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A Mixture-Gaussian-Based SDN Flow Clustering Method

A clustering method, mixed Gaussian technology, applied in special data processing applications, instruments, electrical digital data processing and other directions, can solve the problem of efficient and accurate classification of SDN streams without great progress, and achieves improved clustering effect, The effect of improved accuracy and clustering speed

Active Publication Date: 2017-07-04
FUZHOU UNIV
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Problems solved by technology

[0003] At present, in the software-defined network (SDN) environment, the research on the problem of efficient and accurate classification of SDN flows has not made much progress.

Method used

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  • A Mixture-Gaussian-Based SDN Flow Clustering Method
  • A Mixture-Gaussian-Based SDN Flow Clustering Method
  • A Mixture-Gaussian-Based SDN Flow Clustering Method

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Embodiment Construction

[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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Abstract

The invention relates to an SDN stream clustering method based on gaussian mixture. According to the method, a basic gaussian mixture model algorithm is improved, side information of streams is introduced, and a gaussian mixture model based on side information and constrained by an equivalent set is constructed, so that a clustering effect is improved, and the SDN stream clustering method is applied to SDN data stream clustering. By adopting the method, the accuracy of a clustering result is improved greatly and a clustering speed is increased greatly.

Description

technical field [0001] The invention relates to SDN data stream clustering, in particular to a mixed Gaussian-based SDN stream clustering method. Background technique [0002] Software Defined Network (Software Defined Network, SDN) is a new network innovation architecture of Emulex network, and it is a way to realize network virtualization. Its core technology, OpenFlow, separates the control plane and data plane of network equipment to realize Flexible control of network traffic, making the network more intelligent as a pipeline. [0003] At present, in the software-defined network (SDN) environment, the research on the problem of efficient and accurate classification of SDN flows has not made great progress. Contents of the invention [0004] In view of this, the purpose of the present invention is to propose a mixed Gaussian-based SDN flow clustering method, which greatly improves the accuracy and clustering speed of the clustering results. [0005] The present inven...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
CPCG06F16/285
Inventor 郑相涵陈锋情
Owner FUZHOU UNIV
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