Short message sending quality monitoring system and method based on machine learning

Abstract

The invention provides a short message sending quality monitoring system and method based on machine learning, and the method comprises the steps: carrying out the time delay constraint of a short message sending process through a delay fluctuation feature in the short message sending process, the network delay of a short message sending environment, and a preset basic timeout threshold value, and obtaining the time delay tolerance in the short message sending process; performing confidence adjustment on a basic timeout threshold value in short message sending based on the time delay tolerance to obtain a confidence judgment interval of the timeout threshold value, and further extracting degradation characteristics of a communication channel timeout event in the short message sending process; and inputting the degradation characteristics of the timeout event and the historical delivery rate of short message sending into an intelligent decision model of the communication channel quality, outputting a continuous timeout threshold value of the communication channel in the short message sending process, and performing reliability evaluation on the communication channel quality based on the continuous timeout times in the short message sending process and the continuous timeout threshold value of the communication channel. Based on the above scheme, the time sequence deterioration evaluation of the channel quality in the short message sending timeout state can be realized.

Description

Technical Field

[0001] The present application relates to the technical field of communication quality assessment, and more specifically, to a system and method for monitoring the quality of text message sending based on machine learning. Background Art

[0002] With the widespread adoption of mobile internet, SMS messaging is no longer limited to traditional text messages. It has gradually integrated multimedia content, such as images, audio, and video, creating rich media messaging. This form of SMS offers a richer and more engaging way to deliver information, meeting user needs in diverse scenarios such as social interaction, business promotion, and public services. Furthermore, the security and privacy protection of SMS messaging have received increasing attention. With the improvement of laws and regulations and technological advancements, SMS platforms have implemented stricter measures to protect user data and information security, ensuring the safety and reliability of user information.

[0003] Existing SMS multi-channel switching mechanisms suffer from significant real-time and long-term deficiencies. In real-time, they rely on simple polling or random allocation strategies, failing to dynamically detect instantaneous fluctuations in channel quality. This results in messages being continuously distributed to degraded channels, exacerbating the risk of delivery failures. In the long term, they focus solely on instantaneous failures while ignoring the gradual degradation of channel performance. This lack of trend assessment of channel health prevents the SMS service platform from prematurely eliminating chronically degraded channels, ultimately impacting overall service reliability. This extensive management approach reduces resource utilization and increases the pressure on operations and maintenance personnel to respond passively. Therefore, the industry faces the challenge of assessing the temporal degradation of channel quality during SMS timeouts, thereby improving the accuracy of SMS channel switching. Summary of the Invention

[0004] The present application provides a system and method for monitoring the quality of SMS sending based on machine learning, which can realize the timing degradation evaluation of channel quality under the condition of SMS sending timeout.

[0005] In a first aspect, the present application provides a method for evaluating the quality of a text message sending channel, which is used in a machine learning-based text message sending quality monitoring system to evaluate the quality of a text message sending channel. The method comprises: During the SMS sending process, the response time information from the sending end to the receiving end in the communication channel of the SMS sending request is collected; Extracting delay fluctuation characteristics during SMS sending from the response time information within a preset time window, and applying delay constraints to the SMS sending process based on the delay fluctuation characteristics, the network delay of the SMS sending environment, and a preset basic timeout threshold to obtain a delay tolerance during SMS sending; Performing confidence adjustment on a basic timeout threshold during SMS sending based on the delay tolerance to obtain a confidence interval for the timeout threshold during SMS sending, and then extracting degradation characteristics of a communication channel timeout event during SMS sending from the response time information using the confidence interval; The degradation characteristics of the timeout event and the historical delivery rate of SMS messages are input into an intelligent decision-making model for the quality of the communication channel, and a continuous timeout threshold of the communication channel during the SMS sending process is output. The number of continuous timeouts during the SMS sending process is monitored in real time, and the reliability of the communication channel quality is evaluated based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

[0006] In some embodiments, extracting delay fluctuation characteristics during SMS sending from the response time information specifically includes: Obtaining the response time of all SMS messages sent within a preset time window from the response time information; Determine the moving average delay of SMS messages sent within a preset time window using all response times; The delay fluctuation characteristics during the text message sending process are calculated based on the moving average delay.

