Short message traffic anomaly prediction and early warning method and device, and storage medium

Abstract

The invention relates to the technical field of communication, and provides a short message traffic anomaly prediction and early warning method and device, and a storage medium. The method comprises the following steps: predicting the short message traffic of a target area in a preset time period based on a preset target short message traffic prediction method to obtain target short message traffic prediction data information; judging whether the short message traffic of the target area in the preset time period is abnormal or not based on the target short message traffic prediction data information; if yes, generating a short message processing mechanism of the target area in the preset time period based on the target short message traffic prediction data information; and processing the short message request in the target area within the preset time period based on the short message processing mechanism. According to the method, when the short message flow is abnormal, it is ensured that the short message request with the high priority is processed preferentially, and the situation that the short message is discarded when the short message gateway is overloaded is effectively avoided.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, device and storage medium for predicting and warning abnormal SMS traffic. Background Art

[0002] With the development of modern communication technology, SMS, as a widely used mobile communication service, still plays an important role in business marketing, user verification, emergency notification and other scenarios. Especially in the fields of Internet finance, e-commerce platforms, social networks, etc., SMS verification and notification services have become an important way to ensure user security and maintain user experience. However, with the expansion of SMS application scenarios, SMS traffic has fluctuated greatly between different time periods and different regions, causing operators and service providers to encounter some challenges in dealing with SMS traffic anomalies.

[0003] The existing technology usually adopts a post-processing method, and only performs traffic control and resource allocation when the SMS traffic is abnormal. This passive processing method easily leads to the failure to timely and effectively process important SMS services. Summary of the invention

[0004] The present application provides a method, device and storage medium for predicting and warning abnormal SMS traffic, so as to solve the problems raised by the above-mentioned background technology.

[0005] In a first aspect, the present application provides a method for predicting and warning abnormal SMS traffic, comprising: Based on a preset target SMS traffic prediction method, the SMS traffic of the target area within a preset time period is predicted to obtain target SMS traffic prediction data information; Determine whether there is an abnormality in the SMS traffic of the target area within the preset time period based on the target SMS traffic prediction data information; If so, generating a text message processing mechanism for the target area within the preset time period based on the target text message traffic prediction data information; The SMS request within the target area is processed within the preset time period based on the SMS processing mechanism.

[0006] In a possible implementation, the method for predicting the target SMS traffic volume in a target area within a preset time period is used to predict the target SMS traffic volume, and obtain the target SMS traffic volume prediction data information, including: Predicting the SMS traffic of the target area within a preset time period based on a preset SMS traffic time series prediction model to obtain first SMS traffic prediction data information; Acquire the SMS-driven event information of the target area within the preset time period, and predict the SMS traffic of the target area within the preset time period based on the SMS-driven event information to obtain second SMS traffic prediction data information; the first SMS traffic prediction data information and the second SMS traffic prediction data information constitute the target SMS traffic prediction data information.

[0007] In a possible implementation, the acquiring the SMS-driven event information of the target area within the preset time period includes: Obtaining weather forecast information of the target area within a target time period through a meteorological service platform, wherein the target time period is after the preset time period; Determining whether the weather forecast information contains abnormal weather information; If so, determining that the abnormal weather information in the weather forecast information is a text message driven event; The online interactive activity information of the target area within the preset time period is obtained through the Internet, and the online interactive activity information is determined to be a text message driven event; wherein the online interactive activity information includes a variety of online activities.

[0008] In a possible implementation, predicting the SMS traffic of the target area within the preset time period based on the SMS-driven event information to obtain second SMS traffic prediction data information includes: For each driving event in the driving event information, a target SMS traffic prediction method corresponding to the driving event is obtained in a database, and a SMS traffic prediction value corresponding to the driving event is determined based on the target SMS traffic prediction method, and a SMS type corresponding to the driving event is determined based on a preset SMS classification method; For each driving event in the driving event information, a mapping relationship between the SMS traffic prediction value corresponding to the driving event and the SMS type is constructed; each of the mapping relationships constitutes the second SMS traffic prediction data information.

