P2P Traffic Classification Algorithm based on Hierarchical Aggregation

碩士 === 逢甲大學 === 資訊工程學系 === 105 === As the rapid development of network technology in recent years, there are many unknown P2P traffics in the internet and these P2P traffics will seriously affect the network Quality of Service (QoS). However, it is difficult for the traditional traffic classific...

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Bibliographic Details
Main Authors: LEE, CHUN-YI, 李俊儀
Other Authors: LIU, TZONG-JYE
Format: Others
Language:zh-TW
Published: 2017
Online Access:http://ndltd.ncl.edu.tw/handle/19568381451944400957
Description
Summary:碩士 === 逢甲大學 === 資訊工程學系 === 105 === As the rapid development of network technology in recent years, there are many unknown P2P traffics in the internet and these P2P traffics will seriously affect the network Quality of Service (QoS). However, it is difficult for the traditional traffic classification technology to classify these unknown P2P traffics. In order to maintain the quality of network services, classifying these P2P traffics correctly is an important issue. In this thesis, we propose a P2P traffic classification algorithm based on hierarchical aggregation. The system aggregates flows with the same features and produce aggregated data flows. Then, the system calculates the characteristics of each aggregated data flow and merge these aggregated data flows by their overlapping relationship. Thus, the network traffic automatically converges to the corresponding clusters. The proposed method may accurately classify network traffics. Besides, it also solves the problem of the decision of the cluster number of the general clustering algorithm.