[0007] In some embodiments, confidence adjustment is performed on a basic timeout threshold during SMS sending based on the delay tolerance to obtain a confidence interval for the timeout threshold during SMS sending, specifically including: Obtain the basic timeout threshold and dynamic adjustment coefficient during SMS sending; Determine the confidence adjustment parameter of the timeout threshold during SMS sending by using the dynamic adjustment coefficient and the delay tolerance; The basic timeout threshold is flexibly determined by using the confidence adjustment parameter to obtain a confidence determination interval of the timeout threshold during the text message sending process.

[0008] In some embodiments, extracting degradation characteristics of a communication channel timeout event during SMS sending from the response time information using the confidence interval specifically includes: For each SMS message sent within the preset time window, obtaining the response time of the SMS message sending from the response time information; If the response time exceeds the confidence interval, the SMS sending is recorded as a timeout event, completing the timeout judgment of the SMS sending; Then, the timeout judgment of each SMS message sent within the preset time window is completed, and multiple timeout events are obtained; The number of all timeout events is counted, and then the degradation characteristics of communication channel timeout events during SMS sending are calculated.

[0009] In some embodiments, performing reliability assessment on the communication channel quality based on the number of consecutive timeouts and the consecutive timeout threshold of the communication channel specifically includes: Get the continuous timeout threshold of the communication channel; Determine and calculate the communication delay characteristics in SMS sending by the number of consecutive timeouts and the consecutive timeout threshold; The communication channel quality in text message sending is evaluated based on the communication delay characteristics.

[0010] In some embodiments, the communication channel is a text message transmission link based on an operator's core network.

[0011] In some embodiments, the intelligent decision model is a communication intelligent decision model based on a random forest decision tree.

[0012] In a second aspect, the present application provides a system for monitoring the quality of SMS sending based on machine learning, including a channel quality assessment unit, wherein the channel quality assessment unit includes: The acquisition module is used to collect the response time information from the sending end to the receiving end in the communication channel of the SMS sending request during the SMS sending process; a processing module, configured to extract delay fluctuation characteristics during SMS sending from the response time information within a preset time window, impose a delay constraint on the SMS sending process based on the delay fluctuation characteristics, the network delay of the SMS sending environment, and a preset basic timeout threshold, and obtain a delay tolerance during SMS sending; The processing module is further configured to perform confidence adjustment on a basic timeout threshold during SMS sending based on the delay tolerance to obtain a confidence interval for the timeout threshold during SMS sending, and then extract degradation characteristics of a communication channel timeout event during SMS sending from the response time information using the confidence interval. The execution module is used to input the degradation characteristics of the timeout event and the historical delivery rate of SMS messages into an intelligent decision-making model for the quality of the communication channel, output a continuous timeout threshold of the communication channel during the SMS sending process, monitor the number of continuous timeouts during the SMS sending process in real time, and perform a reliability assessment of the communication channel quality based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

[0013] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned SMS sending channel quality assessment method.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer implements the above-mentioned SMS sending channel quality assessment method when executed.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The present application provides a system and method for monitoring the quality of SMS sending based on machine learning. During the SMS sending process, response time information from the sending end to the receiving end in the communication channel of the SMS sending request is collected. Within a preset time window, delay fluctuation characteristics during the SMS sending process are extracted from the response time information. The SMS sending process is subjected to delay constraints based on the delay fluctuation characteristics, the network delay of the SMS sending environment, and a preset basic timeout threshold to obtain a delay tolerance during the SMS sending process. The basic timeout threshold during the SMS sending process is confidence-adjusted based on the delay tolerance to obtain a confidence determination interval for the timeout threshold during the SMS sending process. The degradation characteristics of the communication channel timeout event during the SMS sending process are then extracted from the response time information using the confidence determination interval. The degradation characteristics of the timeout event and the historical delivery rate of SMS sending are input into an intelligent decision model for the communication channel quality. The continuous timeout threshold of the communication channel during the SMS sending process is output. The number of continuous timeouts during the SMS sending process is monitored in real time. The reliability of the communication channel quality is evaluated based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

