基于小波技术的网络流量分析与刻画

大量研究结果表明实际网络流量具有明显的尺度特性，在大尺度上表现出自相似，在小尺度上表现出多重分形。多重分形为刻画流量在小尺度上的奇异性提供了良好的数学框架，而小波变换对具有长程依赖性的流量起到了去相关的作用，因此有必要利用小波技术来研究多重分形。为了能全面有效地刻画现代网络特征，利用小波技术对实际流量进行分析，首先判断流量的全局特性与局部特性，然后对流量进行不同分组，分别采取组内打乱和组间打乱顺序的方法，深入探讨影响多重分形的因素，最后发现均值和方差对多重分形有较大影响。     

近似自相似性在信息分类中的评估作用

根据构建概念格过程中概念聚类的特性,本文引出了概念格图形的近似自相似性这一特征作为信息分类的评估系数。结论证明,以一个子概念格为基块的概念格图形的近似自相似性越高,那么这个子概念格中的信息在当前信息分类中越重要。以此为依据,可以评估信息分类中某类信息是否满足分类目的。     

移动Ad Hoc网络自相似业务排队性能分析

对实际网络业务大量的测量表明,网络中的业务量存在着自相似特性,移动Ad Hoc网络中的业务同样具有该特性.目前对于移动Ad Hoc网络方面的研究只限于实测和简单的定性分析.采用更接近实际情况的队列长度有限G/D/1排队模型对移动Ad Hoc网络性能进行了分析和仿真,结果表明自相似业务导致排队性能变差,缓存匮乏,时延和分组丢失概率恶化.为此提出了基于网络规划模型的适用于自相似业务的路由算法.该算法利用多路径备份路由,当链路失效时可以迅速地寻找到新的替代路由,减小缓存中排队时延和丢包率,并对网络的发射功率进行优化提高信道空间的复用度.仿真结果表明,该算法可以改善分组丢失概率,提高网络吞吐量,降低时延.     

基于ON/OFF源模型的OBS汇聚算法研究

近年来,大量研究表明,网络业务流量呈现长相关、自相似的特性,采用ON/OFF源模型生成自相似流能够比较真实地反映现实网络中的业务流量。光突发包的汇聚算法是光突发交换的关键技术之一,利用ON/OFF模型生成的自相似流对几种典型的OBS汇聚算法进行研究。仿真表明,不同算法对自相似的影响不同。     

基于网络流量自相似的网络性能测量技术研究

网络性能测量是网络行为分析的基础.本文对基于网络流量自相似的特性对网络性能测量的相关内容以及网络性能指标的测量与分析进行了系统的介绍,并对网络性能测量的下一步发展进行了展望.     

Queue Analysis and Multiplexing of Heavy-tailed Traffic in Wireless Packet Data Networks

Recent research based on traffic measurements shows that Internet traffic flows have a fractal nature (i.e., self-similarity property), which causes an underestimation of network engineering parameters when using the conventional Poisson model. Preliminary field measurements demonstrate that packet data traffic in wireless communications also exhibits self-similarity. In this paper, we investigate the queuing behavior of self-similar traffic flows for data applications in a packet-switching single-server wireless network. The traffic is generated by an on–off source with heavy-tailed on periods and exponentially distributed off periods. We extend previous analysis of a relation among the asymptotic distribution of loss probability, traffic specifications, and transmission rate for a wireline system to a wireless system, taking into account wireless propagation channel characteristics. We also investigate the multiplexing of heavy-tailed traffic flows with a finite buffer for the downlink transmission of a wireless network. Computer simulation results demonstrate that assumptions made in the theoretical analysis are reasonable and the derived relationships are accurate.     

羊肚菌菌丝的分形特征

用菌丝显微图像灰度的统计分布图得到羊肚菌菌丝具有分形学的自相似性并求出其分维数。对比羊肚菌固体、液体不同培养方法下菌丝的形态及分维数,结果为分枝越多分维数越大;对比不同菌种羊肚菌和蛹虫草菌丝的分维数。说明分维数的差别对于菌丝形态特征的研究可以提供基础。     

基于自相似通信量输入的带宽分配算法

自相似网络通信量的发现及其对排队系统性能的影响已经得到了大量的研究。该文研究了自相似通信量输入条件下FIFO排队系统的带宽分配问题。首先得到了假设条件下排队系统的所要求带宽的上界。然后在此基础上研究了同种和异种自相似输入通信量输入情况下的带宽分配策略。最后通过仿真分析验证了所得到结果的有效性。     

Using Self-Similarity to Cluster Large Data Sets

Clustering is a widely used knowledge discovery technique. It helps uncovering structures in data that were not previously known. The clustering of large data sets has received a lot of attention in recent years, however, clustering is a still a challenging task since many published algorithms fail to do well in scaling with the size of the data set and the number of dimensions that describe the points, or in finding arbitrary shapes of clusters, or dealing effectively with the presence of noise. In this paper, we present a new clustering algorithm, based in self-similarity properties of the data sets. Self-similarity is the property of being invariant with respect to the scale used to look at the data set. While fractals are self-similar at every scale used to look at them, many data sets exhibit self-similarity over a range of scales. Self-similarity can be measured using the fractal dimension. The new algorithm which we call Fractal Clustering (FC) places points incrementally in the cluster for which the change in the fractal dimension after adding the point is the least. This is a very natural way of clustering points, since points in the same cluster have a great degree of self-similarity among them (and much less self-similarity with respect to points in other clusters). FC requires one scan of the data, is suspendable at will, providing the best answer possible at that point, and is incremental. We show via experiments that FC effectively deals with large data sets, high-dimensionality and noise and is capable of recognizing clusters of arbitrary shape.     

自然图象单像素灰度值的统计特性研究

本文针对自然图象中单像素灰度值的统计规律进行实验和分析，发现对数正态分布可以对之进行粗略、简单的建模。此外，本文还给出了判断所给定的数据序列是否为统计自相似数据的有效判断方法，并在此基础上断定自然图象具有明显的自相似特性，从而得到针对单像素灰度值且较对数正态分布更精确的建模。最后，本文还给出了对自相似参数日进行估计的两种有效策略。