电信科学 ›› 2012, Vol. 28 ›› Issue (10): 58-63.doi: 10.3969／j.issn.1000-0801.2012.10.010

• 云计算专栏 • 上一篇    下一篇

一个基于云计算的P2P流量识别系统模型的研究

徐雅斌,李艳平,刘曦子   

  1. 北京信息科技大学计算机学院 北京100101
  • 出版日期:2012-10-15 发布日期:2017-07-05
  • 基金资助:
    北京市教委面上科研项目;与数字传播北京市重点实验室资助项目

A Peer-to-Peer Traffic Classification System Model Based on Cloud Computing

Yabin Xu,Yanping Li,Xizi Liu   

  1. School of Computer,Beijing Information Science＆Technology University,Beijing 100101,China
  • Online:2012-10-15 Published:2017-07-05

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摘要：

首先分析了当前网络中P2P流量的占比情况和给网络带来的压力，指出了实际应用中网络流量识别技术存在的问题，给出了深度分组检测技术和流量特征识别技术的实现原理。在此基础上，提出了一种基于开源云计算平台Hadoop，采用MapReduce分布式并行计算架构，构建了将深度分组检测技术和流量特征识别技术相结合的P2P流量识别系统的设计模型。实验结果表明，本文提出的模型能够有效地识别P2P流量，并且在面对大流量时拥有比单机识别更快的识别速度。

关键词: 云计算, P2P流量识别, 深度分组检测, 流量特征识别, MapReduce

Abstract:

Current proportion of P2P traffic in the network and the pressure to the network are analyzed in the first, and the problems of network traffic identification technology in practical applications are pointed out. Then,the realization of the principle of deep packet inspection and flow characteristics recognition technology are presented. A P2P traffic identification system model, which combines the deep packet inspection technology and the flow characteristics recognition technology, based on the open source cloud computing platform Hadoop and MapReduce distributed parallel computing architecture, is put forward. The experimental results show that, this model can effectively identify P2P traffic, and possesses a recognition speed faster than the single identification in the face of large flow.

Key words: cloud computing, P2P traffic classification, DPI, TLI, MapReduce

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