Large traffic flows classification method

To Ensure QoE (quality of experience) to the users when they access so many Internet applications every day, ISPs are faced with challenge and opportunity in bandwidth management. They need some ways to identify each application´s flows generated by user hosts, especially the application classes with large flows because of the higher bandwidth occupation comparing with the other classes with small flows. A novel method is presented to modularize flow size using information gain ratio. The origin dataset is properly partitioned into large flow and small flow subsets by a threshold that is achieved when the data complexity of large flow subset is minimized. The searching algorithm of the partitioned threshold is independent of classification performance. The specific classifiers can be trained to identify large flows and small flows properly on each subset in generalization. Experimental results on real world traffic datasets show that byte accuracy increased 30% averagely when our method is compared with original.