Learning vector quantization in flow classification of IP switched networks
Mika Ilvesmäki, Marko Luoma, Raimo Kantola · 2002
We discuss the flow classification in IP switched networks. Previous work done with flow classification methods has concentrated on optimizing the IP switch performance. We examine the performance of several previously introduced flow classification methods and then we introduce the use of learning vector quantization (LVQ) in flow classification. The LVQ classifier has the ability to offer the user an intuitive traffic profile. The LVQ classifier is found to successfully classify traffic flows with feasible performance requirements while also providing the user with an unambiguous traffic profile.