Networking failure root cause positioning method and device, electronic equipment and readable storage medium

Abstract

The invention provides a networking failure root cause positioning method and device, electronic equipment and a readable storage medium, and relates to the technical field of communication. The method comprises the following steps: evaluating the confidence of a signal based on the intensity values of multiple scanning signals; capturing an error code returned by the equipment in the process of trying to connect the network; inputting the confidence coefficient of the signal and the error code into a preset failure reason diagnosis model, mapping to obtain a standardized failure reason label, and realizing networking failure root cause positioning; the wireless signal intensity is collected for multiple times, the confidence coefficient of the wireless signal intensity is calculated, error codes are combined, networking failure root causes are accurately positioned, the defect that only general error prompts can be provided in a traditional scheme is overcome, automatic and explainable diagnosis of various faults from weak signals and frequency band incompatibility to password errors and DHCP failure is achieved, blind trial and error of a user are remarkably reduced, and the user experience is improved. And the connection success rate and the after-sales processing efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a method, apparatus, electronic device, and readable storage medium for locating the root cause of network failure. Background Technology

[0002] In existing technologies, smart devices (such as IoT terminals and Wi-Fi modules) often experience connection failures during network configuration or restoration due to issues like weak signal, frequency band incompatibility, incorrect passwords, and DHCP allocation failures. Current industry-standard solutions only provide general error messages like "connection timeout" or "incorrect password," failing to pinpoint the root cause of the failure. Users are forced to resolve these issues through repeated trial and error or manual troubleshooting, leading to a poor user experience and increased after-sales maintenance costs. Existing methods lack a systematic evaluation mechanism for network signal quality. For example, relying solely on a single RSSI (Received Signal Strength Indication) measurement to determine signal strength is often inaccurate and lacks joint analysis with error codes returned by the device, making it difficult to automate and explain the root cause of failures, resulting in a poor user experience. Summary of the Invention

[0003] The purpose of this invention is to provide a method, apparatus, electronic device, and readable storage medium for locating the root cause of network failures. By repeatedly collecting wireless signal strength data and calculating its confidence level, combined with the error codes returned by the device, a rule engine is used to accurately locate the root cause of network failures. This method overcomes the shortcomings of traditional solutions that only provide general error messages, achieving automatic and interpretable diagnosis of various faults from "weak signal" and "frequency band incompatibility" to "incorrect password" and "DHCP failure." This significantly reduces users' blind trial and error, improving connection success rates and after-sales processing efficiency.

[0004] In a first aspect, the present invention provides a method for locating the root cause of network failure, comprising: Scan the signals of wireless access points in the current environment and collect signal strength values ​​multiple times; The confidence level of the signal is evaluated based on the strength values ​​of multiple signals. Capture error codes returned by the device during its network connection attempt; The confidence level and error code of the signal are input into a preset failure cause diagnosis model, and a standardized failure cause label is obtained by mapping, so as to realize the root cause location of network failure. Generate repair prompts based on the failure reason tags.

[0005] In some preferred embodiments of the present invention, the step of evaluating the confidence level of a signal based on multiple signal strength values ​​includes: Calculate the standard deviation of the signal intensity values ​​over multiple tests; The confidence level of the signal is determined based on the standard deviation and the preset confidence interval.

[0006] In some preferred embodiments of the present invention, the step of determining the confidence level of a signal based on the standard deviation and a preset confidence interval includes: Determine whether the standard deviation is within the confidence interval; If so, the confidence level of the signal is assigned the preset maximum value; If not, the confidence level is determined by the distance between the standard deviation and the endpoints of any confidence interval.

[0007] In some preferred embodiments of the present invention, the error code includes at least one of the following: management frame or control frame return codes from standard protocols commonly used in wireless local area networks, dynamic host configuration protocol status codes, and transmission control protocol connection phase status codes.

[0008] In some preferred embodiments of the present invention, the failure cause diagnosis model defines a mapping relationship between various condition combinations and failure cause labels; the step of inputting the confidence level and error code of the signal into the preset failure cause diagnosis model and mapping to obtain standardized failure cause labels includes: After combining the confidence level of the signal with the error code, the failure reason label is determined based on the mapping relationship.

