Machine learning based short message transmission quality monitoring system and method

Abstract

The application provides a short message sending quality monitoring system and method based on machine learning. The delay tolerance in the short message sending process is obtained by performing delay constraint on the short message sending process through the delay fluctuation characteristics in the short message sending process, the network delay of the short message sending environment and the preset basic timeout threshold. The confidence adjustment of the basic timeout threshold in the short message sending is performed based on the delay tolerance, the confidence determination interval of the timeout threshold is obtained, and then the degradation characteristics of the communication channel timeout event in the short message sending process are extracted. The degradation characteristics of the timeout event and the historical delivery rate of the short message sending are input into the intelligent decision model of the communication channel quality, and the continuous timeout threshold of the communication channel in the short message sending process is output. The reliability of the communication channel quality is evaluated based on the continuous timeout times in the short message sending process and the continuous timeout threshold of the communication channel. The time sequence degradation evaluation of the channel quality under the short message sending timeout state can be realized based on the above scheme.

Description

Technical Field

[0001] This application relates to the field of communication quality assessment technology, and more specifically, to a machine learning-based SMS sending quality monitoring system and method. Background Technology

[0002] With the widespread adoption of mobile internet, SMS messaging has expanded beyond traditional text messages to include multimedia content such as images, audio, and video, creating rich media SMS. This type of SMS offers a richer and more engaging way to deliver information, meeting users' needs in various scenarios, including social interaction, business promotion, and public services. Furthermore, the security and privacy of SMS messaging have received increased attention. With the improvement of laws and regulations and technological advancements, SMS platforms have adopted stricter measures to protect user data and ensure information security, guaranteeing 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, relying on simple polling or random allocation strategies fails to dynamically detect instantaneous channel quality fluctuations, leading to continuous message distribution to degraded channels and exacerbating the risk of delivery failures. In the long term, focusing solely on instantaneous failures while ignoring the gradual degradation of channel performance and lacking trend-based assessments of channel health prevents SMS service platforms from proactively eliminating chronically degraded channels, ultimately impacting overall service reliability. This crude management approach reduces resource utilization and increases the pressure on maintenance personnel to respond passively. Therefore, how to achieve time-series degradation assessment of channel quality in SMS delivery timeout states, thereby improving the accuracy of SMS channel switching, has become a challenging problem for the industry. Summary of the Invention

[0004] This application provides a machine learning-based SMS sending quality monitoring system and method, which can realize the timing degradation assessment of channel quality under SMS sending timeout conditions.

[0005] Firstly, this application provides a method for evaluating the quality of SMS sending channels, used in a machine learning-based SMS sending quality monitoring system to evaluate the quality of SMS sending channels. The method includes:

[0006] During the SMS sending process, the response time information from the sender to the receiver in the communication channel of the SMS sending request is collected;

[0007] Within a preset time window, delay fluctuation characteristics during SMS sending are extracted from the response time information. The delay fluctuation characteristics, network latency of the SMS sending environment, and preset basic timeout threshold are used to constrain the delay of the SMS sending process, thereby obtaining the delay tolerance during SMS sending.

[0008] Based on the aforementioned delay tolerance, the confidence adjustment of the basic timeout threshold during SMS sending is performed to obtain the confidence judgment interval of the timeout threshold during SMS sending. Then, the degradation characteristics of communication channel timeout events during SMS sending are extracted from the response time information through the confidence judgment interval.

[0009] The degradation characteristics of the timeout events and the historical delivery rate of SMS messages are input into the intelligent decision-making model for communication channel quality. The model outputs the continuous timeout threshold of the communication channel during SMS sending, monitors the number of continuous timeouts during SMS sending in real time, and performs a reliability assessment of the communication channel quality based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

[0010] In some embodiments, extracting delay fluctuation features during SMS sending from the response time information specifically includes:

[0011] Obtain the response time of all SMS messages sent within the preset time window from the response time information;

[0012] The mobile average delay for SMS sending within a preset time window is determined by all response times;

[0013] The delay fluctuation characteristics during SMS sending are calculated based on the mobile average delay.