[0016] It can be seen that in this application, the number of consecutive timeouts during the SMS sending process is monitored in real time, and the reliability of the communication channel quality is evaluated based on the number of consecutive timeouts and the continuous timeout threshold of the communication channel; first, the delay tolerance is determined to obtain an adaptively adjusted delay constraint standard, so that the SMS service platform can more accurately distinguish between normal fluctuations and abnormal degradation. The traditional solution relies on a fixed timeout threshold and cannot adapt to dynamic changes in different network environments (such as congestion, cross-operator transmission), resulting in misjudgment or missed judgment. Adjusting the tolerance based on real-time delay fluctuation characteristics can appropriately relax the threshold in a high-latency environment to avoid incorrect channel switching due to short-term jitter; tightening the constraints in low-latency but high-volume scenarios to capture potential degradation in advance, thereby It can significantly improve the accuracy of timeout event identification; then, by determining the degradation characteristics of timeout events, the timing law of channel degradation can be obtained, thereby realizing fine-grained modeling of channel quality degradation. Traditional methods only count the number of timeouts and ignore the distribution characteristics in the time dimension, resulting in a lag in switching strategy. However, by screening high-confidence timeout events through confidence judgment intervals and analyzing degradation trends in combination with historical delivery rates, the evaluation model can distinguish between occasional failures and continuous degradation, thereby enhancing the timing sensitivity of channel quality assessment and improving the switching accuracy of SMS sending channels in timeout conditions. In summary, based on the above scheme, the timing degradation assessment of channel quality in the SMS sending timeout state can be realized, thereby improving the switching accuracy of SMS sending channels. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0018] Figure 1 is an exemplary flow chart of a method for evaluating the quality of a text message sending channel according to some embodiments of the present application; Figure 2 This is an application scenario diagram of SMS sending according to some embodiments of the present application; Figure 3 is a schematic diagram of a process for implementing reliability assessment according to some embodiments of the present application; Figure 4 is a schematic structural diagram of a channel quality assessment unit according to some embodiments of the present application; Figure 5 It is a structural diagram of a computer device for implementing a method for evaluating the quality of a text message sending channel according to some embodiments of the present application. DETAILED DESCRIPTION

[0019] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0020] refer to Figure 1 , which is an exemplary flow chart of a method for evaluating the quality of a text message sending channel according to some embodiments of the present application. The method for evaluating the quality of a text message sending channel mainly includes the following steps: In step 101, during the SMS sending process, response time information from the sending end to the receiving end in the communication channel of the SMS sending request is collected.

[0021] It should be noted that, in this application, response time information refers to the time data from the sending end initiating the SMS transmission request to the receiving end responding; the communication channel is an SMS transmission link based on the operator's core network; in the SMS transmission scenario, the sending end refers to the SMS service platform, and the receiving end refers to the target user terminal device; the SMS sending request refers to the SMS transmission instruction submitted to the SMS service platform.

[0022] In specific implementation, during the SMS sending process, the status report returned by the operator is used to collect the response time from the sender to the receiver in the communication channel for each SMS sending request within a specified time period (the default is the most recent 1 month), and the collection of all response times is used as the response time information from the sender to the receiver in the communication channel.

[0023] In some embodiments, reference Figure 2 As described above, this figure is an application scenario diagram of SMS sending according to some embodiments of the present application. The figure shows a typical application scenario of SMS sending and receiving. Device 1 on the left side of the figure represents the SMS sender, which sends the SMS content to the cloud service (3 in the figure) via wireless signals. This is usually an SMS gateway or SMS center. The cloud service is responsible for processing and forwarding the SMS, and then sending the SMS to the network area where the recipient is located via wireless signals (there are multiple concentric circles around device 2 in the figure, indicating different signal coverage areas). The recipient's device 2 is within the signal coverage area and can therefore receive the SMS from the sender. The entire process shows the complete path of the SMS from sending to receiving, including transit and distribution through the cloud service.

[0024] In step 102, within a preset time window, the delay fluctuation characteristics of the SMS sending process are extracted from the response time information, and the SMS sending process is subjected to delay constraints based on the delay fluctuation characteristics, the network delay of the SMS sending environment, and the preset basic timeout threshold to obtain the delay tolerance of the SMS sending process.