[0009] In some preferred embodiments of the present invention, the mapping relationship includes: When the error code indicates a password error, it is mapped to a password error label; When the error code indicates that the wireless network frequency band is 5GHz and the confidence level of the signal is lower than the first threshold, the frequency band does not support the tag. When the error code indicates a failure to allocate a Dynamic Host Configuration Protocol (DHCP) service, it is mapped to the DHCP service exception label.

[0010] In some preferred embodiments of the present invention, the method further includes: Upload the anonymized failure reason labels, signal confidence levels, and error codes to the cloud server; The cloud server performs cluster analysis on the collected data and optimizes and updates the failure cause diagnosis model based on the analysis results.

[0011] In a second aspect, the present invention provides a network failure root cause location device, comprising: The network signal strength acquisition module is used to scan the signals of wireless access points in the current environment and collect signal strength values ​​multiple times. The signal confidence processing module is used to evaluate the confidence of a signal based on the intensity values ​​of multiple signals. The error code determination module is used to capture error codes returned by the device during the network connection attempt process; The network failure root cause localization module is used to input the confidence level of the signal and the error code into a preset failure cause diagnosis model, and map them to obtain standardized failure cause labels to realize network failure root cause localization. The repair suggestion module is used to generate repair prompts based on the failure reason tags.

[0012] Thirdly, the present invention provides an electronic device including a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the network failure root cause localization method provided in the first aspect above.

[0013] Fourthly, the present invention provides a readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the network failure root cause localization method provided in the first aspect.

[0014] This invention brings the following beneficial effects: This invention provides a method, apparatus, electronic device, and readable storage medium for locating the root cause of network failures. The method includes: scanning the signals of wireless access points in the current environment and collecting multiple signal strength values; evaluating the confidence level of the signal based on the multiple signal strength values; capturing error codes returned by the device during network connection attempts; inputting the signal confidence level and error codes into a preset failure cause diagnosis model to map them into standardized failure cause labels, thereby achieving root cause location of network failures; generating repair prompts based on the failure cause labels; and accurately locating the root cause of network failures using a rule engine by repeatedly collecting wireless signal strength and calculating its confidence level, combined with the error codes returned by the device. This method overcomes the shortcomings of traditional solutions that only provide general error messages, achieving automatic and interpretable diagnosis of various faults from "weak signal" and "frequency band incompatibility" to "password error" and "DHCP failure," significantly reducing users' blind trial and error and improving connection success rate and after-sales processing efficiency. Attached Figure Description

[0015] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0016] Figure 1 A flowchart of a network failure root cause localization method provided in an embodiment of the present invention; Figure 2This is a schematic diagram of the structure of a network failure root cause localization device provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0017] Icons: 310 - Network signal strength acquisition module; 320 - Signal confidence processing module; 330 - Error code determination module; 340 - Network failure root cause location module; 350 - Repair suggestion module; 400 - Memory; 401 - Processor; 402 - Bus; 403 - Communication interface. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0019] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0020] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0021] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. In addition, the terms "first," "second," "third," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0022] Furthermore, terms such as "horizontal," "vertical," and "sag" do not imply that components must be absolutely horizontal or suspended, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal relative to "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0023] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0024] The following detailed description of some embodiments of the present invention is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0025] Example 1 This invention provides a method for locating the root cause of network failures, see [link to relevant documentation]. Figure 1 The flowchart shown in this embodiment of the invention provides a method for locating the root cause of network failure, the method comprising: Step S102: Scan the signals of wireless access points in the current environment and collect signal strength values ​​multiple times.

[0026] Specifically, when a smart device (such as an IoT terminal or Wi-Fi module) initiates the network configuration or connection process, it first scans the wireless access points (APs) in the current environment using its wireless network module (such as a Wi-Fi chip). For the target SSID specified by the user or that the device attempts to connect to, the Received Signal Strength Indication (RSSI) value is collected multiple times (e.g., n=5-10 times) continuously or at intervals. This step aims to obtain a set of signal strength samples, laying the foundation for subsequent stability analysis and overcoming the shortcomings of high randomness and inaccuracy in single measurements.

[0027] Step S104: Evaluate the confidence level of the signal based on the intensity values ​​of multiple signals.

[0028] Specifically, based on multiple collected RSSI values, a comprehensive signal quality confidence score S is calculated. This confidence score S is used to quantify the reliability and stability of the current signal strength. In a basic implementation, the arithmetic mean of this set of RSSI values ​​can be directly calculated, and this mean can be mapped to a preset score range (such as 0-100) as the confidence score S. Its core purpose is to provide a relatively reliable signal quality assessment index that has been sampled multiple times.

