Name
Abstract | ||
|---|---|---|
The main purpose of this paper is twofold. First, we propose a novel identification method to reveal P2P traffic from traffic aggregation. Our method is based on a set of heuristics derived from the robust properties of P2P traffic. We show the high accuracy of the proposed algorithm based on a validation study. Second, several results of a comprehensive traffic analysis, focusing on the differences between P2P and non-P2P traffic, are reported in the paper. Our results show that the unique properties of P2P application traffic seem to fade away during aggregation and characteristics of the traffic will be similar to that of other non-P2P traffic aggregation. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11753810_51 | Networking |
Keywords | Field | DocType |
p2p traffic,comprehensive traffic analysis,p2p application traffic,non-p2p traffic,main purpose,traffic aggregation,non-p2p traffic aggregation,proposed algorithm,novel identification method,p2p traffic aggregation,high accuracy,p2p | Traffic generation model,Traffic analysis,Peer-to-peer,Computer science,Heuristics,Distributed computing | Conference |
Volume | ISSN | ISBN |
3976 | 0302-9743 | 3-540-34192-7 |
Citations | PageRank | References |
9 | 0.79 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Trang Dinh Dang | 1 | 70 | 6.70 |
| Marcell Perényi | 2 | 68 | 4.53 |
| András Gefferth | 3 | 42 | 2.56 |
| Sándor Molnár | 4 | 306 | 38.56 |