[0025] It should be noted that in this application, the preset time window refers to a fixed time interval set by the system (the default is 5 minutes). The preset time window can be used to divide and analyze the SMS sending situation in different time periods, and different time windows can be set for different time points.

[0026] In some embodiments, extracting the delay fluctuation characteristics during SMS sending from the response time information can be achieved by using the following steps: Obtaining the response time of all SMS messages sent within a preset time window from the response time information; Determine the moving average delay of SMS messages sent within a preset time window using all response times; The delay fluctuation characteristics during the text message sending process are calculated based on the moving average delay.

[0027] It should be noted that in this application, the delay fluctuation feature is used to quantify the degree to which the response time deviates from the average value. The delay fluctuation feature can characterize the stability of network transmission during SMS sending; the moving average delay refers to the arithmetic mean of all SMS sending response times within a specific time window. The moving average delay can reflect the overall transmission efficiency within the time window.

[0028] In specific implementation, first, obtaining the response time of all SMS sending within the preset time window from the response time information can be achieved in the following manner, namely: obtaining the response time of the SMS sending time in the response time information within the preset time window, and thus obtaining the response time of all SMS sending within the preset time window; then, determining the moving average delay of SMS sending within the preset time window through all response times can be achieved in the following manner, namely: taking the mean of all response times as the moving average delay of SMS sending within the preset time window; finally, calculating the delay fluctuation characteristics in the SMS sending process based on the moving average delay can be achieved in the following manner, namely: using the moving average delay to calculate the standard deviation of the response time of all SMS sending within the preset time window as the delay fluctuation characteristics in the SMS sending process.

[0029] In some embodiments, the delay tolerance of the SMS sending process can be obtained by constraining the SMS sending process by using the delay fluctuation characteristics, the network delay of the SMS sending environment, and a preset basic timeout threshold. The following steps can be used to achieve this: Initialize a time-delay regression model based on long short-term memory network as the time-delay constraint model; Using the delay fluctuation characteristics as timing characteristics input in a delay constraint model; The network delay of the SMS sending environment is used as the environmental state feature input in the delay constraint model; The preset basic timeout threshold is used as the benchmark constraint feature input in the delay constraint model; The delay constraint model after feature input is used to dynamically predict the delay of the SMS sending process and output the delay tolerance during the SMS sending process.

[0030] It should be noted that in this application, delay tolerance is an indicator that reflects the acceptable degree of timeout under current network conditions; the delay constraint model is a mathematical model based on a long short-term memory network. The delay constraint model is a specially designed time series regression model based on a long short-term memory network in the SMS service platform. It uses memory units and gating mechanisms to learn the dynamic changes in SMS sending delays. The delay constraint model receives input features in three dimensions: time series features (delay fluctuations) are used to capture the changing trend of response time, environmental state features (network delay) reflect the current network status, and benchmark constraint features (basic timeout threshold) provide a service benchmark. The long short-term memory network can effectively memorize long-term dependencies and filter noise through the synergistic effect of forgetting gates, input gates, and output gates, thereby achieving deep extraction of delay features. During the training process, the delay constraint model optimizes parameters through the backpropagation algorithm and ultimately outputs a dynamic delay tolerance that meets the current network status and service requirements. It takes into account the characteristics of time series data and integrates environmental status and service constraints, making the prediction results more accurate and reliable.

[0031] In step 103, a confidence adjustment is performed on the basic timeout threshold during the SMS sending process based on the delay tolerance to obtain a confidence judgment interval of the timeout threshold during the SMS sending process, and then the degradation characteristics of the communication channel timeout event during the SMS sending process are extracted from the response time information through the confidence judgment interval.

[0032] In some embodiments, confidence adjustment is performed on the basic timeout threshold during SMS sending based on the delay tolerance to obtain a confidence interval for the timeout threshold during SMS sending by using the following steps: Obtain the basic timeout threshold and dynamic adjustment coefficient during SMS sending; Determine the confidence adjustment parameter of the timeout threshold during SMS sending by using the dynamic adjustment coefficient and the delay tolerance; The basic timeout threshold is flexibly determined by using the confidence adjustment parameter to obtain a confidence determination interval of the timeout threshold during the text message sending process.

