Name
Abstract | ||
|---|---|---|
Routers have the ability to output statistics about packets and flows of packets that traverse them. Since however the generation of detailed traffic statistics does not scale well with link speed, increasingly passive traffic measurement employs sampling at the packet level. Packet sampling has become an attractive and scalable means to measure flow data on high-speed links. However, knowing the number and length of the original flows is necessary for some applications. This paper provides an algorithm that uses flow statistics formed from sampled packet stream to infer the absolute frequencies of lengths of flows in the unsampled stream. We achieve this through statistical inference and by exploiting heavy-tailed feather. We also investigate the impact on our results of different packet sampling rate. The experiment results show the inferred distributions are accurate in most cases. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11758549_19 | International Conference on Computational Science (4) |
Keywords | Field | DocType |
packet level,heavy-tailed feature,flow statistic,flow data,packet stream,packet sampling,unsampled stream,original flow,detailed traffic statistic,passive traffic measurement,flow length distribution,different packet,heavy tail,statistical inference | Expectation–maximization algorithm,Computer science,Sampling (signal processing),Network packet,Algorithm,Heavy-tailed distribution,Statistical inference,Sampling (statistics),Data flow diagram,Traverse | Conference |
Volume | ISSN | ISBN |
3994 | 0302-9743 | 3-540-34385-7 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weijiang Liu | 1 | 53 | 9.15 |
| Jian Gong | 2 | 36 | 12.67 |
| Wei Ding | 3 | 10 | 4.39 |
| Guang Cheng | 4 | 61 | 26.17 |