[0029] Step S106: Capture the error code returned by the device during the attempt to connect to the network.

[0030] Specifically, during the process of the device attempting to establish a connection with the target wireless access point, various error codes (E) returned by the device driver layer, network protocol stack, or operating system are monitored and captured in real time. These error codes are direct feedback information generated by the system when the connection fails.

[0031] Step S108: Input the confidence level and error code of the signal into the preset failure cause diagnosis model, and map them to obtain standardized failure cause labels to realize the root cause location of network failure.

[0032] Specifically, the signal confidence level S and the error code E are input together into a preset failure cause diagnosis model (in some preferred embodiments of the present invention, this model can be embodied as a rule engine). This model predefines various mapping rules from "condition combinations" to "standardized failure cause labels L". By matching the (S, E) combination with the conditions in the rule base, a specific, standardized failure cause label L is output, thereby achieving accurate localization of the root cause of network failure. For example, a simple rule could be: if the error code E indicates "password error", then regardless of the signal confidence level S, the label L = "PasswordError" is output.

[0033] Step S110: Generate repair prompt information based on the failure reason label.

[0034] Specifically, based on the failure reason label L, a corresponding, user-understandable repair prompt is retrieved or generated from a pre-set prompt information database. This information can be presented to the user through the device's accompanying mobile application (App) interface, the device's own display screen, or voice broadcast, guiding the user to perform precise operations. For example, for L="PasswordError", the prompt message could be "Incorrect password, please re-enter".

[0035] This invention provides a method for locating the root cause of network failure, comprising: scanning the signals of wireless access points in the current environment and collecting signal strength values ​​multiple times; evaluating the confidence level of the signal based on the multiple signal strength values; capturing error codes returned by the device during network connection attempts; inputting the signal confidence level and error codes into a preset failure cause diagnosis model to map standardized failure cause labels, thereby achieving root cause location of network failure; generating repair prompts based on the failure cause labels; and accurately locating the root cause of network failure by repeatedly collecting wireless signal strength and calculating its confidence level, combined with the error codes returned by the device, using a rule engine. This method overcomes the shortcomings of traditional solutions that can only provide general error prompts, and achieves automatic and interpretable diagnosis of various faults from "weak signal" and "frequency band incompatibility" to "password error" and "DHCP failure," significantly reducing users' blind trial and error, and improving connection success rate and after-sales processing efficiency.

[0036] Example 2 Based on the above embodiments, in some preferred embodiments of the present invention, the step of evaluating the confidence level of a signal based on the intensity values ​​of multiple signals includes: calculating the standard deviation of the intensity values ​​of multiple signals; and determining the confidence level of the signal based on the standard deviation and a preset confidence interval.

[0037] Specifically, the mean of n RSSI sample values ​​is calculated using the following formula. Sum of standard deviations σ: ; ; in, This is the mean of n RSSI samples, where n is the number of samples. Let i be the RSSI sample value. Let be the standard deviation of n RSSI sample values.

[0038] The confidence interval is preset based on experience, when If the signal falls within the confidence interval, the current signal is relatively stable.

[0039] Furthermore, in some preferred embodiments of the present invention, the step of determining the confidence level of a signal based on the standard deviation and a preset confidence interval includes: determining whether the standard deviation is within the confidence interval; if so, assigning the confidence level of the signal to a preset maximum value; if not, determining the confidence level by the distance between the standard deviation and the endpoint of any confidence interval.

[0040] Specifically, if the calculated standard deviation σ falls within the confidence interval [a, b], then the RSSI sample values ​​are considered very stable, and the signal confidence S is directly assigned the highest value (e.g., 100% or 100 points).

[0041] If the standard deviation σ does not fall within the confidence interval [a, b], the confidence level is determined based on the distance between σ and the interval endpoints a or b. The closer the distance, the higher the confidence level; the farther the distance, the lower the confidence level. For example, a linear or nonlinear function can be designed to calculate a confidence score between 0 and 100 based on the value of |σ - a| or |σ - b|. This method verifies signal stability through "mean + standard deviation analysis" and determines the reliability of the mean μ using the confidence interval, greatly enhancing the reference value of the RSSI value.