[0014] In some embodiments, the confidence adjustment of the basic timeout threshold during SMS transmission based on the delay tolerance to obtain the confidence judgment interval of the timeout threshold during SMS transmission specifically includes:

[0015] Obtain the basic timeout threshold and dynamic adjustment coefficient during the SMS sending process;

[0016] The confidence adjustment parameters for the timeout threshold during SMS sending are determined by the dynamic adjustment coefficient and the delay tolerance.

[0017] The confidence adjustment parameter is used to flexibly determine the basic timeout threshold, thereby obtaining the confidence determination range of the timeout threshold during SMS sending.

[0018] In some embodiments, extracting degradation features of communication channel timeout events during SMS sending from the response time information through the confidence interval specifically includes:

[0019] For each SMS message sent within a preset time window, the response time of the SMS message is obtained from the response time information;

[0020] If the response time exceeds the confidence interval, the SMS sending is recorded as a timeout event, and the timeout judgment for SMS sending is completed.

[0021] This allows for timeout checks on each SMS message sent within a preset time window, resulting in multiple timeout events.

[0022] The number of all timeout events is counted, and then the degradation characteristics of communication channel timeout events during SMS sending are calculated.

[0023] In some embodiments, the reliability assessment of the communication channel quality based on the number of consecutive timeouts and the consecutive timeout threshold of the communication channel specifically includes:

[0024] Obtain the continuous timeout threshold of the communication channel;

[0025] The communication delay characteristics in SMS sending are determined by the number of consecutive timeouts and the consecutive timeout threshold.

[0026] The communication channel quality in SMS sending is evaluated based on the aforementioned communication delay characteristics.

[0027] In some embodiments, the communication channel is a short message transmission link based on the operator's core network.

[0028] In some embodiments, the intelligent decision-making model is a communication intelligent decision-making model based on random forest decision trees.

[0029] Secondly, this application provides a machine learning-based SMS sending quality monitoring system, including a channel quality assessment unit, the channel quality assessment unit comprising:

[0030] The data acquisition module is used to collect response time information from the sender to the receiver in the communication channel of the SMS sending request during the SMS sending process.

[0031] The processing module is used to extract the delay fluctuation characteristics of the SMS sending process from the response time information within a preset time window, and to impose delay constraints on the SMS sending process through the delay fluctuation characteristics, the network latency of the SMS sending environment and a preset basic timeout threshold to obtain the delay tolerance of the SMS sending process.

[0032] The processing module is also used to perform confidence adjustment on the basic timeout threshold during SMS sending based on the delay tolerance, to obtain the confidence judgment interval of the timeout threshold during SMS sending, and then extract the degradation characteristics of the communication channel timeout event during SMS sending from the response time information through the confidence judgment interval.

[0033] The execution module is used to input the degradation characteristics of the timeout event and the historical delivery rate of SMS messages into the intelligent decision model of 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 a reliability assessment of the communication channel quality based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

[0034] Thirdly, this application provides a computer device, the computer device including a memory and a processor, the memory for storing a computer program, and the processor for calling and running the computer program from the memory, so that the computer device performs the above-described SMS sending channel quality assessment method.

[0035] Fourthly, this application provides a computer-readable storage medium storing instructions or code that, when executed on a computer, cause the computer to implement the aforementioned SMS sending channel quality assessment method.

