Information transmission scheduling method and system based on intelligent traffic classification

A traffic classification and information transmission technology, which is applied in the information transmission scheduling method and system field based on intelligent traffic classification, can solve the problem of unrecognizable high-priority data types in the Internet of Things, difficulty in meeting user service quality requirements, and insufficient guarantee of network resource allocation and other issues, to achieve the effect of improving sample validity, network resource allocation guarantee, and training effect

Pending Publication Date: 2021-06-11
SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] In order to overcome the deficiencies of the prior art, the present invention provides an information transmission scheduling method and system based on intelligent traffic classification, which solves the existing problems in the prior art that are prone to local load imbalance, unrecognizable high-priority data types of the Internet of Things, and network resources Insufficient distribution guarantee, poor stability, difficulty in meeting different service quality requirements of users, etc.

Method used

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  • Information transmission scheduling method and system based on intelligent traffic classification
  • Information transmission scheduling method and system based on intelligent traffic classification
  • Information transmission scheduling method and system based on intelligent traffic classification

Examples

Experimental program
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Embodiment 1

[0064] Such as Figure 1 to Figure 3 As shown, an information transmission scheduling method based on intelligent traffic classification includes the following steps:

[0065] S1, prepare training data: make the network traffic data set into a traffic feature training set, which is used as the input of the neural network;

[0066] S2, build a neural network: use the classification network to establish a short connection between all the previous layers and the back layer, and build a neural network;

[0067] S3, train the neural network: use the traffic feature training set in step S1 as the input of the neural network, input it into the neural network for training, and obtain the traffic classification model;

[0068] S4, classify the traffic category: classify the traffic data to be processed according to the traffic classification model;

[0069] S5. Perform traffic transmission scheduling: divide the classified traffic data into specific priority levels according to the p...

Embodiment 2

[0097] Such as Figure 1 to Figure 3 As shown, on the basis of the embodiment, this embodiment provides a system of an information transmission scheduling method based on intelligent traffic classification, including the following modules:

[0098] The traffic classification module is used for traffic acquisition, feature extraction and traffic classification of the traffic data to be processed, and information interaction with the network traffic control module.

[0099] Network traffic control module: used for policy matching and traffic forwarding control on classified traffic, and information interaction with traffic classification module, data collection and distribution module;

[0100] Data collection and distribution module: used for two-level scheduling of traffic data. The first level uses weighted scheduling to schedule traffic data packets of different priorities according to the order of priority; the second level uses round-robin scheduling to According to the f...

Embodiment 3

[0106] Such as Figure 1 to Figure 3 As shown, as a further optimization of Embodiment 1 and Embodiment 2, this embodiment includes all the technical features of Embodiment 1 and Embodiment 2. In addition, this embodiment has further refinements and supplements.

[0107] An information transmission scheduling method based on intelligent traffic classification, comprising the following steps:

[0108] S1, prepare training data: make the network traffic data set into a traffic feature training set, which is used as the input of the neural network;

[0109] The data set used in the present invention is a classic Moore network traffic data set, which is the traffic data of Cambridge University collected by Moore et al., and is used in the field of network traffic identification and classification. The data of each flow in this dataset has 12 feature vectors and 1 manually labeled category label. According to the Internet communication standard document, a network flow is defined...

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Abstract

The invention discloses an information transmission scheduling method and system based on intelligent traffic classification. The method comprises the following steps: S1, preparing training data; s2, constructing a neural network; s3, training a neural network; s4, dividing traffic categories; and S5, carrying out traffic transmission scheduling. The method solves the problems that in the prior art, local load unbalance is likely to occur, the type of high-priority data of the Internet of Things cannot be recognized, network resource allocation is not guaranteed in place, stability is poor, and different service quality requirements of users are difficult to meet.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence Internet of things, in particular to an information transmission scheduling method and system based on intelligent traffic classification. Background technique [0002] According to different classification methods, network traffic classification methods can be divided into classification methods based on port matching, classification methods based on deep packet inspection, and classification methods based on machine learning. [0003] The classification method based on port matching is the earliest network traffic classification method, and it is also the simplest and most convenient classification method. It mainly extracts the port number from the obtained traffic data, and maps it to the corresponding application according to the port number classification, so as to achieve the classification effect. This classification method is very efficient, has low time complexity...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/04G06N3/084G06F18/214G06F18/24
Inventor 王洪鹏刘湘德刘刚于翔张瑞黄旭岑林睿李馥丹罗俊薛滔余康
Owner SOUTHWEST CHINA RES INST OF ELECTRONICS EQUIP
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