2007Dianzi Ke-ji Daxue xuebaoRequires access

Research on Dynamic Network Flow Classification

Ying Wang

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Abstract

Dividing the aggregate network volume into connections between host-pairs, we get a connection-oriented model in micro perspective—the dynamic network flow model. Analysis on a great amount of traffic shows that there is no one-to-one relationship between single flows and application protocols, but the single flow is able to reflect the characteristics of user network behaviors. By studying the data transportation features, a classification scheme of the single flow is provided from the perspective of the volume, frequency, and mode of the data interaction of network flows. Moreover, this classification scheme is tested in experimental network environment. And the experimental results show that the method proposed in this paper can capture the users' behavior exactly.

About this research paper

What this paper is about

Dividing the aggregate network volume into connections between host-pairs, we get a connection-oriented model in micro perspective—the dynamic network flow model. Analysis on a great amount of traffic shows that there is no one-to-one relationship between single flows and application protocols, but the single flow is able to reflect the characteristics of user network behaviors. By studying the data transportation features, a classification scheme of the single flow is provided from the perspective of the volume, frequency, and mode of the data interaction of network flows. Moreover, this classification scheme is tested in experimental network environment. And the experimental results show that the method proposed in this paper can capture the users' behavior exactly.

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Available abstract

Dividing the aggregate network volume into connections between host-pairs, we get a connection-oriented model in micro perspective—the dynamic network flow model. Analysis on a great amount of traffic shows that there is no one-to-one relationship between single flows and application protocols, but the single flow is able to reflect the characteristics of user network behaviors. By studying the data transportation features, a classification scheme of the single flow is provided from the perspective of the volume, frequency, and mode of the data interaction of network flows. Moreover, this classification scheme is tested in experimental network environment. And the experimental results show that the method proposed in this paper can capture the users' behavior exactly.

Key concepts: Computer science, Aggregate (composite), Flow (mathematics), Flow network, Perspective (graphical), Scheme (mathematics), Volume (thermodynamics), Dynamic network analysis

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