A traffic processing method based on network data transmission

Abstract

This invention provides a traffic processing method based on network data transmission, comprising: acquiring traffic information to be transmitted and pre-processing the traffic information to be transmitted; performing anomaly detection on the pre-processed traffic information and optimizing the abnormal data to obtain traffic information to be allocated; extracting features from the traffic information to be allocated and classifying the features; analyzing the traffic transmission links to obtain the transmission type and traffic threshold of each traffic transmission link; and matching the traffic information to be transmitted to the corresponding transmission link based on the traffic transmission link analysis results and the feature classification of the traffic to be allocated. By detecting and optimizing the traffic to be transmitted and by allocating the traffic information to be allocated to the corresponding transmission link, the transmission efficiency of each traffic transmission link is improved. Starting from the traffic threshold of the transmission link, each transmission link is better utilized, thereby improving the quality and speed of network data transmission.

Description

Technical Field

[0001] This invention relates to the field of network data transmission technology, and in particular to a traffic processing method based on network data transmission. Background Technology

[0002] Currently, with the development of science and technology, the internet is becoming increasingly integrated into people's lives. Network data transmission plays a crucial role in this development. Network data transmission refers to the transmission of data using a series of lines (fiber optic cables, twisted-pair cables, etc.) through circuit adjustments and according to network transmission protocols. Network development is inseparable from network data transmission; it is network data transmission that connects networks and maximizes their functionality. In network data transmission, proper traffic handling can improve data transmission efficiency.

[0003] Therefore, the present invention provides a traffic processing method based on network data transmission. Summary of the Invention

[0004] This invention provides a traffic processing method based on network data transmission. It optimizes the abnormal data by pre-analyzing and detecting anomalies in the traffic to be transmitted. It also classifies the traffic information to be transmitted and the traffic transmission links to obtain the feature categories of the traffic information to be allocated and the transmission type of each traffic transmission link. It assigns the corresponding transmission links to the traffic information to be allocated, thereby improving the transmission efficiency of each traffic transmission link. Starting from the traffic threshold of the transmission link, it makes better use of each transmission link and improves the quality and speed of network data transmission.

[0005] This invention provides a traffic processing method based on network data transmission, comprising:

[0006] Step 1: Obtain the traffic information to be transmitted and perform filtering and preprocessing on the traffic information to be transmitted;

[0007] Step 2: Perform anomaly detection on the pre-processed traffic information and optimize the abnormal data to obtain the traffic information to be allocated;

[0008] Step 3: Extract features from the traffic information to be allocated and classify those features;

[0009] Step 4: Analyze the traffic transmission links to obtain the transmission type and traffic threshold for each traffic transmission link;

[0010] Step 5: Based on the traffic transmission link analysis results and the feature classification of the traffic to be allocated, match the corresponding transmission link to the traffic information to be transmitted and transmit it.

[0011] Preferably, the present invention provides a traffic processing method based on network data transmission, which acquires traffic information to be transmitted and performs filtering and preprocessing on the traffic information to be transmitted, including:

[0012] Obtain the traffic information to be transmitted and extract the header data of the traffic information to be transmitted;

[0013] Based on the source data information of the header data, the source database type of each header information is obtained;

[0014] Based on the transmission database type at the end of network data transmission, we obtain heterogeneous source database types that differ from the transmission database type in the source data type of each header information.

[0015] The data information corresponding to the different source database types is input into the database type format conversion model to obtain data information with the same format as the transmitted database type.

[0016] Preferably, the present invention provides a traffic processing method based on network data transmission, which performs anomaly detection on the pre-processed traffic information, including:

[0017] Obtain historical traffic information of successfully transmitted data and input it into the detection transmission link;

[0018] Based on the signal waveforms received by each detection node of the detection transmission link, a historical waveform change trend image is obtained when historical traffic information passes through the detection transmission link.

[0019] Based on the historical waveform change trend image, the key points of historical waveform attenuation are obtained;

[0020] The highest point of the segment in the historical waveform change trend image that is before the historical waveform decay key point is obtained as the first key point;

[0021] The lowest point of the segment in the trend of change after the historical waveform decay key point in the historical waveform change trend image is used as the second key point.

[0022] The filtered traffic information is input into the detection transmission link to obtain the transmission signal of the filtered traffic information when it passes through each detection node.

