高速网络的自相似业务模型及其性能评价

文中介绍了９０年代高速网络性能评价领域中一个重大发现，即真实的网络业务具有自相似性。传统的基于Ｍａｒｋｏｖ模型的性能评价结果对自相似业务已不再适用，需要研制新的模型与工具。文中介绍了自相似过程的数学定义及其性质，讨论了重尾分布和诺亚效应及它们与自相似过程的关系，还介绍了几种生成自相似业务的方法和自相似业务模型下队列系统性能评价方面的研究成果。     

基于自相似网络流量模型的分析

流量模型是流量预测和网络性能评价的核心基础。好的流量模型必须能够准确描述网络实际流量的特征情况,才能准确预测流量状况。随着网络业务类型不断增加,实际网络中业务流特性越来越复杂,表现为长相关性和自相似性等。本文重点分析了当前广泛使用的几种自相似模型,对自相似业务的分析和处理具有一定的指导意义。     

自相似网络的时延抖动性能仿真分析

自相似性对网络性能产生了影响是当前的研究热点。建立了一种基于FBM的自相似网络排队时延抖动分析模型,重点讨论了自相似流量作为输入时对排队系统的时延抖动的影响。对理论分形流量和实际测量流量进行了仿真实验,验证了结果的正确性和有效性。实验结果表明：自相似流量长相关强弱的程度对排队系统时延抖动特性具有非常不同的影响,尤其是在缓存较大的情况下。同时,还发现网络流量中长相关发生作用时状态转变与排队系统本身的参数也有关,这是新的发现,对实时业务的网络性能评价具有重要的参考意义。     

网络流量自相似性影响因素的研究

网络流量特征是分析和研究网络性能、规划网络建设的基础。由于自相似模型能够更加真实地描述网络传输的特性,通过生成自相似性的流量进行仿真研究。提出将业务源流量自相似性与网络传输的TCP协议相结合进行研究的方法,探讨影响自相似流量的因素,分析网络行为随参数变化的情况。仿真结果表明业务源流量的自相似与网络状态无关,而网络传输的TCP协议自适应改变网络状态,从而间接改变网络流量的自相似性,但并不能消除业务源流量的自相似性。     

基于FARIMA的网络建模与性能分析

给出了利用FARIMA模型进行建模、拟合实际网络流量的方法和参数估计的具体步骤,研究了长短相关对网络性能的影响.研究结果表明,不论长相关还是短相关,FARIMA模型对实际业务拟合二者都非常接近,当缓存较小时,网络性能将由短相关特性支配,而且随着缓存增加,长相关业务下系统性能的衰减要比短相关业务下衰减的慢,这些发现对今后网络设计性能研究具有重要的参考价值.     

自相似参数辨识与汇聚无线业务尺度特性分析

Hurst参数是衡量网络流量自相似程度和突发性的重要参数,在时域R/S统计、方差 - 时间图法和频域周期图法的基础上,提出一种最优化线性回归小波模型,实现小波域内Hurst参数的准确有效快速辨识.研究了WLAN中多个输入业务源的汇聚过程以及汇聚的多输入自相似业务源统计特性.仿真实验比较了传统的以及基于最优化线性回归小波模型的Hurst参数辨识方法,验证了理论分析中汇聚自相似业务也呈现自相似性的结论,且仿真结果表明,汇聚业务的突发性得到加强而不是削弱.研究结论对网络流量的准确建模以及网络传输中流量控制和优化网络资源配置以及提高网络性能具有重要作用.     

网络业务多重分形特性研究

聚集网络业务的多重分形特性既能考查多尺度下业务的突发性,又能描述突发性相对于时间的变化,是网络业务最显著的统计特性之一.使用网络流量的联合多重分形(JMF)模型 [7]对实际数据进行分析及参数估计,检测网络业务多重分形结构,并产生理论多重分形流量.将JMF模型理论流量、基于自相似特性的分形布朗运动(FBM)模型的理论流量和实际测量流量作为OPNET仿真驱动,进行网络性能仿真.仿真结果显示由JMF模型产生的理论流量与实际测量流量的性能更为接近,进一步验证了网络业务的多重分形特性.     

