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A Novel Algorithm for Estimating Flow Length Distributions-LSM.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Keqiu Li
Jesshope, Chris
Hai Jin
Gaudiot, Jean-Luc
Weijiang Liu
Source :
Network & Parallel Computing (9783540747833); 2007, p445-452, 8p
Publication Year :
2007

Abstract

Traffic sampling technology has been widely deployed in front of many high-speed network applications to alleviate the great pressure on packet capturing.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 a novel algorithm, Least Square Method(LSM), that uses flow statistics formed from sampled packet stream to infer the absolute frequencies of lengths of flows in the unsampled stream. The theoretical analysis shows that the computational complexity of this method is well under control, and the experiment results demonstrate the inferred distributions are as accurate as EM algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540747833
Database :
Complementary Index
Journal :
Network & Parallel Computing (9783540747833)
Publication Type :
Book
Accession number :
33174918
Full Text :
https://doi.org/10.1007/978-3-540-74784-0_45