[0009] In a possible implementation, the method for obtaining the target SMS traffic prediction corresponding to the driving event in the database includes: Encoding the driving event based on a preset encoding rule to obtain a coding sequence corresponding to the driving event; The similarities between the coding sequence and each preset coding in the database are respectively obtained, and the SMS traffic prediction method corresponding to the maximum similarity among each of the similarities is determined as the target SMS traffic prediction method.

[0010] In a possible implementation, the target SMS traffic prediction data information includes a plurality of mapping relationships, where the mapping relationship is a mapping relationship between SMS types and SMS traffic prediction values, and judging whether there is an abnormality in the SMS traffic of the target area within the preset time period based on the target SMS traffic prediction data information includes: Adding the SMS traffic prediction values ​​corresponding to each SMS type to obtain the sum of the SMS traffic prediction values; Comparing the sum of the SMS traffic prediction values ​​with a preset SMS traffic threshold; If the sum of the predicted SMS traffic values ​​is greater than the preset SMS traffic threshold, it is determined that the SMS traffic in the target area within the preset time period is abnormal.

[0011] In a possible implementation, the generating of the SMS processing mechanism for the target area within the preset time period based on the target SMS traffic prediction data information includes: Obtaining the priority of each of the SMS types in the database, and determining the SMS type with a priority higher than a preset priority as the first SMS type, and determining the SMS type with a priority not higher than the preset priority as the second SMS type; When there are multiple SMS requests at the same time, determining whether the number of the SMS requests is less than the preset SMS traffic threshold; If so, determine to process each of the SMS requests simultaneously; If not, determining whether the number of SMS requests corresponding to the first SMS type in the multiple SMS requests is less than the preset SMS traffic threshold; If so, determine to give priority to the SMS request corresponding to the first SMS type in the multiple SMS requests, and store the SMS request corresponding to the second SMS type in the multiple SMS requests in a preset cache, and when the number of SMS requests is less than the preset SMS traffic threshold, process the SMS request corresponding to the second SMS type in the multiple SMS requests stored in the cache based on the number of SMS requests and the preset SMS traffic threshold; If not, the multiple SMS requests are processed based on the priority corresponding to each of the multiple SMS requests.

[0012] In a possible implementation, the method further includes: Binding the target SMS traffic prediction data information with the SMS processing mechanism to obtain a binding result, and storing the binding result in a database; The step of binding the target SMS traffic prediction data information with the SMS processing mechanism to obtain a binding result includes: Performing matrix coding on the target SMS traffic prediction data information to obtain a first coding matrix, and performing matrix coding on the SMS processing mechanism to obtain a second coding matrix; the first coding matrix and the second coding matrix are the same type of matrices; Determine a first target matrix element in the first encoding matrix, and determine a second target matrix element in the second encoding matrix; the sum of the row number and the column number of the first target matrix element is a composite number, and the sum of the row number and the column number of the second target matrix is ​​a composite number; In the first encoding matrix and the second encoding matrix, the first target matrix elements having the same sum of row numbers and column numbers are exchanged with the second target matrix elements to obtain a first target matrix and a second target matrix; wherein the first target matrix is ​​a target matrix corresponding to the first encoding matrix, and the second target matrix is ​​a target matrix corresponding to the second encoding matrix; Bind the first target matrix and the second target matrix to obtain the binding result.

[0013] In a second aspect, the present application provides a device for predicting and warning abnormal SMS traffic, comprising: A prediction module is used to predict the SMS traffic of a target area within a preset time period based on a preset target SMS traffic prediction method to obtain target SMS traffic prediction data information; A judgment module, used for judging whether the SMS traffic of the target area within the preset time period is abnormal based on the target SMS traffic prediction data information; A generating module, configured to generate a SMS processing mechanism for the target area within the preset time period based on the target SMS traffic prediction data information if there is an abnormality in the SMS traffic of the target area within the preset time period; A processing module is used to process the SMS request in the target area within the preset time period based on the SMS processing mechanism.