长程突发通信量的分数自回归预测

以数据包传输的通信量在不同网络条件下均表现出自相似性,自相似通信量在各时间尺度上均具有长程突发特性,其是以泊松过程为模型所描述的短程相关通信量所无法描述的.近来对自相似通信量的高精度测量与研究证实:网络中广泛存在的重尾特性是通信量自相似产生的原因.同时充分提取通信量的自相似性与重尾特性相关信息,是准确预测长程突发通信量的关键.在一种α-基于平稳过程的自相似通信量模型基础上,提出两种独立的自回归预测方法:FAR(Fractional AutoRegressive)预测、FNAR(Fractional Nonlienar AutoRegressive)预测.对这两种预测值进行不同方案的混合预测得到最终预测结果,进一步提高预测精度.     

一种有效的无线Mesh网络流量整形模型

流量整形对QoS(quality of service)控制有着重要的影响.研究并分析发现,无线Mesh网络具有自相似性,其自相似性对网路的QoS性能具有较大的影响.总结并优化了最近几年发展起来的能够深刻透视计算机网络业务流控制问题的网络演算技术,分析发现统计网络演算可以用来计算性能的概率或统计边界问题,适合于无线Mesh网络.运用统计网络演算建立了无线Mesh网络自相似业务流的贪婪分形整形器的数学模型;推导了贪婪分形整形器的统计性能模型.包括整形器的输出特性、队列长度与延迟等性能;数据分析证明贪婪分形整形器对无线Mesh网络自相似业务进行整形不会增加网络端到端延迟和缓冲区容量需求.     

网络中自相似特征业务的控制管理

分析了网络业务的自相似特性以及这种特性对网络性能的影响。结合自相似性的特点提出了一种新的业务控制机制,以有效提高网络性能。     

Modelling priority queuing systems with varying service capacity

Many studies have been conducted to investigate the performance of priority queuing (PQ) systems with constant service capacity. However, due to the time-varying nature of wireless channels in wireless communication networks, the service capacity of queuing systemsmay vary over time. Therefore, it is necessary to investigate the performance of PQ systems in the presence of varying service capacity. In addition, self-similar traffic has been discovered to be a ubiquitous phenomenon in various communication networks, which poses great challenges to performance modelling of scheduling systems due to its fractal-like nature. Therefore, this paper develops a flow-decomposition based approach to performance modelling of PQ systems subject to self-similar traffic and varying service capacity. It specifically proposes an analytical model to investigate queue length distributions of individual traffic flows. The validity and accuracy of the model is demonstrated via extensive simulation experiments.     

自相似通信量对CSMA/CD性能的影响

大量网络通信量测量研究表明,通信量在长时间尺度上的突发性规律可以用分形或自相似模型来描述。为准确评估CSMA/CD协议性能,基于RMD算法产生近似的FBM,并利用近似FMB构造了自相似通信量模型。基于自相似通信量,采用离散事件仿真技术对CSMA/CD协议建立了排队模型,对网络性能进行了分析,通过与通信量服从泊松到达的仿真结果进行对比,说明了自相似特性对网络性能分析的影响。     

Criticisms of modelling packet traffic using long-range dependence (extended version)

This paper criticises the notion that long-range dependence is an important contributor to the queuing behaviour of real Internet traffic. The idea is questioned in two different ways. Firstly, a class of models used to simulate Internet traffic is shown to have important theoretical flaws. It is shown that this behaviour is inconsistent with the behaviour of real traffic traces. Secondly, the notion that long-range correlations significantly affects the queuing performance of traffic is investigated by destroying those correlations in real traffic traces (by reordering). It is shown that the longer ranges of correlations are not important to mean queue length except in one case with an extremely high load.     

Performance analysis of priority scheduling mechanisms under heterogeneous network traffic

Priority scheduling principle plays a crucial role in the Differentiated Services (DiffServ) architecture for the provisioning of Quality-of-Service (QoS) of network-based applications. Analytical modelling and performance evaluation of priority queuing systems have received significant attention and research efforts. However, most existing work has primarily focused on the analysis of priority queuing under either Short Range Dependent (SRD) or Long Range Dependent (LRD) traffic only. Recent studies have shown that realistic traffic reveals heterogeneous nature within modern multi-service networks. With the aim of investigating the impact of heterogeneous traffic on the design and performance of network-based systems, this paper proposes a novel analytical model for priority queuing systems subject to heterogeneous LRD self-similar and SRD Poisson traffic. The key contribution of the paper is to extend the application of the generalized Schilder's theorem (originally a large deviation principle for handling Gaussian processes only) to deal with heterogeneous traffic and further develop the analytical upper and lower bounds of the queue length distributions for individual traffic flows. The validity and accuracy of the model demonstrated through extensive comparisons between analytical bounds and simulation results make it a practical and cost-effective evaluation tool for investigating the performance behaviour of priority queuing systems under heterogeneous traffic with various parameter settings.     

