An effective similarity metric for application traffic classification

—Application level traffic classification is one of the major issues in network monitoring and traffic engineering. In our previous study, we proposed a new traffic classification method that utilizes a flow similarity function based on Cosine Similarity. This paper compares the classification accuracy of three similarity metrics, Jaccard Similarity, Cosine Similarity, and Gaussian Radius Based Function, to select appropriate similarity metrics for application traffic classification. This paper also defines a new two-stage traffic classification algorithm that can guarantee high classification accuracy even under an asymmetric routing environment, with reasonable complexity. Keywords—Application level traffic classification, traffic monitoring, similarity function

• Type: Journal
• Year: 2010
• Where: NOMS
• Authors: Jae Yoon Chung, Byungchul Park, Young J. Won, John Strassner, James W. Hong
• Keywords: Communications, Cosine Similarity, Level Traffic Classification, NOMS 2010, Traffic Classification