Adaptive Flow Classification in IP Switching-The Measurement Based Approach

摘要

In this work, we first briefly introduce the concept of IP flow classification on a general conceptual level. The intentrion is to rise above the technological details and create a conceptual point of view on flow classification and closely related issues. Then we move on to study and compare earlier flow classificaiton methods such as the all and selected flow classifier and the packet count flow classifier. The comparison of these methods is done with actual networks traffic and various performance metrics are presented. It is found that while the traditional methods of flow classificaiton are found to reduce the resource usage of the network elements, they provide the user with an ambiguous traffic profile at the best. A measurement based learning approach to flow classification is then presented.