基于自相似通信量的p-坚持CSMA/CD协议仿真

近年来,大量的通信量测量研究表明实际的网络通信量具有自相似或长范围相关特性。为了准确评估军用网络的性能,论文利用叠加多个ON/OFF信源的方法,建立了自相似通信量模型,并对该模型所产生的序列进行检测,验证了其自相似特性;在此基础上,基于自相似通信量,采用离散事件仿真技术对军用网络中的p-坚持CSMA/CD协议建立了排队模型,通过仿真测试了各种负载下p值对冲突次数、平均等待时间、平均队长以及吞吐率等性能指标的影响,仿真结果表明,根据信道负载的轻重,动态调整p的取值可以提高网络的性能。     

Suggestions of efficient self-similar generators

The growth of Grid computing and the Internet has been exponential in recent years. These high-speed communication networks have had a tremendous impact on our civilisation. High-speed communication networks offer a wide range of applications, such as multimedia and data intensive applications, which differ significantly in their traffic characteristics and performance requirements. Many analytical studies have shown that self-similar network traffic can have a detrimental impact on network performance, including amplified queueing delays and packet loss rates in broadband wide area networks. Thus, full understanding of the self-similar nature in teletraffic engineering is an important issue.This paper presents a detailed survey of self-similar generators proposed for generating sequential and fixed-length self-similar pseudo-random sequences for simulation in communication networks. We evaluate and compare the operational properties of the fixed-length and sequential generators of self-similar pseudo-random sequences. The statistical accuracy and time required to produce long sequences are discussed theoretically and studied experimentally. The evaluation of the generators concentrated on two aspects: (i) how accurately self-similar processes can be generated (assuming a given mean, variance and self-similarity parameter H), and (ii) how quickly the generators can generate long self-similar sequences. Overall, our results have revealed that the fastest and most accurate generators of the six sequential and five fixed-length sequence generators considered are the SRP-FGN, FFT and FGN-DW methods.     

基于超爱尔兰分布的自相似网络排队模型研究

现有网络的业务流研究表明,多种通信业务中普遍存在自相似特性,但是如何对自相似业务流进行建模和分析一直是个难解问题。基于超爱尔兰拟合算法,建立了到达为泊松分布,服务时间为超爱尔兰分布的M/HErD/1/K自相似排队模型,推导得到呼叫损失概率、平均排队队长等排队性能的解析解。在实际业务环境下和传统的M/M/1/K排队模型进行了仿真对比,结果表明M/HErD/1/K模型不仅可有效表征业务流的快挂业务特性,而且能仿真出该网络在业务负荷较重时潜在的运营风险,对实际网络运营管理具有重要的指导作用。     

基于小波域混合高斯模型的自相似流量合成算法

自相似流量特性对网络性能具有重要影响，流量建模与合成是网络性能评价的基本环节．提出了一种基于小波域混合高斯模型的自相似流量建模与合成方法：小波变换的近似Karhunen—Loeve（K-L）变换特性可以有效去除流量过程的长程相关，而混合高斯模型准确地描述了小波系数的非高斯分布．对合成流量进行了统计分析以及排队性能仿真．实验表明该方法能够更准确地对通信流量进行建模和合成，并且具有运算量小（O（N））、流量生成快速等优点．     

A case for exploiting self-similarity of network traffic in TCP congestion control

Analytical and empirical studies have shown that self-similar traffic can have detrimental impact on network performance including amplified queuing delay and packet loss ratio. On the flip side, the ubiquity of scale-invariant burstiness observed across diverse networking contexts can be exploited to better design resource control algorithms. In this paper, we explore the issue of exploiting the self-similar characteristics of network traffic in TCP congestion control. We show that the correlation structure present in long-range dependent traffic can be detected on-line and used to predict the future traffic. We then devise a novel scheme, called TCP with traffic prediction (TCP-TP), that exploits the prediction result to infer, in the context of AIMD steady-state dynamics, the optimal operational point at which a TCP connection should operate. Through analytical reasoning, we show that the impact of prediction errors on fairness is minimal. We also conduct ns-2 simulation and FreeBSD 4.1-based implementation studies to validate the design and to demonstrate the performance improvement in terms of packet loss ratio and throughput attained by connections.