复杂网络演化模型及网络流量自相似分析-计算机软件与理论专业论文.docxVIP

I I 复杂网络演化模型及网络流量自相似研究 摘 要 近年来，随着人们对复杂网络的进一步研究，发现在现实世界中，越来越 多的系统可以用复杂网络描述，如社会网络中的科研合作网，技术网络中的电 力网，Internet，万维网等。如何合理地概括抽象这些复杂网络，使其真实的再 现实际网络的演化过程，逐渐成为复杂网络研究的核心问题。同时，在复杂网 络的应用研究中，把复杂网络的理论知识与其它领域的知识相结合成为一种发 展趋势。本文利用网络流量的自相似特性，将复杂网络中节点度的概念与网络 流量方面相结合，建立流量模型来预测网络实际流量。 本文主要工作如下： (1) 在加权无标度网络模型(BBV)的基础上，研究并提出了一个针对有向网 络的点权有限加权复杂网络模型，通过理论分析和仿真实验模拟，发现在该模 型中，节点的出入度和出入强度均服从幂律分布。 (2) 对某高校校园网的流量网络进行分析，得出 其度分布服从幂律分布且 幂律指数在 2 到 3 之间，说明校园网的流量网络近似符合上述提出的模型。 (3) 利用离散小波变换对校园网核心节点的出入 日均流量数据进行处理， 并运用阻尼二乘法对自回归滑动平均模型（ARMA）的参数进行估计，提出了 一个校园网流量预测模型。在此基础上，再结合复杂网络重要节点的概念，对 网络流量自相似的安全事件定位进行了研究。 关键字：BBV 网络；点权有限有向复杂网络；网络流量；自相似；ARMA 模型 II II Research of Complex Network Evolving Model and Self-similar Network Traffic ABSTRACT In recent years, with further study of complex networks, it was found that more and more real world systems，such as research cooperation networks of social network, the power grid of technology networks, Internet and World Wide Web, can be described by complex network. However, how to properly summarize and abstract these complex networks to reconstruct the evolution of the real networks has gradually become the key of researching complex network. Meanwhile, in the application of complex network research, it has been a trend that the theoretical knowledge of complex networks combines with the knowledge in other fields. Motivated by this, we construct the network traffic model to predict the actual traffic data, by the self-similarity of network traffic. The main work of this thesis is as follows: Based on the BBV scale-free model, the Directed Model for Weighted Networks Based on Limited Node Strength is introduced. Our experiment shows that the value of out-strength and in-strength distribution and in-degree and out-degree of nodes obey distribution of the exponent of power-law. Through analyzing the traffic of a campus network, we found the exponent of power-law can be adjusted between 2 to 3. Therefore, the presented model can be applied in the campus network traffi