[0023] The transmitted signal is input into an oscilloscope to obtain the top pulse and bottom pulse of the transmitted signal;

[0024] The number of intersections between the top pulse and the signal waveform corresponding to the first key point obtained for each historical traffic information is obtained, and the signal waveform corresponding to the top pulse with the most intersections is obtained as the first signal waveform;

[0025] The number of intersections between the bottom pulse and the signal waveform corresponding to the second key point obtained from each historical traffic information is obtained, and the signal waveform corresponding to the bottom pulse with the most intersections is obtained as the second signal waveform;

[0026] The first signal waveform and the second signal waveform are integrated to obtain the transmission waveform attenuation point of the integrated waveform;

[0027] Calculate the signal strength difference between the transmission waveform attenuation point and the key attenuation point of the historical waveform;

[0028] If the numerical difference is greater than the preset difference, it is determined that there is abnormal data in the filtered and preprocessed traffic information.

[0029] Preferably, the present invention provides a traffic processing method based on network data transmission, which performs anomaly detection on the pre-processed traffic information and optimizes the abnormal data to obtain traffic information to be allocated, including:

[0030] The abnormal data is input into the abnormal data optimization model to obtain data that can be transmitted normally.

[0031] Based on the data that can be transmitted normally and the data that is free of abnormalities, the traffic information to be allocated is obtained.

[0032] Preferably, the present invention provides a traffic processing method based on network data transmission, which extracts features from the traffic information to be allocated and performs feature classification, including:

[0033] The traffic information to be allocated is broken down to obtain the traffic characteristic information corresponding to the traffic information to be allocated;

[0034] Based on the traffic characteristic information, corresponding feature keywords are obtained;

[0035] Input the feature keywords into the feature vector transformation model to obtain the feature vector corresponding to each feature keyword;

[0036] When there is only one feature vector corresponding to the traffic information to be allocated, the feature category of the traffic information to be allocated is the feature category corresponding to the feature vector;

[0037] When there is more than one feature vector corresponding to the traffic information to be allocated, calculate the feature distinguishability between each feature vector corresponding to the traffic information to be allocated and the preset feature vector;

[0038] The feature category of the feature vector corresponding to the feature with the highest feature discrimination value is used as the feature category of the traffic information to be assigned.

[0039] Preferably, the present invention provides a traffic processing method based on network data transmission, which calculates the feature distinguishability between each feature vector corresponding to the traffic information to be allocated and a preset feature vector, including:

[0040]

[0041] Where E represents the feature discrimination degree between each feature vector corresponding to the traffic information to be allocated and the preset feature vector; a i b represents the i-th value in the feature vector corresponding to the traffic information to be allocated; i represents the i-th value in the preset feature vector; max represents the sign of the maximum value; log2 represents the logarithmic function with base 2; ∝ i The value type of the i-th value is indicated; n represents the number of values ​​in the corresponding feature vector.

[0042] Preferably, the present invention provides a traffic processing method based on network data transmission, which analyzes traffic transmission links to obtain the transmission type of each traffic transmission link, including:

[0043] Obtain and analyze the node information at the first node of the traffic transmission link to obtain the encrypted link information;

[0044] Based on the external information of the encrypted link information, the corresponding link key is matched;

[0045] Based on the encrypted link information and the link key, the link information of the traffic transmission link is obtained;

[0046] Based on the link information, the transmission type corresponding to each traffic transmission link is obtained.

[0047] Preferably, the present invention provides a traffic processing method based on network data transmission, which analyzes traffic transmission links to obtain the transmission type and traffic threshold of each traffic transmission link, including:

[0048] Based on the link information, the historical transmission logs of the traffic transmission link are obtained;

[0049] Based on the historical transmission logs, obtain the historical traffic transmission volume and historical transmission time;

[0050] A historical transmission efficiency graph is constructed using historical traffic volume as the vertical axis and historical transmission time as the horizontal axis.

[0051] Based on the historical transmission efficiency map, the value of the horizontal axis corresponding to the highest point is selected as the traffic threshold of the traffic transmission link.