[0014] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the SMS traffic anomaly prediction and early warning method as described in any one of the above items is implemented.

[0015] The present application provides a method, device and storage medium for predicting and warning of SMS traffic anomaly. The method includes: predicting the SMS traffic of a target area within a preset time period based on a preset target SMS traffic prediction method to obtain target SMS traffic prediction data information; judging whether the SMS traffic of the target area within the preset time period is abnormal based on the target SMS traffic prediction data information; if so, generating a SMS processing mechanism for the target area within the preset time period based on the target SMS traffic prediction data information; and processing SMS requests within the target area within the preset time period based on the SMS processing mechanism. The method, on the one hand, predicts the SMS traffic of the target area within the preset time period based on the preset target SMS traffic prediction method to obtain target SMS traffic prediction data information, thereby realizing the prediction of the SMS traffic of the target area, which helps to timely discover potential SMS traffic anomalies, thereby avoiding SMS service interruption. On the other hand, when it is detected that the SMS traffic of the target area within the preset time period is abnormal, the SMS processing mechanism of the target area within the preset time period is generated based on the target SMS traffic prediction data information, thereby realizing that when the SMS traffic is abnormal, high-priority SMS requests are processed first, effectively avoiding the SMS gateway from discarding SMS when it is overloaded. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0017] Figure 1 A flowchart of a method for predicting and warning abnormal SMS traffic provided by an embodiment of the present application; Figure 2 A schematic block diagram of the structure of the SMS traffic anomaly prediction and early warning device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0020] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0021] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0022] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0023] See also Figure 1 , Figure 1 A flowchart of a method for predicting and warning abnormal SMS traffic provided by an embodiment of the present application is shown in FIG. Figure 1 As shown, the SMS traffic anomaly prediction and warning method provided in the embodiment of the present application includes steps S1 to S4.

[0024] Step S1: predicting the SMS traffic of a target area within a preset time period based on a preset target SMS traffic prediction method to obtain target SMS traffic prediction data information.

[0025] Specifically, step S1 includes the following steps: Based on a preset SMS traffic time series prediction model, the SMS traffic in the target area within a preset time period is predicted to obtain first SMS traffic prediction data information; wherein the SMS traffic time series prediction model is trained using historical SMS traffic data information in the target area, and the historical SMS traffic data information is SMS traffic data information driven by no SMS events; Acquire the SMS-driven event information of the target area within the preset time period, and predict the SMS traffic of the target area within the preset time period based on the SMS-driven event information to obtain second SMS traffic prediction data information; the first SMS traffic prediction data information and the second SMS traffic prediction data information constitute the target SMS traffic prediction data information.

[0026] Wherein, the step of obtaining the SMS-driven event information of the target area within the preset time period comprises the following steps: Obtaining weather forecast information of the target area within a target time period through a meteorological service platform, wherein the target time period is after the preset time period; Determining whether the weather forecast information contains abnormal weather information; If so, the abnormal weather information in the weather forecast information is determined to be a text message driven event; the abnormal weather information includes high temperature, extreme cold, strong wind, typhoon, heavy rain, etc.; it can be understood that when abnormal weather information exists in the target time period, it is necessary to notify the personnel in the target area to take precautions by text message notification within the preset time period. Therefore, when abnormal weather information exists in the target time period, it is necessary to determine the abnormal weather information as a text message driven event; The online interactive activity information of the target area within the preset time period is obtained through the Internet, and the online interactive activity information is determined to be an SMS-driven event; wherein, the online interactive activity information includes a variety of online activities, and the online interactive activity information includes but is not limited to online promotions, online live broadcasts, online voting and online lotteries, etc.; it is understandable that when conducting online promotions, it is necessary to carry out marketing by sending text messages, and when conducting online live broadcasts, when users purchase products or services, they need to verify their identities by sending verification codes, and when conducting online voting and online lotteries, participants are also required to vote or draw by sending text messages. Therefore, it is necessary to determine activities such as online promotions, online live broadcasts, online voting and online lotteries as SMS-driven events.

