Improved EM method for internet traffic classification

Abstract

Network traffic classification algorithm based on the machine learning has attracted more and more attention. Because the traditional EM algorithm has the disadvantage that the algorithm has the sensitivity of initial value and converge to local optimal point easily. This paper proposed a new improved EM algorithm based on the q-DAEM. The improved algorithm applies the EM algorithm to generate a constrained matrix, then combine the constrained matrix with the q-DAEM algorithm to reduce the search range, so that a better Gaussian mixture model can be derived from this algorithm. The algorithm was applied to the Moore datasets for evaluation, the experimental results show that this improved algorithm which applied to network traffic classification can lead to a higher precision and overall accuracy.