[0052] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0053] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0054] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0055] Figure 1 This is a flowchart of a traffic processing method based on network data transmission in an embodiment of the present invention. Detailed Implementation

[0056] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0057] Example 1:

[0058] This invention provides a traffic processing method based on network data transmission, such as... Figure 1 Shown, including:

[0059] Step 1: Obtain the traffic information to be transmitted and perform filtering and preprocessing on the traffic information to be transmitted;

[0060] Step 2: Perform anomaly detection on the pre-processed traffic information and optimize the abnormal data to obtain the traffic information to be allocated;

[0061] Step 3: Extract features from the traffic information to be allocated and classify those features;

[0062] Step 4: Analyze the traffic transmission links to obtain the transmission type and traffic threshold for each traffic transmission link;

[0063] Step 5: Based on the traffic transmission link analysis results and the feature classification of the traffic to be allocated, match the corresponding transmission link to the traffic information to be transmitted and transmit it.

[0064] In this embodiment, the filtering preprocessing refers to filtering the traffic information to be transmitted that needs to be transmitted over the network, filtering out data information whose database type is different from the transmission database type at the end of the transmission, and converting the data format to facilitate transmission.

[0065] In this embodiment, anomaly detection refers to detecting anomalies in the pre-processed traffic information. This involves identifying and optimizing data with anomalies by detecting signal waveform anomalies in the transmission process of each data point. Anomalies include missing anomalies and error anomalies.

[0066] In this embodiment, the traffic information to be allocated refers to the abnormal information that has been optimized to become normally transmittable information and information consisting of no abnormal data, waiting to be identified and the corresponding type of transmission link allocated.

[0067] In this embodiment, feature extraction refers to obtaining feature keywords by analyzing the feature information in the traffic information to be allocated, and converting them into feature vectors through a feature vector transformation model. The feature types of each traffic information to be allocated are obtained based on the number of feature vectors and the analysis of their discriminative power.

[0068] In this embodiment, feature classification refers to classifying the traffic information to be allocated into different categories based on the functional attributes and data attribute classification standards, thereby achieving the purpose of facilitating the transmission of traffic information to be allocated by matching the corresponding attributes of the transmission link.

[0069] In this embodiment, the traffic transmission link refers to the link used to transmit traffic information.

[0070] In this embodiment, the transmission type refers to the different types of traffic transmission links classified according to the functional attributes and data attribute classification standards of the traffic transmission link, so as to achieve the purpose of allocating the corresponding traffic information to be allocated.

[0071] In this embodiment, the traffic threshold refers to the value of the maximum amount of traffic information that each traffic transmission link can transmit while ensuring the highest transmission efficiency.

[0072] The beneficial effects of the above technical solution are: by pre-analyzing and detecting anomalies in the traffic to be transmitted, abnormal data is obtained for optimization; by classifying the traffic information to be transmitted and the traffic transmission links, the characteristic categories of the traffic information to be allocated and the transmission type of each traffic transmission link are obtained; the traffic information to be allocated is assigned to the corresponding transmission link for transmission, thereby improving the transmission efficiency of each traffic transmission link; and by making better use of each transmission link based on the traffic threshold of the transmission link, the quality and speed of network data transmission are improved.

[0073] Example 2:

[0074] This invention provides a traffic processing method based on network data transmission, which acquires traffic information to be transmitted and performs filtering and preprocessing on the traffic information to be transmitted, including:

[0075] Obtain the traffic information to be transmitted and extract the header data of the information to be transmitted;

[0076] Based on the source data information of the header data, the source database type of each header information is obtained;

[0077] Based on the transmission database type at the end of network data transmission, we obtain heterogeneous source database types that differ from the transmission database type in the source data type of each header information.

[0078] The data information corresponding to the different source database types is input into the database type format conversion model to obtain data information with the same format as the transmitted database type.

[0079] In this embodiment, header data refers to the information containing attribute information in the header of the traffic information to be transmitted. The attribute information includes the source data information of the traffic information to be transmitted, as well as the length and amount of information of the traffic information to be transmitted.

[0080] In this embodiment, the source data information refers to the source data information of the traffic information to be transmitted, which includes the source database information of the traffic information to be transmitted, thereby achieving the purpose of obtaining the information format of the traffic information to be transmitted.

[0081] In this embodiment, the source database type refers to the database type of the source data information of the traffic information to be transmitted, thereby achieving the purpose of obtaining the information format of the traffic information to be transmitted.

