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G. Szabo, D. Orincasy, S. Malomsoky, and I. Szabo, "On the Validation of Traffic Classification Algorithms", in Passive and Active Measurement Conference (PAM), Apr 2008.
On the Validation of Traffic Classification Algorithms
Authors: G. Szabo
D. Orincasy
S. Malomsoky
I. Szabo
Published: Passive and Active Measurement Conference (PAM), 2008
URL:http://www.springerlink.com/index/tu142x745t3t2688.pdf
Entry Dates: 2009-02-13
Abstract: Detailed knowledge of the traffic mixture is essential for network operators and administrators, as it is a key input for numerous network management activities. Traffic classification aims at identifying the traffic mixture in the network. Several different classification approaches can be found in the literature. However, the validation of these methods is weak and ad hoc, because neither a reliable and widely accepted validation technique nor reference packet traces with well-defined content are available. In this paper, a novel validation method is proposed for characterizing the accuracy and completeness of traffic classification algorithms. The main advantages of the new method are that it is based on realistic traffic mixtures, and it enables a highly automated and reliable validation of traffic classification. As a proof-of-concept, it is examined how a state-of-the-art traffic classification method performs for the most common application types.
Results:
  • datasets: 43 hours; 6 Gbytes; collected in a separated access netwok;
  • P2P:70%;Web:26%;VoIP:2%;Streaming:1%;Secure Channel:1%;
  • a method for validate classificaiton methods;
  • a deterministic and reliable solution: at the traffic generating terminal, packets are collected into flows and flows are marked with the identifier of the application that generated the packets of the flow;
  • realizing with a driver that can be easily installed on terminals;
  Last Modified: Wed Mar-27-2019 22:23:20 PDT
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