[0027] The method of predicting the SMS traffic of the target area within the preset time period based on the SMS driven event information to obtain second SMS traffic prediction data information includes the following steps: For each driving event in the driving event information, a target SMS traffic prediction method corresponding to the driving event is obtained in a database, and a predicted SMS traffic value corresponding to the driving event is determined based on the target SMS traffic prediction method, and the SMS type corresponding to the driving event is determined based on a preset SMS classification method; specifically, the target SMS traffic prediction method corresponding to the driving event is obtained in a database, including: encoding the driving event based on a preset encoding rule to obtain a coding sequence corresponding to the driving event; respectively obtaining the similarity between the coding sequence and each preset coding in the database, and determining that the SMS traffic prediction method corresponding to the maximum similarity among each of the similarities is the target SMS traffic prediction method; For each driving event in the driving event information, a mapping relationship between the SMS traffic prediction value corresponding to the driving event and the SMS type is constructed; each of the mapping relationships constitutes the second SMS traffic prediction data information.

[0028] Step S1 of this solution predicts the SMS traffic of the target area within a preset time period based on a preset SMS traffic time series prediction model to obtain the first SMS traffic prediction data information, obtains the SMS-driven event information of the target area within the preset time period, and predicts the SMS traffic of the target area within the preset time period based on the SMS-driven event information to obtain the second SMS traffic prediction data information to achieve a more comprehensive and accurate SMS traffic prediction. This dual prediction mechanism can not only accurately predict daily SMS traffic, but also dynamically respond to SMS traffic fluctuations caused by emergencies, thereby improving the service quality, emergency response capability and resource scheduling efficiency of the SMS system.

[0029] Step S2: determining whether there is an abnormality in the SMS traffic of the target area within the preset time period based on the target SMS traffic prediction data information.

[0030] Specifically, the target SMS traffic prediction data information includes a plurality of mapping relationships, wherein the mapping relationship is a mapping relationship between SMS types and SMS traffic prediction values, and judging whether there is an abnormality in the SMS traffic of the target area within the preset time period based on the target SMS traffic prediction data information includes: Adding the SMS traffic prediction values ​​corresponding to each SMS type to obtain the sum of the SMS traffic prediction values; Compare the sum of the SMS traffic prediction values ​​with a preset SMS traffic threshold; wherein the preset SMS traffic threshold is the maximum number of SMS messages that can be processed simultaneously by the SMS processing platform in the target area; If the sum of the predicted SMS traffic values ​​is greater than the preset SMS traffic threshold, it is determined that the SMS traffic of the target area within the preset time period is abnormal. It can be understood that when the sum of the predicted SMS traffic values ​​is greater than the preset SMS traffic threshold, it is determined that the SMS traffic of the target area within the preset time period is abnormal in order to prevent the number of SMS messages processed at the same time within the preset time period from being greater than the preset SMS traffic threshold, which causes the gateway to be overloaded when the number of SMS messages processed at the same time is greater than the preset SMS traffic threshold, thereby causing the gateway to lose some SMS messages, so that some SMS requests with higher priority cannot be processed in a timely and effective manner, affecting the user experience.

[0031] Step S3: If yes, generate a SMS processing mechanism for the target area within the preset time period based on the target SMS traffic prediction data information.