[0082] In this embodiment, the transmission database type refers to the database type of the data received at the end of the network data transmission, thereby achieving the purpose of obtaining a standard information format.

[0083] In this embodiment, heterogeneous source database type refers to a source database type whose source database type corresponding to the traffic information to be transmitted is different from the transmission database type through database type comparison.

[0084] In this embodiment, the database type format conversion model refers to a model trained from data of different database types that can convert data information corresponding to different source database types into data information in the same format as the transmitted database type, thereby facilitating data reception.

[0085] The beneficial effects of the above technical solution are: by analyzing the source data information of the traffic information to be transmitted, the source database type is obtained and the data information format that is different from the transmission database type is converted into the data format of the transmission database type, which facilitates data reception and improves the transmission efficiency of the transmission link.

[0086] Example 3:

[0087] This invention provides a traffic processing method based on network data transmission, which performs anomaly detection on pre-processed traffic information, including:

[0088] Obtain historical traffic information of successfully transmitted data and input it into the detection transmission link;

[0089] Based on the signal waveforms received by each detection node of the detection transmission link, a historical waveform change trend image is obtained when historical traffic information passes through the detection transmission link.

[0090] Based on the historical waveform change trend image, the key points of historical waveform attenuation are obtained;

[0091] The highest point of the segment in the historical waveform change trend image that is before the historical waveform decay key point is obtained as the first key point;

[0092] The lowest point of the segment in the trend of change after the historical waveform decay key point in the historical waveform change trend image is used as the second key point.

[0093] The filtered traffic information is input into the detection transmission link to obtain the transmission signal of the filtered traffic information when it passes through each detection node.

[0094] The transmitted signal is input into an oscilloscope to obtain the top pulse and bottom pulse of the transmitted signal;

[0095] The number of intersections between the top pulse and the signal waveform corresponding to the first key point obtained for each historical traffic information is obtained, and the signal waveform corresponding to the top pulse with the most intersections is obtained as the first signal waveform;

[0096] The number of intersections between the bottom pulse and the signal waveform corresponding to the second key point obtained from each historical traffic information is obtained, and the signal waveform corresponding to the bottom pulse with the most intersections is obtained as the second signal waveform;

[0097] The first signal waveform and the second signal waveform are integrated to obtain the transmission waveform attenuation point of the integrated waveform;

[0098] Calculate the signal strength difference between the transmission waveform attenuation point and the key attenuation point of the historical waveform;

[0099] If the numerical difference is greater than the preset difference, it is determined that there is abnormal data in the filtered and preprocessed traffic information.

[0100] In this embodiment, historical traffic information refers to traffic information from successful, non-abnormal transmissions in the past.

[0101] In this embodiment, the detection transmission link refers to a transmission link specifically built for detecting traffic information signals, with each attribute parameter being a standard that equally conforms to the transmission of any type of traffic information.

[0102] In this embodiment, the detection node refers to the node connected in the detection transmission link.

[0103] In this embodiment, the historical waveform change trend image refers to the waveform of the signal strength received by each detection node in the detection transmission link after the historical traffic information is input into the detection transmission link, and the change trend of the waveform in chronological order.

[0104] In this embodiment, the key point of historical waveform attenuation refers to the point in the historical waveform change trend image where the waveform attenuation amplitude is the largest.

[0105] In this embodiment, the first key point refers to the highest point in the trend of change before the key point of historical waveform attenuation, which represents the point where the signal is strongest.

[0106] In this embodiment, the second key point refers to the lowest point in the trend of change after the historical waveform attenuation key point, which represents the point where the signal is at its lowest.

[0107] In this embodiment, the top pulse refers to the electrical signal that has a brief, pulse-like fluctuation at the top of the transmitted signal waveform.

[0108] In this embodiment, the bottom pulse refers to the brief, pulsating electrical signal at the bottom of the transmitted signal waveform, resembling a pulse.

[0109] In this embodiment, the first signal waveform refers to the signal waveform corresponding to the top pulse that intersects the signal waveform corresponding to the first key point obtained by each historical traffic information the most times.

[0110] In this embodiment, the second signal waveform refers to the signal waveform corresponding to the bottom pulse that intersects the signal waveform corresponding to the second key point obtained from each historical traffic information the most times.