[0036] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0037] This application provides a machine learning-based SMS sending quality monitoring system and method. During SMS sending, the system collects response time information from the sender to the receiver in the communication channel of the SMS sending request. Within a preset time window, it extracts latency fluctuation characteristics from the response time information. The system then constrains the SMS sending process based on these latency fluctuation characteristics, network latency in the SMS sending environment, and a preset basic timeout threshold, obtaining a latency tolerance. Based on this latency tolerance, it adjusts the confidence level of the basic timeout threshold to obtain a confidence interval for the timeout threshold. The system then extracts degradation characteristics of communication channel timeout events from the response time information using this confidence interval. Finally, it inputs the degradation characteristics of the timeout events and the historical delivery rate of SMS sending into an intelligent decision-making model for communication channel quality, outputting a continuous timeout threshold for the communication channel during SMS sending. The system monitors the number of consecutive timeouts in real time and performs a reliability assessment of the communication channel quality based on the number of consecutive timeouts and the continuous timeout threshold.

[0038] Therefore, this application monitors the number of consecutive timeouts during SMS sending in real time, and assesses the reliability of the communication channel quality based on the number of consecutive timeouts and the consecutive timeout threshold of the communication channel. First, by determining the latency tolerance, an adaptively adjustable latency constraint standard can be obtained, enabling the SMS service platform to more accurately distinguish between normal fluctuations and abnormal degradation. Traditional solutions rely on fixed timeout thresholds, which cannot adapt to dynamic changes in different network environments (such as congestion and cross-carrier transmission), leading to misjudgments or missed judgments. Adjusting the tolerance based on real-time latency fluctuation characteristics allows for appropriate relaxation of the threshold in high-latency environments, avoiding accidental channel switching due to brief jitter. In low-latency but high-fluctuation scenarios, the constraint is tightened to detect potential degradation in advance. This approach significantly improves the accuracy of timeout event identification. Then, by determining the degradation characteristics of timeout events, the temporal pattern of channel degradation can be obtained, enabling fine-grained modeling of channel quality degradation. Traditional methods only count the number of timeouts, ignoring the distribution characteristics over time, leading to lagging switching strategies. However, by filtering high-confidence timeout events through confidence intervals and combining historical delivery rates to analyze degradation trends, the evaluation model can distinguish between occasional failures and persistent degradation, thereby enhancing the temporal sensitivity of channel quality assessment and improving the switching accuracy of SMS sending channels under timeout conditions. In summary, based on the above scheme, the temporal degradation assessment of channel quality under SMS sending timeout conditions can be achieved, thus improving the switching accuracy of SMS sending channels. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is an exemplary flowchart of a method for evaluating the quality of SMS sending channels according to some embodiments of this application;

[0041] Figure 2 This is an application scenario diagram of SMS sending shown in some embodiments of this application;

[0042] Figure 3 This is a flowchart illustrating the process of implementing reliability assessment according to some embodiments of this application;

[0043] Figure 4 This is a schematic diagram of the structure of a channel quality assessment unit according to some embodiments of this application;

[0044] Figure 5This is a schematic diagram of the structure of a computer device that implements a method for evaluating the quality of SMS sending channels according to some embodiments of this application. Detailed Implementation

[0045] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0046] refer to Figure 1 The figure is an exemplary flowchart of a method for evaluating the quality of an SMS sending channel according to some embodiments of this application. The method for evaluating the quality of an SMS sending channel mainly includes the following steps:

[0047] In step 101, 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.

[0048] It should be noted that, in this application, response time information refers to the time data elapsed 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.

[0049] In practice, 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 month). The collection of all response times is then used as the response time information from the sender to the receiver in the communication channel.

[0050] In some embodiments, reference Figure 2 The diagram illustrates an application scenario for SMS sending according to some embodiments of this application. It shows a typical SMS sending and receiving scenario. Device 1 on the left represents the SMS sender, which wirelessly transmits the SMS content to a cloud service (3 in the diagram), typically an SMS gateway or SMS center. The cloud service processes and forwards the SMS, then wirelessly transmits it to the recipient's network area (multiple concentric circles around device 2 in the diagram represent different signal coverage areas). Device 2, being within the signal coverage area, is able to receive the SMS from the sender. The entire process demonstrates the complete path of an SMS from sending to receiving, including relaying and distribution via the cloud service.