[0042] Furthermore, in some preferred embodiments of the present invention, the error code includes at least one of the following: management frame or control frame return codes from standard protocols commonly used in wireless local area networks (IEEE 802.11), Dynamic Host Configuration Protocol status codes, and Transmission Control Protocol connection phase status codes.

[0043] Specifically, the captured error code E covers multiple aspects of the connection establishment process to ensure comprehensive information. These include, but are not limited to: IEEE 802.11 protocol layer: Return status codes from management frames (such as Association / Authentication Response) or control frames.

[0044] Network Configuration Layer: Status codes returned when Dynamic Host Configuration Protocol (DHCP) interactions fail.

[0045] Transport layer: Error codes generated by the Transmission Control Protocol (TCP) when the attempt to establish a connection (three-way handshake) fails.

[0046] The multi-layered error capture mechanism ensures that faults can be located at every stage, from physical connection and authentication to IP address allocation and transmission connection.

[0047] Furthermore, in some preferred embodiments of the present invention, the failure cause diagnosis model defines a mapping relationship between various condition combinations and failure cause labels; the step of inputting the confidence level of the signal and the error code into the preset failure cause diagnosis model and mapping to obtain standardized failure cause labels includes: combining the confidence level of the signal and the error code, and then determining the failure cause label based on the mapping relationship.

[0048] Specifically, the failure cause diagnosis model can be a rule-based engine that defines the mapping relationship between signal confidence S (or its derived quality states, such as "strong", "medium", "weak"), error code E, and possible other contextual information (such as AP frequency band) and failure cause label L. This model can clearly handle complex scenarios; for example, even if the password is correct, if the connection times out due to extremely poor signal, it can be correctly diagnosed as "WeakSignal" rather than the general "connection timeout".

[0049] Furthermore, in some preferred embodiments of the present invention, the mapping relationship includes: when the error code indicates a password error, mapping to a password error tag; when the error code indicates that the wireless network frequency band is 5GHz and the confidence level of the signal is lower than a first threshold, mapping to a frequency band not supported tag; when the error code indicates that the Dynamic Host Configuration Protocol (DHCP) allocation has failed, mapping to a DHCP service exception tag.

[0050] Specifically, the rule engine can be a lookup table or decision tree consisting of "if-then" statements that runs locally on the device. See Table 1 for examples of some rules: Table 1

[0051] Furthermore, in some preferred embodiments of the present invention, the method further includes: uploading anonymized failure cause labels, signal confidence levels, and error codes to a cloud server; the cloud server performs cluster analysis on the collected data, and optimizes and updates the failure cause diagnosis model based on the analysis results.

[0052] Specifically, after user authorization, the device uploads anonymized diagnostic data (including failure cause label L, signal confidence level S, error code E, etc.) to the cloud server. The cloud server performs cluster analysis and big data mining on the massive amount of log data uploaded by the device, aiming to discover new failure modes, verify the accuracy of existing rules, or optimize parameters such as confidence interval thresholds. Based on the analysis results, the cloud generates an updated rule base or model parameters, and silently distributes them to the terminal device through firmware upgrades or online configuration. This allows the diagnostic capabilities of the entire system to continuously improve and enhance themselves as users use it, and the continuous evolution capability of the diagnostic model can be improved through cloud-based cluster analysis.

[0053] Example 3 Based on the above embodiments, this invention provides a network failure root cause location device, see [link to embodiment]. Figure 2 The diagram shown is a structural schematic of a network failure root cause localization device provided in an embodiment of the present invention. The device includes: The network signal strength acquisition module 310 is used to scan the signals of wireless access points in the current environment and collect the signal strength values ​​multiple times.

[0054] The signal confidence processing module 320 is used to evaluate the confidence of a signal based on the intensity values ​​of multiple signals.

[0055] Error code determination module 330 is used to capture error codes returned by the device during the process of attempting to connect to the network.

[0056] The network failure root cause localization module 340 is used to input the confidence level of the signal and the error code into a preset failure cause diagnosis model, and map them to obtain standardized failure cause labels to realize network failure root cause localization.

[0057] The repair suggestion module 350 is used to generate repair prompts based on the failure reason tags.