[0111] In this embodiment, waveform integration refers to averaging the signal strength values ​​corresponding to each moment of the first and second signal waveforms, and then using the average values ​​at each moment to form a new waveform image, thereby achieving the purpose of comprehensive analysis of the first and second signal waveforms.

[0112] In this embodiment, the transmission waveform attenuation point refers to the point in the integrated waveform after the first signal waveform and the second signal waveform are integrated, where the waveform attenuation amplitude is the largest.

[0113] In this embodiment, the preset difference refers to a pre-set value, indicating that when the difference in signal strength values ​​corresponding to the transmission waveform attenuation point and the historical waveform attenuation key point is greater than the preset difference, abnormal data exists in the pre-processed traffic information, thereby achieving the purpose of filtering abnormal data.

[0114] The beneficial effects of the above technical solution are as follows: by inputting historical traffic information into the detection transmission link to obtain and analyze the waveform of the detection node, the waveforms at the most representative historical waveform attenuation key points, the first key point, and the second key point are obtained. Furthermore, by inputting the filtered traffic information into the detection transmission link for analysis, the top pulse and bottom pulse are obtained. The waveforms at the first and second key points are comprehensively analyzed to obtain a representative integrated waveform. The waveforms at the historical waveform attenuation key points are analyzed to obtain abnormal data. By identifying and optimizing the abnormal data, the transmission efficiency of the transmission link is improved.

[0115] Example 4:

[0116] This invention provides a traffic processing method based on network data transmission, which performs anomaly detection on pre-processed traffic information and optimizes the abnormal data to obtain traffic information to be allocated, including:

[0117] The abnormal data is input into the abnormal data optimization model to obtain data that can be transmitted normally.

[0118] Based on the data that can be transmitted normally and the data that is free of abnormalities, the traffic information to be allocated is obtained.

[0119] In this embodiment, the abnormal data optimization model refers to a model that is trained using abnormal data and the causes of abnormality, and can be optimized according to the causes of abnormality in the abnormal data to obtain a model that can transmit data normally.

[0120] The beneficial effects of the above technical solution are: by optimizing abnormal data, the quality of transmitted data is improved, and the efficiency of network data transmission is increased.

[0121] Example 5:

[0122] This invention provides a traffic processing method based on network data transmission, which extracts features from traffic information to be allocated and performs feature classification, including:

[0123] The traffic information to be allocated is broken down to obtain the traffic characteristic information corresponding to the traffic information to be allocated;

[0124] Based on the traffic characteristic information, corresponding feature keywords are obtained;

[0125] Input the feature keywords into the feature vector transformation model to obtain the feature vector corresponding to each feature keyword;

[0126] When there is only one feature vector corresponding to the traffic information to be allocated, the feature category of the traffic information to be allocated is the feature category corresponding to the feature vector;

[0127] When there is more than one feature vector corresponding to the traffic information to be allocated, calculate the feature distinguishability between each feature vector corresponding to the traffic information to be allocated and the preset feature vector;

[0128] The feature category of the feature vector corresponding to the feature with the highest feature discrimination value is used as the feature category of the traffic information to be assigned.

[0129] In this embodiment, traffic characteristic information refers to the information representing attribute characteristics in the traffic information to be allocated, which can represent the attributes of the traffic to be allocated.

[0130] In this embodiment, the feature vector transformation model refers to a model trained from feature keywords and corresponding feature vectors that can transform feature keywords into feature vectors.

[0131] In this embodiment, the feature category refers to the different types of traffic information to be allocated, which are classified according to the functional attributes and data attributes of the traffic information to be allocated. These include: functional category and data type.

[0132] In this embodiment, feature discrimination refers to the degree to which the feature keywords corresponding to the feature vector to be allocated represent the representativeness of the traffic information to be allocated, based on the discriminability between the feature vector corresponding to the traffic information to be allocated and the preset feature vector.

[0133] The beneficial effects of the above technical solution are: by extracting feature information from the traffic information to be allocated, the feature vector corresponding to each traffic information to be allocated is obtained, and the feature category of the traffic information to be allocated is obtained, thereby improving the efficiency of network data transmission.