[0032] Specifically, step S3 includes the following steps: Obtaining the priority of each of the SMS types in the database, and determining the SMS type with a priority higher than the preset priority as the first SMS type, and determining the SMS type with a priority not higher than the preset priority as the second SMS type; wherein the SMS request corresponding to the first SMS type must be processed and completed within the preset time period, for example, a verification code SMS, an abnormal weather notification SMS, a lottery SMS, and a voting SMS, and the SMS request corresponding to the first SMS type may not be processed and completed within the preset time period, for example: a marketing SMS; When there are multiple SMS requests at the same time, determining whether the number of the SMS requests is less than the preset SMS traffic threshold; If so, determine to process each of the SMS requests simultaneously; If not, determining whether the number of SMS requests corresponding to the first SMS type in the multiple SMS requests is less than the preset SMS traffic threshold; If so, determine to give priority to the SMS requests corresponding to the first SMS type in the multiple SMS requests, and store the SMS requests corresponding to the second SMS type in the multiple SMS requests in a preset cache, and when the number of SMS requests is less than the preset SMS traffic threshold, process the SMS requests corresponding to the second SMS type in the multiple SMS requests stored in the cache based on the number of SMS requests and the preset SMS traffic threshold; specifically, the amount of SMS requests processed at one time corresponding to the second SMS type in the multiple SMS requests stored in the cache is the difference between the preset SMS traffic threshold and the number of SMS requests; If not, the multiple SMS requests are processed based on the priority corresponding to each of the multiple SMS requests. Specifically, each of the SMS requests is classified based on the priority corresponding to each of the SMS requests to obtain multiple SMS request sets, each of the SMS request sets has a different priority, and each of the SMS request sets is processed in sequence from high to low priority. It should be noted that when processing a certain SMS request set, if the amount of SMS requests in the SMS request set is greater than the preset SMS traffic threshold, the SMS requests in the SMS request set are processed in batches, and the amount of SMS requests processed each time is not greater than the preset SMS traffic threshold.

[0033] Step S3 provided in this embodiment can ensure that SMS requests with high priorities are processed first while ensuring the processing efficiency of SMS requests, thereby improving user experience.

[0034] Step S4: Processing the SMS requests within the target area within the preset time period based on the SMS processing mechanism.

[0035] The method provided in this embodiment, on the one hand, predicts the SMS traffic of the target area within the preset time period based on a preset target SMS traffic prediction method to obtain target SMS traffic prediction data information, thereby realizing the prediction of the SMS traffic in the target area, which is helpful to timely discover potential SMS traffic anomalies, thereby avoiding SMS service interruptions. On the other hand, when it is detected that the SMS traffic of the target area within the preset time period is abnormal, a SMS processing mechanism for the target area within the preset time period is generated based on the target SMS traffic prediction data information, thereby ensuring that high-priority SMS requests are processed first when SMS traffic is abnormal, effectively avoiding the SMS gateway from discarding SMS messages when it is overloaded.

[0036] In some embodiments, the method further comprises: Binding the target SMS traffic prediction data information with the SMS processing mechanism to obtain a binding result, and storing the binding result in a database; The step of binding the target SMS traffic prediction data information with the SMS processing mechanism to obtain a binding result includes the following steps: Performing matrix coding on the target SMS traffic prediction data information to obtain a first coding matrix, and performing matrix coding on the SMS processing mechanism to obtain a second coding matrix; the first coding matrix and the second coding matrix are the same type of matrices; Determine a first target matrix element in the first encoding matrix, and determine a second target matrix element in the second encoding matrix; the sum of the row number and the column number of the first target matrix element is a composite number, and the sum of the row number and the column number of the second target matrix is ​​a composite number; In the first encoding matrix and the second encoding matrix, the first target matrix elements having the same sum of row numbers and column numbers are exchanged with the second target matrix elements to obtain a first target matrix and a second target matrix; wherein the first target matrix is ​​a target matrix corresponding to the first encoding matrix, and the second target matrix is ​​a target matrix corresponding to the second encoding matrix; Bind the first target matrix and the second target matrix to obtain the binding result.

[0037] The method provided in this embodiment, on the one hand, can ensure that the two data sets are matched and converted in the same dimension by encoding the target SMS traffic prediction data information and the SMS processing mechanism into the same type of encoding, thereby improving the efficiency of data processing. On the other hand, by exchanging the first target matrix elements with the second target matrix elements whose row numbers and column numbers are consistent in the first encoding matrix and the second encoding matrix, the first target matrix and the second target matrix are obtained, which effectively avoids the random or disordered binding process and ensures that the data remains logical when binding. On the other hand, the binding results are stored in the database for subsequent quick query and call, which enhances the traceability and intelligent management capabilities of the system.

