Estimating flow distributions from sampled flow statistics Academic Article

abstract

• 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. 2005 IEEE.

authors

• Duffield, Nick

published proceedings

• IEEE-ACM TRANSACTIONS ON NETWORKING

author list (cited authors)

• Duffield, N., Lund, C., & Thorup, M.

citation count

• 142

complete list of authors

• Duffield, N||Lund, C||Thorup, M

publication date

• October 2005

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE/ACM Transactions on Networking  Journal

keywords

• Ip Flows
• Maximum Likelihood Estimation
• Measurement
• Measurement Errors
• Packet Sampling
• Sampling Methods

Digital Object Identifier (DOI)

• 10.1109/TNET.2005.852874

start page

• 933

end page

• 946

volume

• 13

issue

• 5

URL

• http://dx.doi.org/10.1109/tnet.2005.852874