述了已有的研究工作针对不同应用环境和研究内容所采用的不同的研究方法和技术手段,并分析了各种研究方法的特点、局限性和适用场合等;最后本文还对现有研究工作存在的问题及有待于进一步研究的课题进行了探讨.     

网络流量分析系统的设计与实现

现有的网络管理系统普遍存在以下问题：一是缺乏对用户用量、用法的监控和管理;二是缺乏对安全、计费、网络优化等应有的增值服务功能;三是不支持网络管理员和高级经理对网络管理高层次业务需求分析。设计的网络流量分析系统作为对网络管理系统的有力补充和提升,解决了常规网管系统的缺陷,直接从网络管理高层次需求入手,满足客户对网络使用状况分析、网络安全防卫、基于用量的计费模式等需求。     

On change detection and displacement vector estimation in image sequences

Recent developments in the areas of displacement vector estimation as well as dissimilarity grading by a maximum likelihood ratio can be related to each other quantitatively in such a way that dissimilarity grading is reduced to interframe displacement estimation.     

Comparing ada and FORTRAN lines of code: Some experimental results

This paper presents the results of a study comparing pairs of functionally equivalent programs written in the FORTRAN and Ada languages. We found the Ada programs to require more lines of code than their functionally equivalent FORTRAN counterparts. However, we also observed that the overhead for Ada diminishes as program size increases. Our limited data suggested that there may be a cross-over point beyond which the size of an Ada program would be smaller than a functionally equivalent FORTRAN program. We explore some of the reasons for these economies of scale when using Ada. The implications of our findings on software cost estimating are also discussed.     

基于软件规模度量求精分析应注意的问题

软件规模度量是软件工程领域研究的一个重要方向,具有很强的系统性、理论性和实践性.文章从面向实际应用的角度出发,论述了估算模型选定、需求分析、软件开发人员技能评估、待评估系统的类型特点同软件规模度量之间的关系.浅析了四者在软件规模度量求精分析中的重要作用.     

软件度量中估算方法分析

根据软件度量中的估算方法的应用情况,分析了其中具有代表性的估算方法,在此基础上比较了这些代表性估算方法的异同,并进一步研究了它们各自的特点,指出了它们在软件生命周期中不同时期的应用及应注意的问题。     

Direct measurement vs. indirect inference for determining network-internal delays

We consider direct techniques for measuring network-internal delays that rely on network routers as measurement nodes, and indirect techniques that rely on end-to-end measurements and infer delay distributions on the common internal paths. The direct technique does not require any additional infrastructure support, and can thus be directly applied to the analysis of network performance and the study of the Internet. The use of routers for measurement also results in a simple mathematical formulation of the delay estimation problem, thereby providing robustness and accuracy. However, the irregularity of Internet routing somewhat limits the applicability of the direct technique. In contrast, indirect techniques are not sensitive to routes to internal nodes, but accumulate increased errors over longer paths. We use simulation to compare the direct and indirect methods and present results from network measurements exploring the applicability and limitations of these techniques.     

网络中突发业务自相似建模及其Hurst系数估计

提出了一种基于自回归AR模型的Hurst系数的估计方法，并给出了数学推导过程。采用真实网络突发业务的仿真结果表明，该文所提出的方法比传统的R／S法等估计方法具有更高的估计精度，能更好地反映真实网络业务流量的自相似性。该方法可望用于网络业务流量的管理和网络拥塞控制。     

Towards automated progress assessment of workpackage components in construction projects using computer vision

Traditional methods of collecting data on the progress of construction projects often involve human judgement, high costs, and are too infrequent to provide managers with timely and accurate control data. This study proposes a system that aims to address some of these shortcomings through automation. Our first contribution is a framework for the automatic generation of work packages. We describe the conceptual model and develop a prototype implementation, based on the results of a survey designed to capture the current practice of formulating work packages as performed in the industry. Our second contribution is a system that employs computer vision (CV) techniques to report on the progress of these work packages automatically. This is achieved by analysing sequences of digital images acquired regularly by on-site cameras. The result of this analysis, when compared with the expected state of construction, provides progress feedback on the work packages, allowing a project to be monitored more effectively.     

