Fast classification and estimation of internet traffic flows

Authors:
Sumantra R. Kundu;Sourav Pal;Kalyan Basu;Sajal K. Das
Affiliations:
Center for Research in Wireless, Mobility and Networking, The University of Texas at Arlington, TX;Center for Research in Wireless, Mobility and Networking, The University of Texas at Arlington, TX;Center for Research in Wireless, Mobility and Networking, The University of Texas at Arlington, TX;Center for Research in Wireless, Mobility and Networking, The University of Texas at Arlington, TX
Venue:
PAM'07 Proceedings of the 8th international conference on Passive and active network measurement
Year:
2007

Citing 13
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Abstract

This paper makes two contributions: (i) it presents a scheme for classifying and identifying Internet traffic flows which carry a large number of packets (or bytes) and are persistent in nature (also known as the elephants), from flows which carry a small number of packets (or bytes) and die out fast (commonly referred to as the mice), and (ii) illustrates how non-parametric Parzen window technique can be used to construct the probability density function (pdf) of the elephants present in the original traffic stream. We validate our approach using a 15-minute trace containing around 23 million packets from NLANR.