[0038] See also Figure 2 , Figure 2 A schematic block diagram of the structure of the SMS traffic anomaly prediction and warning device 100 provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the SMS traffic anomaly prediction and warning device 100 provided in the embodiment of the present application includes: The prediction module 110 is used to predict the SMS traffic of the target area within a preset time period based on a preset target SMS traffic prediction method to obtain target SMS traffic prediction data information.

[0039] The judgment module 120 is used to judge whether there is an abnormality in the SMS traffic of the target area within the preset time period based on the target SMS traffic prediction data information.

[0040] The generation module 130 is used to generate a SMS processing mechanism for the target area within the preset time period based on the target SMS traffic prediction data information if there is an abnormality in the SMS traffic of the target area within the preset time period.

[0041] The processing module 140 is configured to process the SMS request within the target area within the preset time period based on the SMS processing mechanism.

[0042] It should be noted that technicians in the relevant technical field can clearly understand that for the convenience and conciseness of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned SMS traffic anomaly prediction and early warning method embodiment, and will not be repeated here.

[0043] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by one or more processors, the one or more processors implement the SMS traffic anomaly prediction and early warning method provided in the embodiment of the present application.

[0044] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for predicting and warning abnormal SMS traffic, characterized in that: include: Based on a preset target SMS traffic prediction method, the SMS traffic of the target area within a preset time period is predicted to obtain target SMS traffic prediction data information; Determine whether there is an abnormality in the SMS traffic of the target area within the preset time period based on the target SMS traffic prediction data information; If so, generating a text message processing mechanism for the target area within the preset time period based on the target text message traffic prediction data information; The SMS request within the target area is processed within the preset time period based on the SMS processing mechanism.

2. The method for predicting and warning abnormal SMS traffic according to claim 1, characterized in that: The method for predicting the target SMS traffic volume based on the preset target SMS traffic volume predicts the SMS traffic volume in the target area within the preset time period to obtain the target SMS traffic volume prediction data information, including: Predicting the SMS traffic of the target area within a preset time period based on a preset SMS traffic time series prediction model to obtain first SMS traffic prediction data information; Acquire the SMS-driven event information of the target area within the preset time period, and predict the SMS traffic of the target area within the preset time period based on the SMS-driven event information to obtain second SMS traffic prediction data information; the first SMS traffic prediction data information and the second SMS traffic prediction data information constitute the target SMS traffic prediction data information.

3. The method for predicting and warning abnormal SMS traffic according to claim 2, characterized in that: The obtaining of the SMS-driven event information of the target area within the preset time period includes: Obtaining weather forecast information of the target area within a target time period through a meteorological service platform, wherein the target time period is after the preset time period; Determining whether the weather forecast information contains abnormal weather information; If so, determining that the abnormal weather information in the weather forecast information is a text message driven event; The online interactive activity information of the target area within the preset time period is obtained through the Internet, and the online interactive activity information is determined to be a text message driven event; wherein the online interactive activity information includes a variety of online activities.

4. The method for predicting and warning abnormal SMS traffic according to claim 3, characterized in that: The predicting the SMS traffic of the target area within the preset time period based on the SMS driven event information to obtain second SMS traffic prediction data information includes: For each driving event in the driving event information, a target SMS traffic prediction method corresponding to the driving event is obtained in a database, and a SMS traffic prediction value corresponding to the driving event is determined based on the target SMS traffic prediction method, and a SMS type corresponding to the driving event is determined based on a preset SMS classification method; For each driving event in the driving event information, a mapping relationship between the SMS traffic prediction value corresponding to the driving event and the SMS type is constructed; each of the mapping relationships constitutes the second SMS traffic prediction data information.

5. The method for predicting and warning abnormal SMS traffic according to claim 4, characterized in that: The method for obtaining the target SMS traffic prediction corresponding to the driving event in the database includes: Encoding the driving event based on a preset encoding rule to obtain a coding sequence corresponding to the driving event; The similarities between the coding sequence and each preset coding in the database are respectively obtained, and the SMS traffic prediction method corresponding to the maximum similarity among each of the similarities is determined as the target SMS traffic prediction method.

