P2P Traffic Classification Algorithm based on Hierarchical Aggregation
| Autor: | LEE, CHUN-YI, 李俊儀 |
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| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 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. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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