[0051] In step 102, within a preset time window, the delay fluctuation characteristics during the SMS sending process are extracted from the response time information. The delay fluctuation characteristics, the network latency of the SMS sending environment, and the preset basic timeout threshold are used to constrain the delay of the SMS sending process, thereby obtaining the delay tolerance during the SMS sending process.

[0052] It should be noted that in this application, the preset time window refers to a fixed duration interval set by the system (the default is 5 minutes). This 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.

[0053] In some embodiments, extracting delay fluctuation characteristics during SMS sending from the response time information can be achieved using the following steps:

[0054] Obtain the response time of all SMS messages sent within the preset time window from the response time information;

[0055] The mobile average delay for SMS sending within a preset time window is determined by all response times;

[0056] The delay fluctuation characteristics during SMS sending are calculated based on the mobile average delay.

[0057] It should be noted that, in this application, the latency fluctuation feature is used to quantify the degree to which the response time deviates from the average value. This latency fluctuation feature can characterize the stability of network transmission during SMS sending. The moving average latency refers to the arithmetic mean of the response times of all SMS sending within a specific time window. This moving average latency can reflect the overall transmission efficiency within that time window.

[0058] In specific implementation, firstly, obtaining the response time of all SMS messages sent within the preset time window from the response time information can be achieved by: obtaining the response time of SMS messages sent within the preset time window from the response time information, thus obtaining the response time of all SMS messages sent within the preset time window; then, determining the moving average delay of SMS messages sent within the preset time window based on all response times can be achieved by: using the average of all response times as the moving average delay of SMS messages sent within the preset time window; finally, calculating the delay fluctuation characteristics during SMS sending based on the moving average delay can be achieved by: using the standard deviation of the response times of all SMS messages sent within the preset time window calculated using the moving average delay as the delay fluctuation characteristics during SMS sending.

[0059] In some embodiments, the latency constraint on the SMS sending process based on the latency fluctuation characteristics, the network latency of the SMS sending environment, and a preset basic timeout threshold, to obtain the latency tolerance in the SMS sending process, can be achieved through the following steps:

[0060] Initialize a time delay regression model based on a long short-term memory network as a time delay constraint model;

[0061] The delay fluctuation characteristics are used as time-series feature inputs in the time-delay constraint model;

[0062] The network latency of the SMS sending environment is used as the environmental state feature input in the latency constraint model;

[0063] The preset basic timeout threshold is used as the baseline constraint feature input in the delay constraint model;

[0064] The latency constraint model, based on the input features, dynamically predicts the latency of SMS sending and outputs the latency tolerance during SMS sending.

[0065] It should be noted that in this application, latency tolerance is an indicator reflecting the acceptable level of timeout under current network conditions; the latency constraint model is a mathematical model based on a long short-term memory network. This latency constraint model is a specially designed time-series regression model based on a long short-term memory network in the SMS service platform. It learns the dynamic change law of SMS sending latency through memory units and gating mechanisms. This latency constraint model receives three dimensions of input features: time-series features (latency fluctuations) to capture the changing trend of response time, environmental state features (network latency) to reflect the current network condition, and baseline constraint features (basic timeout threshold) to provide a business benchmark. The long short-term memory network can effectively remember long-term dependencies and filter noise through the synergistic effect of forget gates, input gates, and output gates, thereby achieving deep extraction of latency features. During the training process, the latency constraint model optimizes parameters through the backpropagation algorithm and finally outputs a dynamic latency tolerance that conforms to the current network condition and business requirements. It considers the characteristics of time-series data and integrates environmental state and business constraints, making the prediction results more accurate and reliable.

[0066] In step 103, the confidence adjustment of the basic timeout threshold during SMS sending is performed based on the delay tolerance to obtain the confidence judgment interval of the timeout threshold during SMS sending. Then, the degradation characteristics of communication channel timeout events during SMS sending are extracted from the response time information through the confidence judgment interval.

