Network flow characteristic analysis method based on fractional order Fourier transformation

A fractional-order Fourier transform and network traffic technology, applied in data exchange networks, digital transmission systems, electrical components, etc., can solve problems such as high algorithm complexity and inability to meet the real-time analysis of network traffic characteristics, and achieve time complexity Low, strong robustness, effect of increasing robustness
CN104767656AInactive Publication Date: 2015-07-08CHINA ELECTRIC POWER RES INST +3
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
CHINA ELECTRIC POWER RES INST
Publication Date
2015-07-08
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention provides a network flow characteristic analysis method based on fractional order Fourier transformation. The method includes the steps that firstly, network flow data are extracted; secondly, a network flow characteristic analysis algorithm is adopted, and the Hurst index is obtained based on the network flow data; thirdly, the current network state is analyzed based on network flow feature parameters, and the Hurst index is corrected. The network flow characteristic analysis method based on the fractional order Fourier transformation has the advantages of the time domain estimation method and the frequency domain estimation method, the algorithm time complexity is low, the influences caused by the time scale are small, and robustness is high.
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Description

technical field

[0001] The invention relates to a method for analyzing network traffic characteristics, in particular to a method for analyzing network traffic characteristics based on fractional Fourier transform. Background technique

[0002] With the rapid development of Internet services carried in the communication network, the network traffic behavior is becoming more and more complex, and the demand for different types of network services is increasing, which puts forward higher requirements for the efficiency and security of network data transmission. Predicting the changing trend of data traffic in advance, rationally allocating limited network resources, and optimizing network expansion in a planned way are crucial to solving network congestion and providing better user services.

[0003] Predicting the trend of network data traffic changes requires integrated analysis based on existing data in order to make predictions under the guidance of certain theories. Then...

Claims

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