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Estimating flow distributions from sampled flow statistics

delete2005-10-01
delete106
PRE
AI
N
Nick Duffield
C
Carsten Lund
M
Mikkel Thorup
DOI：10.1109/TNET.2005.852874delete
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Abstract

Abstract

En 中文
Passive traffic measurement increasingly employs sampling at the packet level. Many high-end routers form flow statistics from a sampled substream of packets. Sampling controls the consumption of resources by the measurement operations. However, knowledge of the statistics of flows in the unsampled stream remains useful, for understanding both characteristics of source traffic, and consumption of resources in the network. This paper provides methods that use flow statistics formed from sampled packet stream to infer the frequencies of the number of packets per flow in the unsampled stream. A key task is to infer the properties of flows of original traffic that evaded sampling altogether. We achieve this through statistical inference, and by exploiting protocol level detail reported in flow records. We investigate the impact on our results of different versions of packet sampling.
Keywords:
IP flows
maximum likelihood estimation
measurement
measurement errors
packet sampling
sampling methods
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Journal

I
IEEE-ACM Transactions on Networking
IF:
3.6
Papers:
4.4K
Citations:
9.5K

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