Emerging P2P Traffic Analysis and Modeling 


Vol. 29,  No. 2, pp. 279-288, Feb.  2004


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  Abstract

Rapidly emerging P2P(Peer to Peer) applications generate very bursty traffic, which gives a lot of burden to network, and the amount of such traffic is increasing rapidly. Thus it is becoming more important to understand the characteristics of such traffic and reflect it when we design and analyze the network. To do that we measured the traffic in a campus network and present flow statistics and traffic models of the measured traffic, and compare them with those of the web traffic. The results indicate that P2P traffic is much burstier than web traffic and as a result it negatively affects network performance. We modeled P2P traffic using self-similar traffic model to predict packet delay and loss occurred in network which are very important to evaluate network performance. We also predict queue length distribution and loss probability in SSQ(Single Server Queue). To assess accuracy of traffic model., we compare the SSQ statistics of traffic models with that of the traffic trace. The results show that self-similar traffic models we use can predict P2P traffic behavior in network precisely. It is expected that the traffic models we derived can be used when we design network capacity and predict network performance and QoS of the P2P applications.

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  Cite this article

[IEEE Style]

S. Joo and C. Lee, "Emerging P2P Traffic Analysis and Modeling," The Journal of Korean Institute of Communications and Information Sciences, vol. 29, no. 2, pp. 279-288, 2004. DOI: .

[ACM Style]

Sung-don Joo and Chae-Woo Lee. 2004. Emerging P2P Traffic Analysis and Modeling. The Journal of Korean Institute of Communications and Information Sciences, 29, 2, (2004), 279-288. DOI: .

[KICS Style]

Sung-don Joo and Chae-Woo Lee, "Emerging P2P Traffic Analysis and Modeling," The Journal of Korean Institute of Communications and Information Sciences, vol. 29, no. 2, pp. 279-288, 2. 2004.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880