Abstract
To reduce the number of packets used in categorizing flows, we propose a new traffic classification method by investigating the relationships between flows instead of considering them individually. Based on the flow identities, we introduce seven types of relationships for a flow and a further Expanding Vector (EV) by searching relevant flows in a particular time window. The proposed Traffic Classification method based on Expanding Vector (TCEV) does not require an inspection of the detailed flow properties, and thus, it can be conducted with a linear complexity of the flow number. The experiments performed on real-world traffic data verify that our method (1) attains as high a performance as the representative methods, while significantly reducing the number of processed packets; (2) is robust against packet loss and the absence of flow direction; and (3) is capable of reaching higher accuracy in the recognition of TCP mice flows.
| Original language | English |
|---|---|
| Pages (from-to) | 178-192 |
| Number of pages | 15 |
| Journal | Computer Networks |
| Volume | 129 |
| DOIs | |
| State | Published - 24 Dec 2017 |
Keywords
- Flow relationship
- Mice flow
- Packet loss
- Traffic classification