【作者】 朱小钦；

【导师】 朱光喜；

【作者基本信息】 华中科技大学 ， 通信与信息系统， 2004， 硕士

【摘要】 随着网络应用的普及和通信业务的日益增长,互联网变得越来越繁忙,有效的控制管理显得尤为重要。长期以来,网络建模和分析以泊松分布和马尔可夫过程理论为基础,而近年来大量网络业务测量表明网络业务具有自相似特性,这种特征不能由传统模型描述。本文在湖北省多媒体与网络通讯工程重点实验室开放基金项目——“基于α稳定过程理论的自相似网络业务流研究”的支持下,对网络自相似业务建模的理论基础、自相似业务条件下网络的规划设计以及业务控制等进行了研究。本文首先描述了网络业务流中的自相似现象,介绍了自相似的定义和性质,全面叙述了网络业务自相似性研究领域的研究现状,为后续研究奠定了基础。接着本文根据网络业务特征,提出用α稳定分布作为网络建模的理论基础。首先根据α稳定分布的定义和性质分析指出α稳定分布能很好的描述网络中的高斯信号和非高斯信号,同时刻画业务的长程相关性和短程相关性。然后通过实际测量数据的统计分析验证了自相似业务流的数据分布模式。选择具有代表性的业务数据,分别以单位时间内的数据包个数和流量作为分析对象,根据α稳定分布的验证原理,统计验证了网络业务流到达过程服从α稳定分布。然后本文全面探讨了业务的自相似性对网络性能的影响,分析指出在输入业务为自相似业务时,缓冲区的平均队列长度的尾分布呈威布尔函数或双曲线衰减,不同于泊松分布推导的指数衰减,这些特征导致实际的时延和丢包率远远高于传统模型推导的结果,自相似程度越高,性能下降越明显。如果增大缓冲区容量,虽然能适当降低丢包现象,但时延增长太大;如果提高带宽,则可以同时减小丢包率和时延。因此,在进行网络规划设计时,必须结合业务特征确定网络配置参数。最后,本文提出了一种拥塞控制机制,该拥塞控制机制利用业务流的长程相关性来预测未来时间段的业务流量,根据预测结果动态调整发送速率,充分利用网络资源,有效的避免拥塞。本文采用LFSN(线性分形稳定噪声)过程对自相似业务建模,给出了LFSN过程的预测算法,将预测算法与提出的拥塞控制机制结合,改进基本的AIMD(线性增加成倍减小)速率控制算法,对改进算法进行了仿真分析,实验结果表明该算法能有效的提高网络吞吐量和利用率,减小丢包率。最后,分析指出该拥塞控制机制具有较好的实用性。更多还原

【Abstract】 With the popularization of network application and increase of communication services, Internet is becoming more and more busy. It’s very important for effective control and management polices to be implemented. For a long time, traffic modeling and analysis is based on Poisson distribution and Markov process. But recently measures of network traffic have shown the self-similar nature of network traffic. And this property can’t be described by traditional model. Under the support of project of “self-similar network traffic research based on alpha stable process” granted by multimedia and network communication engineering laboratory, some research work has been done in the area of theory foundation of traffic modeling, network design and traffic control.Firstly, self-similar phenomenon in network traffic is depicted. Definition and properties of self-similar process are presented. A comprehensive introduction of research results in the area of traffic self-similar is given. All these form a basis for latter research work.Secondly, this paper proposes the use of alpha stable distribution in traffic modeling. Analysis based on the combination of alpha stable distribution and properties and network traffic property shows validity of application of alpha stable process to traffic modeling. Moreover, this point is verified through statistical analysis of real traffic data. A representative trace is selected and regrouped separately according to packet count in unit time and throughput in unit time. Then this trace is thoroughly analyzed according to validation theory of alpha stable distribution. The result shows that network traffic arrival process can be accurately described alpha stable process.Thirdly, impact of self-similarity on network performance is discussed. If the input is self-similar traffic, the tail of mean queue length in buffer decreases as Weibullian distribution or hyperbolic function. This is different from result concluded from Poisson model. These properties induce large queuing delay and high packet loss rate. And the deterioration of performance becomes more evident when there is high self-similarity. If a larger buffer is used, packet loss rate will be lower to some extent. But queuing delay will increase dramatically. On contrary, if network bandwidth is enhanced, both the packet loss rate and queuing delay will decrease. Therefore, it’s vital to determine appropriate buffer when network is planned.At last, a new congestion control scheme is proposed based on prediction of network traffic. <WP=5>It takes advantage of long range dependence to predict traffic level in the future period. Then the sending rate is adjusted according to the prediction result. Thus network resource is fully utilized and congestion can be avoided to some extent. In this paper, traffic modeling based on linear fractional stable noise process is given and prediction algorithm is presented. This algorithm can be applied to the proposed control scheme to improve additive increase multiplicative decrease rate control. Simulation is conducted to analyze the performance of the proposed scheme. The simulation results show that this scheme can improve throughput and decrease packet loss rate. Finally, the practicability of this scheme is analyzed.更多还原