[0033] It should be noted that in this application, the confidence judgment interval represents the dynamic range of the timeout threshold, providing upper and lower bounds for the timeout judgment of SMS sending, the lower bound is used for timeout warning, and the upper bound is used for timeout judgment; the basic timeout threshold is the initial timeout judgment standard value preset in the SMS service platform, which is usually set according to business needs and historical data as a benchmark reference for timeout judgment; the dynamic adjustment coefficient is a parameter used to quantify the degree of influence of the current network environment on the timeout threshold. The dynamic adjustment coefficient is adjusted in real time according to the current network load status. The closer the value is to 1, the more stable the network environment is, and the smaller the adjustment range of the timeout threshold is; the confidence adjustment parameter represents the adjustment range of the timeout threshold, and the confidence adjustment parameter determines the degree of relaxation or tightening of the basic threshold.

[0034] In specific implementation, first, obtaining the basic timeout threshold and dynamic adjustment coefficient during the SMS sending process can be achieved in the following manner, namely: obtaining the basic timeout threshold and dynamic adjustment coefficient during the SMS sending process from the console of the SMS service platform, and the dynamic adjustment coefficient is a real number between 0.5 and 1; then, determining the confidence adjustment parameter of the timeout threshold during the SMS sending process through the dynamic adjustment coefficient and the delay tolerance can be achieved in the following manner, namely: taking the product of the dynamic adjustment coefficient and the delay tolerance as the confidence adjustment parameter of the timeout threshold during the SMS sending process; finally, elastically judging the basic timeout threshold through the confidence adjustment parameter, and obtaining the confidence judgment interval of the timeout threshold during the SMS sending process can be achieved in the following manner, namely: taking the product of the confidence adjustment parameter and the basic timeout threshold as the timeout adjustment amount, and thus taking the sum of the timeout adjustment amount and the basic timeout threshold as the benchmark adjustment value of the timeout threshold during the SMS sending process.

[0035] In step 104, the degradation characteristics of the timeout event and the historical delivery rate of SMS messages are input into an intelligent decision model for the quality of the communication channel, and a continuous timeout threshold of the communication channel during SMS sending is output. The number of continuous timeouts during SMS sending is monitored in real time, and the reliability of the communication channel quality is evaluated based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

[0036] In some embodiments, extracting the degradation characteristics of the communication channel timeout event during SMS sending from the response time information using the confidence interval can be achieved by using the following steps: For each SMS message sent within the preset time window, obtaining the response time of the SMS message sending from the response time information; If the response time exceeds the confidence interval, the SMS sending is recorded as a timeout event, completing the timeout judgment of the SMS sending; Then, the timeout judgment of each SMS message sent within the preset time window is completed, and multiple timeout events are obtained; The number of all timeout events is counted, and then the degradation characteristics of communication channel timeout events during SMS sending are calculated.

[0037] It should be noted that, in this application, the timeout frequency refers to the ratio of the number of timeout events occurring within the statistical period to the total number of transmissions, and the timeout frequency can reflect the reliability of the channel; in specific implementation, first, for each SMS transmission within the preset time window, the response time of the SMS transmission is obtained from the response time information; then, if the response time exceeds the range of the confidence judgment interval, the SMS transmission is recorded as a timeout event, and the timeout judgment of the SMS transmission is completed; then, the timeout judgment of each SMS transmission within the preset time window is completed, and multiple timeout events are obtained. This can be implemented in the following way, namely: the timeout judgment of each SMS transmission within the preset time window can be completed by the above method, and multiple timeout events after the timeout judgment can be obtained. The timeout event indicates that the response time of a single SMS transmission exceeds the upper limit of the confidence judgment interval. Record; finally, count the number of all timeout events, and then calculate the degradation characteristics of the communication channel timeout event during the SMS sending process. This can be implemented in the following way, namely: count the number of all timeout events, and take the ratio of the number of all timeout events to the total number of SMS transmissions as the degradation characteristics of the communication channel timeout event during the SMS sending process.

