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首页> 外文期刊>Discrete dynamics in nature and society >Multilevel Bloom Filters for P2P Flows Identification Based on Cluster Analysis in Wireless Mesh Network
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Multilevel Bloom Filters for P2P Flows Identification Based on Cluster Analysis in Wireless Mesh Network

机译:无线网状网络中基于聚类分析的P2P流识别多级Bloom过滤器

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With the development of wireless mesh networks and distributed computing, lots of new P2P services have been deployed and enrich the Internet contents and applications. The rapid growth of P2P flows brings great pressure to the regular network operation. So the effective flow identification and management of P2P applications become increasingly urgent. In this paper, we build a multilevel bloom filters data structure to identify the P2P flows through researches on the locality characteristics of P2P flows. Different level structure stores different numbers of P2P flow rules. According to the characteristics values of the P2P flows, we adjust the parameters of the data structure of bloom filters. The searching steps of the scheme traverse from the first level to the last level. Compared with the traditional algorithms, our method solves the drawbacks of previous schemes. The simulation results demonstrate that our algorithm effectively enhances the performance of P2P flows identification. Then we deploy our flow identification algorithm in the traffic monitoring sensors which belong to the network traffic monitoring system at the export link in the campus network. In the real environment, the experiment results demonstrate that our algorithm has a fast speed and high accuracy to identify the P2P flows; therefore, it is suitable for actual deployment.
机译:随着无线网状网络和分布式计算的发展,已经部署了许多新的P2P服务,并丰富了Internet内容和应用程序。 P2P流量的快速增长给常规网络运营带来了巨大压力。因此,有效的P2P应用程序流识别和管理变得越来越紧迫。在本文中,我们通过研究P2P流的局部性特征,建立了一个多级Bloom过滤器数据结构来识别P2P流。不同级别的结构存储不同数量的P2P流规则。根据P2P流的特征值,我们调整Bloom过滤器数据结构的参数。该方案的搜索步骤从第一级到最后一级。与传统算法相比,我们的方法解决了以前方案的弊端。仿真结果表明,该算法有效提高了P2P流识别的性能。然后,我们将流量识别算法部署在校园网络出口链接中属于网络流量监控系统的流量监控传感器中。在实际环境中,实验结果表明我们的算法能够快速,准确地识别P2P流。因此,它适合实际部署。

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