[0067] In some embodiments, the confidence adjustment of the basic timeout threshold during SMS transmission based on the delay tolerance to obtain the confidence judgment interval of the timeout threshold during SMS transmission can be achieved by the following steps:

[0068] Obtain the basic timeout threshold and dynamic adjustment coefficient during the SMS sending process;

[0069] The confidence adjustment parameters for the timeout threshold during SMS sending are determined by the dynamic adjustment coefficient and the delay tolerance.

[0070] The confidence adjustment parameter is used to flexibly determine the basic timeout threshold, thereby obtaining the confidence determination range of the timeout threshold during SMS sending.

[0071] 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 warnings, and the upper bound is used for timeout judgment. The basic timeout threshold is the preset initial timeout judgment standard value in the SMS service platform, which is usually set according to business needs and historical data, and serves 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. This confidence adjustment parameter determines the degree of relaxation or tightening of the basic threshold.

[0072] In specific implementation, firstly, obtaining the basic timeout threshold and dynamic adjustment coefficient during SMS sending can be achieved as follows: The basic timeout threshold and dynamic adjustment coefficient during SMS sending can be obtained from the console of the SMS service platform. The dynamic adjustment coefficient is a real number between 0.5 and 1. Then, determining the confidence adjustment parameter of the timeout threshold during SMS sending using the dynamic adjustment coefficient and the delay tolerance can be achieved as follows: The product of the dynamic adjustment coefficient and the delay tolerance can be used as the confidence adjustment parameter of the timeout threshold during SMS sending. Finally, flexibly judging the basic timeout threshold using the confidence adjustment parameter to obtain the confidence judgment interval of the timeout threshold during SMS sending can be achieved as follows: The product of the confidence adjustment parameter and the basic timeout threshold can be used as the timeout adjustment amount, and the sum of the timeout adjustment amount and the basic timeout threshold can be used as the baseline adjustment value of the timeout threshold during SMS sending.

[0073] In step 104, the degradation characteristics of the timeout event and the historical delivery rate of SMS messages are input into the intelligent decision-making model for communication channel quality, and the 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.

[0074] In some embodiments, extracting the degradation characteristics of communication channel timeout events during SMS sending from the response time information through the confidence determination interval can be achieved using the following steps:

[0075] For each SMS message sent within a preset time window, the response time of the SMS message is obtained from the response time information;

[0076] If the response time exceeds the confidence interval, the SMS sending is recorded as a timeout event, and the timeout judgment for SMS sending is completed.

[0077] This allows for timeout checks on each SMS message sent within a preset time window, resulting in multiple timeout events.

[0078] The number of all timeout events is counted, and then the degradation characteristics of communication channel timeout events during SMS sending are calculated.

[0079] It should be noted that, in this application, the timeout frequency refers to the proportion of timeout events occurring within a statistical period to the total number of transmissions. This timeout frequency reflects the reliability of the channel. Specifically, firstly, for each SMS transmission within a 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, completing the timeout judgment for SMS transmission. Then, the timeout judgment for each SMS transmission within the preset time window is completed, and multiple timeout events are obtained. This can be achieved by: completing the timeout judgment for each SMS transmission within the preset time window using the above method, thus obtaining multiple timeout events after the timeout judgment. Each timeout event represents a record of a single SMS transmission response time exceeding the upper limit of the confidence judgment interval. Finally, the number of all timeout events is counted, and the degradation characteristics of communication channel timeout events during SMS transmission are calculated. This can be achieved by: counting the number of all timeout events, and using the ratio of the number of all timeout events to the total number of SMS transmissions as the degradation characteristics of communication channel timeout events during SMS transmission.