[0134] Example 6:

[0135] This invention provides a traffic processing method based on network data transmission, which calculates the feature discriminant degree between each feature vector corresponding to the traffic information to be allocated and a preset feature vector, including:

[0136]

[0137] Where E represents the feature discrimination degree between each feature vector corresponding to the traffic information to be allocated and the preset feature vector; a i b represents the i-th value in the feature vector corresponding to the traffic information to be allocated; irepresents the i-th value in the preset feature vector; max represents the sign of the maximum value; log2 represents the logarithmic function with base 2; ∝ i The value type of the i-th value is indicated; n represents the number of values ​​in the corresponding feature vector.

[0138] The beneficial effects of the above technical solution are: by calculating the feature distinguishability between each feature vector corresponding to the traffic information to be allocated and the preset feature vector, the feature keywords that best represent the traffic information to be allocated are obtained, thereby achieving the purpose of classifying the traffic information to be allocated and improving the efficiency of network data transmission.

[0139] Example 7:

[0140] This invention provides a traffic processing method based on network data transmission, which analyzes traffic transmission links to obtain the transmission type of each traffic transmission link, including:

[0141] Obtain and analyze the node information at the first node of the traffic transmission link to obtain the encrypted link information;

[0142] Based on the external information of the encrypted link information, the corresponding link key is matched;

[0143] Based on the encrypted link information and the link key, the link information of the traffic transmission link is obtained;

[0144] Based on the link information, the transmission type corresponding to each traffic transmission link is obtained.

[0145] In this embodiment, encrypted link information refers to encrypted link attribute information, including transmission type.

[0146] In this embodiment, external information refers to information in the encrypted link information that can be obtained without a key, including basic key types.

[0147] In this embodiment, the link key refers to the key used to decrypt the link information within the encrypted link information.

[0148] The beneficial effects of the above technical solution are: by analyzing the transmission type of each traffic transmission link, the purpose of allocating traffic information according to category can be achieved, thereby improving the efficiency of network data transmission.

[0149] Example 8:

[0150] This invention provides a traffic processing method based on network data transmission, which analyzes traffic transmission links to obtain the transmission type and traffic threshold of each traffic transmission link, including:

[0151] Based on the link information, the historical transmission logs of the traffic transmission link are obtained;

[0152] Based on the historical transmission logs, obtain the historical traffic transmission volume and historical transmission time;

[0153] A historical transmission efficiency graph is constructed using historical traffic volume as the vertical axis and historical transmission time as the horizontal axis.

[0154] Based on the historical transmission efficiency map, the value of the horizontal axis corresponding to the highest point is selected as the traffic threshold of the traffic transmission link.

[0155] In this embodiment, the historical transmission log refers to the historical transmission work log of the traffic transmission link, including the historical traffic transmission volume and historical transmission time during the historical transmission process.

[0156] In this embodiment, the historical transmission efficiency graph refers to a graph constructed with historical traffic transmission volume as the vertical axis and historical transmission time as the horizontal axis, which can represent the relationship between historical traffic transmission volume and historical transmission time.

[0157] The beneficial effects of the above technical solution are: by analyzing historical transmission logs, the relationship between historical traffic transmission volume and historical transmission time can be obtained, the traffic threshold of the traffic transmission link can be obtained, the amount of traffic information transmitted on the traffic transmission link can be better allocated, and the quality and speed of network data transmission can be improved.

[0158] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A traffic processing method based on network data transmission, characterized in that, include: Step 1: Obtain the traffic information to be transmitted and perform filtering and preprocessing on the traffic information to be transmitted; Step 2: Perform anomaly detection on the pre-processed traffic information and optimize the abnormal data to obtain the traffic information to be allocated; Step 3: Extract features from the traffic information to be allocated and classify those features; Step 4: Analyze the traffic transmission links to obtain the transmission type and traffic threshold for each traffic transmission link; Step 5: Based on the traffic transmission link analysis results and the feature classification of the traffic to be allocated, match the corresponding transmission link to the traffic information to be transmitted and transmit it; Anomaly detection is performed on the pre-processed traffic information, including: Obtain historical traffic information of successfully transmitted data and input it into the detection transmission link; Based on the signal waveforms received by each detection node of the detection transmission link, a historical waveform change trend image is obtained when historical traffic information passes through the detection transmission link. Based on the historical waveform change trend image, the key points of historical waveform attenuation are obtained; The highest point of the segment in the historical waveform change trend image that is before the historical waveform decay key point is obtained as the first key point; The lowest point of the segment in the trend of change after the historical waveform decay key point in the historical waveform change trend image is used as the second key point. The filtered traffic information is input into the detection transmission link to obtain the transmission signal of the filtered traffic information when it passes through each detection node. The transmitted signal is input into an oscilloscope to obtain the top pulse and bottom pulse of the transmitted signal; The number of intersections between the top pulse and the signal waveform corresponding to the first key point obtained for each historical traffic information is obtained, and the signal waveform corresponding to the top pulse with the most intersections is obtained as the first signal waveform; The number of intersections between the bottom pulse and the signal waveform corresponding to the second key point obtained from each historical traffic information is obtained, and the signal waveform corresponding to the bottom pulse with the most intersections is obtained as the second signal waveform; The first signal waveform and the second signal waveform are integrated to obtain the transmission waveform attenuation point of the integrated waveform; Calculate the signal strength difference between the transmission waveform attenuation point and the key attenuation point of the historical waveform; If the numerical difference is greater than the preset difference, it is determined that there is abnormal data in the filtered and preprocessed traffic information.

