A novel algorithm for estimating flow length distributions-LSM

Authors:
Weijiang Liu
Affiliations:
School of Computer Science and Technology, Dalian Maritime University, Dalian, Liaoning, China
Venue:
NPC'07 Proceedings of the 2007 IFIP international conference on Network and parallel computing
Year:
2007

Citing 6
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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.