[0080] In some embodiments, the degradation characteristics of the timeout event and the historical delivery rate of SMS messages are input into an intelligent decision-making model for communication channel quality, and the continuous timeout threshold of the communication channel during SMS sending is output using the following steps:

[0081] Initialize a communication intelligent decision model based on random forest decision trees as an intelligent decision model for communication channel quality;

[0082] The degradation characteristics of the timeout event are used as inputs to the real-time quality characteristics in the intelligent decision-making model;

[0083] Use the historical delivery rate of SMS messages as the input of historical stability features in the intelligent decision-making model;

[0084] The intelligent decision-making model, after using feature input, evaluates the reliability status of the communication channel during SMS sending and obtains the continuous timeout threshold of the communication channel during SMS sending.

[0085] It should be noted that in this application, the continuous timeout threshold is a critical value used to determine whether a communication channel has experienced a persistent failure. The intelligent decision-making model is a communication intelligent decision-making model based on random forest decision trees. By constructing multiple decision trees for ensemble learning, this intelligent decision-making model receives two key inputs: real-time quality features (deterioration features of timeout events) reflecting the current channel status, and historical stability features (delivery rate) reflecting long-term performance. Each decision tree independently analyzes the nonlinear relationship between features, selects the optimal split point through information gain, and increases the difference between trees through bootstrap sampling (e.g., bootstrap sampling) in the random forest. Finally, a voting mechanism is used to synthesize the results of each decision tree and output a reliable continuous timeout threshold. This avoids the problem of overfitting of a single decision tree and accurately captures the complex relationship between communication quality and various features, achieving dynamic and robust channel evaluation. During model training, cross-validation is used to optimize parameters such as tree depth to ensure good generalization ability in actual business.

[0086] It should be noted that, in this application, the number of consecutive timeouts refers to the cumulative number of times the SMS sending response time exceeds the dynamic threshold consecutively 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 timeout events in SMS sending in real time as the number of consecutive timeouts in the SMS sending process.

[0087] In some embodiments, the reliability of the communication channel quality is assessed based on the number of consecutive timeouts and the consecutive timeout threshold of the communication channel, with reference to... Figure 3 The figure is a schematic diagram of the process for implementing reliability assessment in some embodiments of this application. The reliability assessment in this embodiment can be implemented by the following steps:

[0088] In step 1041, the continuous timeout threshold of the communication channel is obtained;

[0089] In step 1042, the communication delay characteristics in SMS sending are determined by the number of consecutive timeouts and the consecutive timeout threshold;

[0090] In step 1043, the communication channel quality in SMS sending is evaluated based on the communication delay characteristics.

[0091] In specific implementation, firstly, the continuous timeout threshold of the communication channel is obtained from the console of the SMS service platform; then, the communication delay characteristics in SMS sending can be determined by the ratio of the continuous timeout count to the continuous timeout threshold as the communication delay characteristic in SMS sending, which reflects the severity of channel transmission delay; finally, the communication channel quality in SMS sending can be evaluated based on the communication delay characteristics as follows: a mapping table of communication delay characteristic intervals and channel quality levels is obtained from the console of the SMS service platform, the channel quality level corresponding to the communication delay characteristic interval 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.

[0092] It should be noted that the solution integrates real-time monitoring and trend prediction technologies. Through a three-stage process of dynamic threshold triggering, multi-dimensional feature extraction, and intelligent evaluation, it not only meets the requirements for rapid response to sudden failures but also identifies potential quality degradation trends. The self-verification mechanism built into the SMS service platform can prevent misjudgments and ensure the accuracy of evaluation results, which meets the requirements of telecommunications-grade service quality management standards. Data interaction between various levels is carried out through a message bus to ensure the efficiency and scalability of the processing flow.

[0093] Furthermore, in another aspect of this application, in some embodiments, this application provides a machine learning-based SMS sending quality monitoring system, which includes a channel quality assessment unit, referencing... Figure 4 The figure is a schematic diagram of the structure of a channel quality assessment unit according to some embodiments of this application. The channel quality assessment unit includes: an acquisition module 201, a processing module 202, and an execution module 203, which are described below:

[0094] The acquisition module 201 in this application is mainly used to acquire the response time information from the sender to the receiver in the communication channel of the SMS sending request during the SMS sending process.