[0038] In some embodiments, the degradation characteristics of the timeout event and the historical delivery rate of SMS messages are input into an intelligent decision model for communication channel quality, and outputting a continuous timeout threshold for the communication channel during SMS sending can be achieved by the following steps: Initialize a communication intelligent decision model based on random forest decision tree as the intelligent decision model for communication channel quality; Using the degradation characteristics of the timeout event as real-time quality characteristics input into the intelligent decision model; The historical delivery rate of SMS messages is used as the historical stability feature input in the intelligent decision-making model; The intelligent decision model after feature input is used to evaluate the reliability status of the communication channel during the SMS sending process, and the continuous timeout threshold of the communication channel during the SMS sending process is obtained.

[0039] It should be noted that in this application, the continuous timeout threshold is the critical value used to determine whether a persistent fault occurs in the communication channel; the intelligent decision-making model is a communication intelligent decision-making model based on a random forest decision tree, which performs integrated learning by constructing multiple decision trees. The intelligent decision-making model receives two key inputs: real-time quality features (degradation features of timeout events) reflect the current channel status, and historical stability features (delivery rate) reflect the long-term performance. Each decision tree independently analyzes the nonlinear relationship between features and selects the optimal partitioning point through information gain. The random forest increases the difference between trees through self-service sampling (for example: bootstrap sampling). Finally, a voting mechanism is used to integrate the results of each decision tree and output a reliable continuous timeout threshold. This not only avoids the problem of overfitting of a single decision tree, but also accurately captures the complex relationship between communication quality and various features, and realizes dynamic and robust channel evaluation. Cross-validation is used to optimize parameters such as tree depth during model training to ensure good generalization ability in actual business.

[0040] It should be noted that, in this application, the number of consecutive timeouts refers to the cumulative number of times that the SMS sending response time exceeds the dynamic threshold continuously within the actual monitoring window; in specific implementation, the statistical method of timeout events in this application is used to count the number of consecutive SMS sending timeout events in real time as the number of consecutive timeouts in the SMS sending process.

[0041] In some embodiments, the reliability of the communication channel quality is evaluated based on the number of consecutive timeouts and the consecutive timeout threshold of the communication channel, referring to Figure 3 The figure is a schematic diagram of a process for implementing reliability evaluation in some embodiments of the present application. In this embodiment, reliability evaluation can be implemented using the following steps: In step 1041, a continuous timeout threshold of the communication channel is obtained; In step 1042, a communication delay characteristic in SMS sending is determined and calculated based on the number of consecutive timeouts and the consecutive timeout threshold; In step 1043, the communication channel quality in the text message sending is evaluated based on the communication delay characteristics.

[0042] In specific implementation, first, a continuous timeout threshold of the communication channel is obtained from the console of the SMS service platform; then, the communication delay feature in SMS sending is determined and calculated based on the number of continuous timeouts and the continuous timeout threshold, which can be implemented in the following manner: the ratio of the number of continuous timeouts to the continuous timeout threshold is used as the communication delay feature in SMS sending, and the communication delay feature is a feature that reflects the severity of channel transmission delay; finally, the quality of the communication channel in SMS sending is evaluated based on the communication delay feature, which can be implemented in the following manner: a mapping table of characteristic intervals of communication delay and channel quality levels is obtained from the console of the SMS service platform, the channel quality level corresponding to the characteristic interval of communication delay where the communication delay feature is located is obtained from the mapping table, and the channel quality level is used as the evaluation result of the communication channel quality in SMS sending.

[0043] It should be noted that the solution integrates real-time monitoring and trend prediction technologies. Through the three-stage processing of dynamic threshold triggering, multi-dimensional feature extraction and intelligent evaluation, it can not only meet the rapid response to sudden failures, but also identify potential quality degradation trends. The built-in self-checking mechanism of the SMS service platform can prevent misjudgment and ensure the accuracy of the evaluation results, complying with the regulatory requirements of telecommunications-grade service quality management. Data exchange between various layers is carried out through the message bus to ensure the efficiency and scalability of the processing process.