2. The method according to claim 1, characterized in that, Obtain the traffic information to be transmitted and perform filtering and preprocessing on the traffic information, including: Obtain the traffic information to be transmitted and extract the header data of the traffic information to be transmitted; Based on the source data information of the header data, the source database type of each header information is obtained; Based on the transmission database type at the end of network data transmission, we obtain heterogeneous source database types that differ from the transmission database type in the source data type of each header information. The data information corresponding to the different source database types is input into the database type format conversion model to obtain data information with the same format as the transmitted database type.

3. The method according to claim 1, characterized in that, Anomaly detection is performed on the pre-processed traffic information, and the abnormal data is optimized to obtain the traffic information to be allocated, including: The abnormal data is input into the abnormal data optimization model to obtain data that can be transmitted normally. Based on the data that can be transmitted normally and the data that is free of abnormalities, the traffic information to be allocated is obtained.

4. The method according to claim 1, characterized in that, Feature extraction and feature classification are performed on the traffic information to be allocated, including: The traffic information to be allocated is broken down to obtain the traffic characteristic information corresponding to the traffic information to be allocated; Based on the traffic characteristic information, corresponding feature keywords are obtained; Input the feature keywords into the feature vector transformation model to obtain the feature vector corresponding to each feature keyword; When there is only one feature vector corresponding to the traffic information to be allocated, the feature category of the traffic information to be allocated is the feature category corresponding to the feature vector; When there is more than one feature vector corresponding to the traffic information to be allocated, calculate the feature distinguishability between each feature vector corresponding to the traffic information to be allocated and the preset feature vector; The feature category of the feature vector corresponding to the feature with the highest feature discrimination value is used as the feature category of the traffic information to be assigned.

5. The method according to claim 4, characterized in that, Calculating the feature discriminant of each feature vector corresponding to the traffic information to be allocated and a preset feature vector, including: in, This represents the feature distinguishability between each feature vector corresponding to the traffic information to be allocated and a preset feature vector; This represents the i-th value in the feature vector corresponding to the traffic information to be allocated; This represents the i-th value in the preset feature vector; Indicates the sign of the maximum value; Represents the logarithmic function with base 2; The value type of the i-th value is indicated; n represents the number of values ​​in the corresponding feature vector.

6. The method according to claim 1, characterized in that, Analyze the traffic transmission links to obtain the transmission type of each traffic transmission link, including: Obtain and analyze the node information at the first node of the traffic transmission link to obtain the encrypted link information; Based on the external information of the encrypted link information, the corresponding link key is matched; Based on the encrypted link information and the link key, the link information of the traffic transmission link is obtained; Based on the link information, the transmission type corresponding to each traffic transmission link is obtained.

7. The method according to claim 6, characterized in that, Analyze the traffic transmission links to obtain the transmission type and traffic threshold for each link, including: Based on the link information, the historical transmission logs of the traffic transmission link are obtained; Based on the historical transmission logs, obtain the historical traffic transmission volume and historical transmission time; A historical transmission efficiency graph is constructed using historical traffic volume as the vertical axis and historical transmission time as the horizontal axis. Based on the historical transmission efficiency map, the value of the horizontal axis corresponding to the highest point is selected as the traffic threshold of the traffic transmission link.

Images