[0095] Processing module 202, in this application, is used to extract the delay fluctuation characteristics of the SMS sending process from the response time information within a preset time window, and to impose time delay constraints on the SMS sending process through the delay fluctuation characteristics, the network latency of the SMS sending environment and a preset basic timeout threshold, so as to obtain the time delay tolerance of the SMS sending process.

[0096] It should be noted that the processing module 202 is also used to perform confidence adjustment on the basic timeout threshold in the SMS sending process based on the delay tolerance, to obtain the confidence judgment interval of the timeout threshold in the SMS sending process, and then extract the degradation characteristics of the communication channel timeout event in the SMS sending process from the response time information through the confidence judgment interval.

[0097] The execution module 203 in this application is mainly used to input the degradation characteristics of the timeout event and the historical delivery rate of SMS sending into the intelligent decision model of 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 a reliability assessment of the communication channel quality based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

[0098] The foregoing has detailed examples of a machine learning-based SMS sending quality monitoring system and method provided in the embodiments of this application. It is understood that the corresponding apparatus, in order to achieve the above functions, includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0099] In some embodiments, this application also provides a computer device, the computer device including a memory and a processor, the memory for storing a computer program, and the processor for calling and running the computer program from the memory, so that the computer device performs the above-described SMS sending channel quality assessment method.

[0100] In some embodiments, reference Figure 5 The dashed lines in the figure indicate that the unit or module is optional. This figure is a schematic diagram of the structure of a computer device implementing a text message sending channel quality assessment method according to an embodiment of this application. The text message sending channel quality assessment method described in the above embodiments can... Figure 5 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device may be a terminal device, a server or a chip.

[0101] Processor 301 can be a general-purpose processor or a special-purpose processor. For example, processor 301 can be a central processing unit (CPU), which can be used to control computer devices, execute software programs, and process data from software programs. The computer device may also include a communication unit 305 for inputting (receiving) and outputting (transmitting) signals.

[0102] For example, the computer device may be a chip, and the communication unit 305 may be the input and / or output circuit of the chip, or the communication unit 305 may be the communication interface of the chip, which may be a component of a terminal device, network device or other device.

[0103] For 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.

[0104] The computer device may include one or more memories 302 storing a program 304. The program 304 can be executed by a processor 301 to generate instructions 303, causing the processor 301 to execute the method described in the above method embodiments according to the instructions 303. Optionally, the memory 302 may also store data (such as a target audit model). Optionally, the processor 301 may also read data stored in the memory 302, which may be stored at the same storage address as the program 304, or it may be stored at a different storage address than the program 304.

[0105] The processor 301 and memory 302 can be configured separately or integrated together, for example, integrated on the system on chip (SOC) of the terminal device.

[0106] It should be understood that each step of the above method embodiment can be completed by hardware logic circuits or software 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 gate, transistor logic devices, or discrete hardware components.

[0107] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] For example, in some embodiments, this application also provides a computer-readable storage medium storing instructions or code that, when executed on a computer, cause the computer to implement the above-described SMS sending channel quality assessment method.

[0109] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0110] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for evaluating the quality of SMS sending channels, used in a machine learning-based SMS sending quality monitoring system to evaluate the quality of SMS sending channels, characterized in that, Includes the following steps: During the SMS sending process, the response time information from the sender to the receiver in the communication channel of the SMS sending request is collected; Within a preset time window, delay fluctuation characteristics during SMS sending are extracted from the response time information. The delay fluctuation characteristics, network latency of the SMS sending environment, and preset basic timeout threshold are used to constrain the delay of SMS sending process, thereby obtaining the delay tolerance during SMS sending. The preset time window refers to a fixed time interval set by the system. This preset time window can be used to divide and analyze SMS sending in different time periods, and different time windows are set for different time points. Based on the aforementioned delay tolerance, the confidence adjustment of the basic timeout threshold during SMS sending is performed to obtain the confidence judgment interval of the timeout threshold during SMS sending. Then, the degradation characteristics of communication channel timeout events during SMS sending are extracted from the response time information through the confidence judgment interval. The degradation characteristics of the timeout events and the historical delivery rate of SMS messages are input into the intelligent decision-making model for communication channel quality. The model outputs the continuous timeout threshold of the communication channel during SMS sending, monitors the number of continuous timeouts during SMS sending in real time, and performs a reliability assessment of the communication channel quality based on the number of continuous timeouts and the continuous timeout threshold of the communication channel.