[0044] In addition, another aspect of the present application, in some embodiments, the present application provides a short message sending quality monitoring system based on machine learning, the short message sending quality monitoring system based on machine learning includes a channel quality evaluation unit, reference Figure 4 , which is a schematic diagram of the structure of a channel quality assessment unit according to some embodiments of the present application. The channel quality assessment unit includes: an acquisition module 201, a processing module 202, and an execution module 203, which are described as follows: The acquisition module 201 in this application is mainly used to collect the response time information from the sending end to the receiving end in the communication channel of the SMS sending request during the SMS sending process; Processing module 202, in this application, is used to extract delay fluctuation characteristics during SMS sending from the response time information within a preset time window, impose delay constraints on the SMS sending process based on the delay fluctuation characteristics, the network delay of the SMS sending environment, and a preset basic timeout threshold, and obtain a delay tolerance during SMS sending; It should be noted that the processing module 202 is further configured to perform confidence adjustment on a basic timeout threshold during SMS sending based on the delay tolerance to obtain a confidence interval for the timeout threshold during SMS sending, and then extract degradation characteristics of the communication channel timeout event during SMS sending from the response time information using the confidence interval. Execution module 203. In this application, execution module 203 is mainly used to input the degradation characteristics of the timeout event and the historical delivery rate of SMS sending into the intelligent decision-making model of the communication channel quality, output the continuous timeout threshold of the communication channel during SMS sending, monitor the number of continuous timeouts during SMS sending in real time, and perform reliability evaluation on the communication channel quality based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

[0045] The above describes in detail the examples of the SMS sending quality monitoring system and method based on machine learning provided by the embodiments of the present application. It can be understood that, in order to realize the above functions, the corresponding device includes hardware structures and / or software modules corresponding to the execution of each function. It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0046] In some embodiments, the present application also provides a computer device, which includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned SMS sending channel quality assessment method.

[0047] In some embodiments, reference Figure 5 The dotted line in the figure indicates that the unit or module is optional. The figure is a structural diagram of a computer device for implementing a method for evaluating the quality of a text message sending channel according to an embodiment of the present application. The method for evaluating the quality of a text message sending channel described in the above embodiment can be Figure 5 The computer device shown in the figure is implemented, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device can be a terminal device, a server or a chip.

[0048] The processor 301 may be a general-purpose processor or a dedicated processor. For example, the processor 301 may be a central processing unit (CPU), which may be used to control the computer device, execute software programs, and process data from the software programs. The computer device may also include a communication unit 305 for inputting (receiving) and outputting (transmitting) signals.

[0049] For example, the computer device may be a chip, the communication unit 305 may be an input and / or output circuit of the chip, or the communication unit 305 may be a communication interface of the chip, and the chip may be a component of a terminal device, a network device, or other device.

[0050] For another example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0051] The computer device may include one or more memories 302, on which a program 304 is stored. The program 304 can be executed by the processor 301 to generate instructions 303, so that the processor 301 executes the method described in the above method embodiment according to the instructions 303. Optionally, data (such as a target audit model) can also be stored in the memory 302. Optionally, the processor 301 can also read data stored in the memory 302. The data can be stored at the same storage address as the program 304, or at a different storage address from the program 304.

[0052] The processor 301 and the memory 302 may be provided separately or integrated together, for example, integrated on a system on chip (SOC) of a terminal device.

[0053] It should be understood that each step of the above method embodiment can be completed by a hardware-based logic circuit or software-based instructions in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0054] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0055] For example, in some embodiments, the present application also provides a computer-readable storage medium, which stores instructions or codes. When the instructions or codes are executed on a computer, the computer implements the above-mentioned SMS sending channel quality assessment method.

