Network topology inference method and system based on convolutional neural network

A convolutional neural network and network topology technology, applied in the field of network topology inference method and system based on convolutional neural network, can solve the problem of low robustness, and achieve the effect of good robustness and high tolerance

Inactive Publication Date: 2019-08-16
CHINA UNIV OF GEOSCIENCES (WUHAN)
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Problems solved by technology

[0003] The technical problem to be solved by the present invention is to propose a three-way sub-topology inference method and system based on a convolutional neural network in view of the above-mentioned technical ...

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  • Network topology inference method and system based on convolutional neural network
  • Network topology inference method and system based on convolutional neural network
  • Network topology inference method and system based on convolutional neural network

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[0039] In order to make the purpose, technical solution and advantages of the present invention clearer, the embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0040] A network topology inference method and system based on a convolutional neural network, the main content of which is to infer three-way sub-topological structure information by using the CNN model, and then use this as the input to infer the topology structure.

[0041] Such as figure 1 As shown, a network topology inference method based on convolutional neural network, including:

[0042] S1. Collect three-way sub-topology data on the network to be inferred;

[0043] S2, building a CNN model;

[0044] S3, formatting the collected data to train the CNN model;

[0045] S4. Perform end-to-end measurement on the network to be inferred;

[0046] S5. Input the measured end-to-end data into the CNN model for three-way sub-topology inference;

[0047]...

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Abstract

The invention discloses a network topology inference method and system based on a convolutional neural network, and the method comprises the steps: judging three paths of sub-topology structures through the convolutional neural network, taking the information as an input, and inferring a network topology through employing a topology inference algorithm in the invention. The topology inference algorithm is the same as that of most traditional topology inference algorithms. According to the algorithm provided by the invention, the topology is constructed by determining the positions of the branch nodes and the nodes connected to the branch nodes; the difference is that three paths of sub-topological structure information are input into the algorithm, and compared with similar measurement type quantitative data input in a traditional method, the qualitative data is higher in error tolerance degree, and therefore better robustness is achieved.

Description

technical field [0001] The present invention relates to the field of network tomography, and more specifically, relates to a convolutional neural network-based network topology inference method and system. Background technique [0002] The external measurement technology based on router cooperation initiates the measurement process at the edge of the network, and obtains the parameters to be measured through the feedback of internal nodes to the detection data. Among them, the more common tools include ping for diagnosing network connectivity, traceroute for obtaining network topology, and pathchar for measuring performance parameters such as link bandwidth and delay. Such methods will fail when internal nodes do not support collaboration due to factors such as network security. In addition, most of these methods use ICMP (Internet Control Measurement Protocol) packets as detection data, but the priority of ICMP packets in actual networks is low, so the measured performance...

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Application Information

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IPC IPC(8): G06K9/62G06N3/04H04L12/24
CPCH04L41/145H04L41/12G06N3/044G06N3/045G06F18/214
Inventor 潘胜利曾德泽张宗旺
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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