2. The method as described in claim 1, characterized in that, Extracting latency fluctuation features during SMS sending from the response time information specifically includes: Obtain the response time of all SMS messages sent within the preset time window from the response time information; The mobile average delay for SMS sending within a preset time window is determined by all response times; The delay fluctuation characteristics during SMS sending are calculated based on the mobile average delay.

3. The method as described in claim 1, characterized in that, Based on the aforementioned delay tolerance, the confidence adjustment of the basic timeout threshold during SMS transmission is performed to obtain the confidence judgment interval of the timeout threshold during SMS transmission, specifically including: Obtain the basic timeout threshold and dynamic adjustment coefficient during the SMS sending process; The confidence adjustment parameters for the timeout threshold during SMS sending are determined by the dynamic adjustment coefficient and the delay tolerance. The confidence adjustment parameter is used to flexibly determine the basic timeout threshold, thereby obtaining the confidence determination range of the timeout threshold during SMS sending.

4. The method as described in claim 1, characterized in that, Extracting the degradation features of communication channel timeout events during SMS sending from the response time information through the confidence interval specifically includes: For each SMS message sent within a preset time window, the response time of the SMS message is obtained from the response time information; If the response time exceeds the confidence interval, the SMS sending is recorded as a timeout event, and the timeout judgment for SMS sending is completed. This allows for timeout checks on each SMS message sent within a preset time window, resulting in multiple timeout events. 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 as described in claim 1, characterized in that, The reliability assessment of the communication channel quality based on the number of consecutive timeouts and the consecutive timeout threshold of the communication channel specifically includes: Obtain the continuous timeout threshold of the communication channel; The communication delay characteristics in SMS sending are determined by the number of consecutive timeouts and the consecutive timeout threshold. The communication channel quality in SMS sending is evaluated based on the aforementioned communication delay characteristics.

6. The method as described in claim 1, characterized in that, The communication channel is a text message transmission link based on the operator's core network.

7. The method as described in claim 1, characterized in that, The intelligent decision-making model is a communication intelligent decision-making model based on random forest decision trees.

8. A machine learning-based SMS sending quality monitoring system, comprising a channel quality assessment unit, which performs SMS sending channel quality assessment using the method described in any one of claims 1 to 7, characterized in that, The channel quality assessment unit includes: The data acquisition module is used to collect response time information from the sender to the receiver in the communication channel of the SMS sending request during the SMS sending process. The processing module is used to extract the delay fluctuation characteristics of the SMS sending process from the response time information within a preset time window, and to impose delay constraints on the SMS sending process through the delay fluctuation characteristics, the network latency of the SMS sending environment and a preset basic timeout threshold to obtain the delay tolerance of the SMS sending process. The processing module is also used to perform confidence adjustment on the basic timeout threshold during SMS sending based on the delay tolerance, to obtain the confidence judgment interval of the timeout threshold during SMS sending, and then extract the degradation characteristics of the communication channel timeout event during SMS sending from the response time information through the confidence judgment interval. The execution module is used to input the degradation characteristics of the timeout event and the historical delivery rate of SMS messages into the intelligent decision model of 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 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 computer programs, and the processor is used to call and run the computer programs from the memory, so that the computer device performs 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 code that, when executed on a computer, cause the computer to implement the SMS sending channel quality assessment method as described in any one of claims 1 to 7.

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