6. The method for predicting and warning abnormal SMS traffic according to claim 1, characterized in that: The target SMS traffic prediction data information includes a plurality of mapping relationships, wherein the mapping relationship is a mapping relationship between SMS types and SMS traffic prediction values, and the step of judging whether the SMS traffic of the target area within the preset time period is abnormal based on the target SMS traffic prediction data information includes: Adding the SMS traffic prediction values ​​corresponding to each SMS type to obtain the sum of the SMS traffic prediction values; Comparing the sum of the SMS traffic prediction values ​​with a preset SMS traffic threshold; If the sum of the predicted SMS traffic values ​​is greater than the preset SMS traffic threshold, it is determined that the SMS traffic in the target area within the preset time period is abnormal.

7. The method for predicting and warning abnormal SMS traffic according to claim 6, characterized in that: The generating of the SMS processing mechanism for the target area within the preset time period based on the target SMS traffic prediction data information includes: Obtaining the priority of each of the SMS types in the database, and determining the SMS type with a priority higher than a preset priority as the first SMS type, and determining the SMS type with a priority not higher than the preset priority as the second SMS type; When there are multiple SMS requests at the same time, determining whether the number of the SMS requests is less than the preset SMS traffic threshold; If so, determine to process each of the SMS requests simultaneously; If not, determining whether the number of SMS requests corresponding to the first SMS type in the multiple SMS requests is less than the preset SMS traffic threshold; If so, determine to give priority to the SMS request corresponding to the first SMS type in the multiple SMS requests, and store the SMS request corresponding to the second SMS type in the multiple SMS requests in a preset cache, and when the number of SMS requests is less than the preset SMS traffic threshold, process the SMS request corresponding to the second SMS type in the multiple SMS requests stored in the cache based on the number of SMS requests and the preset SMS traffic threshold; If not, the multiple SMS requests are processed based on the priority corresponding to each of the multiple SMS requests.

8. The method for predicting and warning abnormal SMS traffic according to claim 1, characterized in that: The method further comprises: Binding the target SMS traffic prediction data information with the SMS processing mechanism to obtain a binding result, and storing the binding result in a database; The step of binding the target SMS traffic prediction data information with the SMS processing mechanism to obtain a binding result includes: Performing matrix coding on the target SMS traffic prediction data information to obtain a first coding matrix, and performing matrix coding on the SMS processing mechanism to obtain a second coding matrix; the first coding matrix and the second coding matrix are the same type of matrices; Determine a first target matrix element in the first encoding matrix, and determine a second target matrix element in the second encoding matrix; the sum of the row number and the column number of the first target matrix element is a composite number, and the sum of the row number and the column number of the second target matrix is ​​a composite number; In the first encoding matrix and the second encoding matrix, the first target matrix elements having the same sum of row numbers and column numbers are exchanged with the second target matrix elements to obtain a first target matrix and a second target matrix; wherein the first target matrix is ​​a target matrix corresponding to the first encoding matrix, and the second target matrix is ​​a target matrix corresponding to the second encoding matrix; Bind the first target matrix and the second target matrix to obtain the binding result.

9. A device for predicting and warning abnormal SMS traffic, characterized in that: include: A prediction module is used to predict the SMS traffic of a target area within a preset time period based on a preset target SMS traffic prediction method to obtain target SMS traffic prediction data information; A judgment module, used for judging whether the SMS traffic of the target area within the preset time period is abnormal based on the target SMS traffic prediction data information; A generating module, configured to generate a SMS processing mechanism for the target area within the preset time period based on the target SMS traffic prediction data information if there is an abnormality in the SMS traffic of the target area within the preset time period; A processing module is used to process the SMS request in the target area within the preset time period based on the SMS processing mechanism.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the method for predicting and warning abnormal SMS traffic according to any one of claims 1 to 8 is implemented.

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