[0056] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0057] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for evaluating the quality of a text message sending channel, used in a text message sending quality monitoring system based on machine learning, characterized in that: The method comprises the following steps: During the SMS sending process, the response time information from the sending end to the receiving end in the communication channel of the SMS sending request is collected; Extracting delay fluctuation characteristics during SMS sending from the response time information within a preset time window, and applying delay constraints to the SMS sending process based on the delay fluctuation characteristics, the network delay of the SMS sending environment, and a preset basic timeout threshold to obtain a delay tolerance during SMS sending; Performing confidence adjustment on a basic timeout threshold during SMS sending based on the delay tolerance to obtain a confidence interval for the timeout threshold during SMS sending, and then extracting degradation characteristics of a communication channel timeout event during SMS sending from the response time information using the confidence interval; The degradation characteristics of the timeout event and the historical delivery rate of SMS messages are input into an intelligent decision-making model for the quality of the communication channel, and a continuous timeout threshold of the communication channel during the SMS sending process is output. The number of continuous timeouts during the SMS sending process is monitored in real time, and the reliability of the communication channel quality is evaluated based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

2. The method according to claim 1, wherein Extracting delay fluctuation characteristics during SMS sending from the response time information specifically includes: Obtaining the response time of all SMS messages sent within a preset time window from the response time information; Determine the moving average delay of SMS messages sent within a preset time window using all response times; The delay fluctuation characteristics during the text message sending process are calculated based on the moving average delay.

3. The method according to claim 1, wherein The confidence interval of the basic timeout threshold during SMS sending is adjusted based on the delay tolerance, and the confidence interval of the timeout threshold during SMS sending is obtained, which specifically includes: Obtain the basic timeout threshold and dynamic adjustment coefficient during SMS sending; Determine the confidence adjustment parameter of the timeout threshold during SMS sending by using the dynamic adjustment coefficient and the delay tolerance; The basic timeout threshold is flexibly determined by using the confidence adjustment parameter to obtain a confidence determination interval of the timeout threshold during the text message sending process.

4. The method according to claim 1, wherein Extracting the degradation characteristics of the communication channel timeout event during SMS sending from the response time information through the confidence interval specifically includes: For each SMS message sent within the preset time window, obtaining the response time of the SMS message sending from the response time information; If the response time exceeds the confidence interval, the SMS sending is recorded as a timeout event, completing the timeout judgment of the SMS sending; Then, the timeout judgment of each SMS message sent within the preset time window is completed, and multiple timeout events are obtained; The number of all timeout events is counted, and then the degradation characteristics of communication channel timeout events during SMS sending are calculated.

5. The method according to claim 1, wherein The reliability evaluation of the communication channel quality based on the number of consecutive timeouts and the consecutive timeout threshold of the communication channel specifically includes: Get the continuous timeout threshold of the communication channel; Determine and calculate the communication delay characteristics in SMS sending by the number of consecutive timeouts and the consecutive timeout threshold; The communication channel quality in text message sending is evaluated based on the communication delay characteristics.

6. The method according to claim 1, wherein The communication channel is a short message transmission link based on the operator's core network.

7. The method according to claim 1, wherein The intelligent decision-making model is a communication intelligent decision-making model based on a random forest decision tree.

8. A machine learning-based SMS sending quality monitoring system, comprising a channel quality assessment unit, characterized in that: The channel quality assessment unit includes: The acquisition module is used to collect the response time information from the sending end to the receiving end in the communication channel of the SMS sending request during the SMS sending process; a processing module, configured to extract delay fluctuation characteristics during SMS sending from the response time information within a preset time window, impose a delay constraint on the SMS sending process based on the delay fluctuation characteristics, the network delay of the SMS sending environment, and a preset basic timeout threshold, and obtain a delay tolerance during SMS sending; The processing module is further configured to perform confidence adjustment on a basic timeout threshold during SMS sending based on the delay tolerance to obtain a confidence interval for the timeout threshold during SMS sending, and then extract degradation characteristics of a communication channel timeout event during SMS sending from the response time information using the confidence interval. The execution module is used to input the degradation characteristics of the timeout event and the historical delivery rate of SMS messages into an intelligent decision-making model for the quality of the communication channel, output a continuous timeout threshold of the communication channel during the SMS sending process, monitor the number of continuous timeouts during the SMS sending process in real time, and perform a reliability assessment of the communication channel quality based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the SMS sending channel quality assessment method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions or codes, and when the instructions or codes are executed on a computer, the computer implements the method for evaluating the quality of a short message sending channel according to any one of claims 1 to 7.

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