Packet out-of-order and retransmission in statistics-based traffic analysis

Su-Kang Lee, Hyun-Min Ahn, Myung-Sup Kim
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引用次数: 1

Abstract

With the rapid growth of the Internet, the importance of application traffic analysis increases for efficient network management. The statistical information in traffic flows, can be efficiently utilized for application traffic identification. However, the packet out-of-order and retransmission generated at the traffic collection point reduce the performance of the statistics-based traffic analysis. In this paper, we propose a novel method to detect and resolve the packet out-of-order and retransmission problem in order to improve completeness and accuracy of the traffic identification. To prove the feasibility of the proposed method, we applied our method to a real traffic analysis system using statistical flow information, and compared the performance of the system with the selected 9 popular applications. The experiment showed maximum 4.9% of completeness growth in traffic bytes, which shows that the proposed method contributes to the analysis of heavy flow.
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基于统计的流量分析中的丢包和重传
随着Internet的快速发展,应用流量分析对于高效的网络管理越来越重要。利用交通流中的统计信息,可以有效地进行应用流量识别。但是,在流量采集点产生的数据包乱序和重传会降低基于统计的流量分析的性能。为了提高流量识别的完整性和准确性,本文提出了一种新的检测和解决数据包乱序和重传问题的方法。为了证明该方法的可行性,我们将该方法应用于一个真实的统计流量信息的交通分析系统,并将该系统的性能与选定的9个流行应用进行了比较。实验结果表明,流量字节的完备性增长最大可达4.9%,表明该方法对大流量分析有一定的贡献。
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