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The distribution of network flow sizes is an important yet difficult metric to estimate in a network. It is important because it characterizes traffic compositions and is a crucial component of anomaly detection methods. It is difficult to estimate because of its high memory and computational requirements. In this talk we report on two different methods for estimating the flow size distribution. The first part of the talk focuses on flow size estimation based on packet sampling (e.g., NetFlow). Our discussion of this method emphasizes the use of Fisher Information as the metric for evaluating the benefits of different types of information on flow size distribution estimation. For example, when we restrict ourselves to TCP flows, the Fisher Information tells us that simply counting the number of packets per flow does not produce an accurate estimate of the size distribution of such flows (contrary to earlier reported results), whereas the inclusion of information such as sequence numbers makes the estimation problem tractable. In the second half of the talk, we focus on flow size estimation based on an on-line data streaming approach. Our discussion of this approach focuses on the use of probabilistic counting and counter folding, both of which allow for a substantial reduction, over previous algorithms, in the amount of processing and the amount of memory needed to obtain accurate estimates of the flow size distribution. This work was performed jointly with Bruno Ribeiro and Tao Ye. Biography Don Towsley is a Professor at the University of Massachusetts in the Department of Computer Science. His research interests include networks and performance evaluation. He currently serves as Editor-in-Chief of IEEE/ACM Transactions on Networking, and on the editorial boards of Journal of the ACM and IEEE Journal on Selected Areas in Communications. He was Program Co-chair of the joint ACM SIGMETRICS and PERFORMANCE '92 conference and the Performance 2002 conference. Towsley has received the 2007 IEEE Koji Kobayashi Award, the 2007 ACM SIGMETRICS Achievement Award,the 2008 ACM SIGCOMM Lifetime Achievement Award, a 2008 SIGCOMM Test-of-Time Paper Award, the 1998 IEEE Communications Society William Bennett Best Paper Award, and numerous conference/workshop best paper awards. Last, he has been elected Fellow of both the ACM and IEEE.
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