SDN stream clustering method based on gaussian mixture
A clustering method, mixed Gaussian technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of efficient and accurate classification of SDN flows without much progress
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[0021] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0022] Such as figure 1 As shown, the present embodiment provides a mixed Gaussian-based SDN flow clustering method, which specifically includes the following steps;
[0023] Step S1: Record the quintuple of the original SDN data, and use the KMeans clustering algorithm to complete the mapping relationship between the SND data flow and the user;
[0024] Step S2: Use the Gaussian mixture model GMM and the formula Estimate the probability density distribution of SDN data flow, where K is the number of Gaussian models, a i is the weight of the i-th Gaussian model, p i (x|θ i ) is the probability density function of the i-th Gaussian model, the p i (x|θ i ) mean is μ k , with variance σ k ; θ i =(μ i ,∑ i ), μ i ,∑ i Generate the parameters of the model for the data to be solved;
[0025] Step S3: using flow duration, number of data packets,...
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