基于分形理论P2P流量行为的自相似性

Study on the Self-Similarity of P2P Traffic Behavior Based on Fractal Method

针对单个主机单个协议流量的自相似性和非宏观上流量的自相似性,分析了端到端(P2P)网络流量的自相似性.对常见的端到端(P2P)应用进行分析后发现,其应用层数据存在自相似性,且在时间尺度与行为尺度的比较中,P2P应用层流量在行为尺度上的自相似性表现得更加明显和稳定.为了将行为尺度上的自相似性应用到业务感知领域,提出了一种新的P2P流量识别算法,该算法通过计算网络流量不同行为尺度下的容量维,再辅以主动系数来识别P2P流量.实验结果证明,新算法在P2P流量识别方面的准确率高于同类算法,在加密流量的识别上表现尤为突出.

The self-similarity of peer-to-peer （ P2P） traffic is studied based on fractal method. Different from former researches,the traffic of single protocol is concerned. Two popular P2P applications are tested and showen that the application layer traffic tends to be self-similar. The self-similarity is more stable under behavior scale than under time scale. The self-similarity of the P2P traffic is applied to P2P traffic identification. A new traffic identification algorithm is proposed based on the fractal dimension and positivity of the network traffic. Experimentss show that the performance of the proposed algorithm is better than the existed in terms of accuracy especially for encrypted traffic.