互联网流量分类中流量特征研究

互联网流量特征用于描述和测量网络流量,是开展流量分类的重要基础。为了系统性分析互联网流量特征,首先根据统计对象或统计角度研究流量特征的归类法,随后展开评述每类流量特征;针对流量特征的稳定性问题,分析报文抽样、网络环境和模糊化技术对流量特征的影响;从分类能力、稳定性、时效性和分类粒度等方面评述流量特征的优缺点,为流量统计特征应用提供指导性建议;最后总结流量特征的未来研究方向。     

基于分布式统计时间序列的网络流量分析

研究网络数据在分布式存储下的相关性,有利于入侵检测整体的学习和指导优化数据的存储.重点研究了网络传输过程中各种类型数据的流量的这种相关性,提出了一种基于分布式统计(DS)的时间序列分析方法:根据网络协议间的关系将数据包分组,分析数量关系并给出报警阈值.仿真实验结果表明,该方法能较好地发现各种网络攻击.     

基于时间序列图挖掘的网络流量异常检测

网络流量异常检测要解决的核心问题之一是获得信息的全面性和流量信息描述的准确性.针对现有网络异常流量检测方法分析多时间序列的不足,提出了一种基于图挖掘的流量异常检测方法.该方法使用时间序列图准确、全面地描述用于流量异常检测的多时间序列的相互关系;通过对项集模式进行支持度计数,挖掘各种频繁项集模式,有利于对各种异常流量的有效检测;通过挖掘各项集之间的关系,引入了项集的权重系数,解决了流量异常检测的多时间序列相互关系的量化问题.仿真结果表明,该方法能有效地检测出网络流量异常,并且对DDos攻击的检测效果明显优于基于连续小波变换的检测方法.     

基于改进非广延熵特征提取的双随机森林实时入侵检测方法

在网络骨干链路的高速、大数据量环境下,相对于正常数据,攻击及异常数据相对较少,进行实时入侵检测难度大。针对此问题,提出了一种基于改进非广延熵特征提取和双随机森林的实时入侵检测方法。利用非广延熵,提取出流量属性取值分布的多维特征,通过对非广延熵的改进来降低特征间的相关性。使用完整的特征样本集建立第一个随机森林检测模型,使用包含攻击数据的特征样本子集建立第二个随机森林检测模型,通过双随机森林检测算法实现对少量异常的有效检测。实验结果表明,该方法能够在有限流量信息的基础上获得较高的检测精确率和召回率,其时间和空间复杂度适当,适合于对骨干链路的实时入侵检测。     

On the conversion between IFPUG and COSMIC software functional size units: A theoretical and empirical study

Since 1984 the International Function Point Users Group (IFPUG) has produced and maintained a set of standards and technical documents about a functional size measurement methods, known as IFPUG, based on Albrecht function points. On the other hand, in 1998, the Common Software Measurement International Consortium (COSMIC) proposed an improved measurement method known as full function points (FFP). Both the IFPUG and the COSMIC methods both measure functional size of software, but produce different results. In this paper, we propose a model to convert functional size measures obtained with the IFPUG method to the corresponding COSMIC measures. We also present the validation of the model using 33 software projects measured with both methods. This approach may be beneficial to companies using both methods or migrating to COSMIC such that past data in IFPUG can be considered for future estimates using COSMIC and as a validation procedure.     

高速主干网测量系统的设计与实现

网络测量是监控管理网络的基础。高速网流量采集和数据归并是它的难点问题之一。文章以CERNET网络管理与流量计费为背景,实现了一种高性能可扩展的网络被动测量系统Linuxflow。     

Traffic Matrix Inference in IP Networks

While the traffic matrix is used as basic data for many network planning tasks, it must be recognized that its inference in IP networks is particularly difficult and error prone. This paper discusses the issue of defining representative traffic demands and surveys proposed techniques for directly measuring elements of the traffic matrix or inferring their value from link measurements.