[0058] Furthermore, in some preferred embodiments of the present invention, the signal confidence processing module 320 is used to calculate the standard deviation of the intensity values ​​of multiple signals; and to determine the confidence level of the signal based on the standard deviation and a preset confidence interval.

[0059] Furthermore, in some preferred embodiments of the present invention, the signal confidence processing module 320 is used to determine whether the standard deviation is within the confidence interval; if so, the confidence of the signal is assigned a preset maximum value; if not, the confidence is determined by the distance between the standard deviation and the endpoint of any confidence interval.

[0060] Furthermore, in some preferred embodiments of the present invention, the error code includes at least one of the following: management frame or control frame return codes from standard protocols commonly used in wireless local area networks, dynamic host configuration protocol status codes, and transmission control protocol connection phase status codes.

[0061] Furthermore, in some preferred embodiments of the present invention, the failure cause diagnosis model defines a mapping relationship between various condition combinations and failure cause labels; the network failure root cause localization module 340 is used to combine the confidence level of the signal with the error code and determine the failure cause label based on the mapping relationship.

[0062] Furthermore, in some preferred embodiments of the present invention, the mapping relationship includes: when the error code indicates a password error, mapping to a password error tag; when the error code indicates that the wireless network frequency band is 5GHz and the confidence level of the signal is lower than a first threshold, mapping to a frequency band not supported tag; when the error code indicates that the Dynamic Host Configuration Protocol (DHCP) allocation has failed, mapping to a DHCP service exception tag.

[0063] Furthermore, in some preferred embodiments of the present invention, the apparatus further includes: a cloud optimization module, used to upload anonymized failure reason labels, signal confidence levels, and error codes to a cloud server; The cloud server performs cluster analysis on the collected data and optimizes and updates the failure cause diagnosis model based on the analysis results.

[0064] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the network failure root cause localization device described above can be referred to the corresponding process in the embodiments of the aforementioned network failure root cause localization method, and will not be repeated here.

[0065] Example 4 This invention also provides an electronic device for running a network failure root cause localization method; see [link to related documentation]. Figure 3 The diagram shown is a structural schematic of an electronic device provided by an embodiment of the present invention. The electronic device includes a memory 400 and a processor 401. The memory 400 is used to store one or more computer instructions, which are executed by the processor 401 to implement the above-mentioned network failure root cause localization method.

[0066] Furthermore, Figure 3The electronic device shown also includes a bus 402 and a communication interface 403. The processor 401, the communication interface 403 and the memory 400 are connected via the bus 402.

[0067] The memory 400 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 403 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 402 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0068] Processor 401 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 401 or by instructions in software form. Processor 401 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a readily available storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 400, and processor 401 reads information from memory 400 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0069] This invention also provides a readable storage medium storing computer-executable instructions. When these computer-executable instructions are called and executed by a processor, they cause the processor to implement the aforementioned network failure root cause localization method. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0070] The computer program products of the network failure root cause localization method, apparatus and electronic device provided in the embodiments of the present invention include a readable storage medium storing program code. The instructions included in the program code can be used to execute the methods in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0071] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and / or device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0072] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0073] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for locating the root cause of network failure, characterized in that, include: Scan the signals of wireless access points in the current environment and collect the signal strength values ​​multiple times; The confidence level of the signal is evaluated based on the intensity values ​​of the signal multiple times. Capture error codes returned by the device during its network connection attempt; The confidence level of the signal and the error code are input into a preset failure cause diagnosis model to obtain a standardized failure cause label, thereby realizing the root cause location of network failure. Based on the failure reason label, generate repair prompt information.

2. The network failure root cause localization method according to claim 1, characterized in that, The step of evaluating the confidence level of the signal based on multiple intensity values ​​of the signal includes: Calculate the standard deviation of the signal intensity values ​​multiple times; The confidence level of the signal is determined based on the standard deviation and the preset confidence interval.

3. The network failure root cause localization method according to claim 2, characterized in that, The step of determining the confidence level of the signal based on the standard deviation and the preset confidence interval includes: Determine whether the standard deviation is within the confidence interval; If so, the confidence level of the signal is assigned a preset maximum value; If not, the confidence level is determined by the distance between the standard deviation and the endpoints of any of the confidence intervals.

4. The method for locating the root cause of network failure according to claim 1, characterized in that, The error codes include at least one of the following: management frame or control frame return codes from standard protocols commonly used in wireless LANs, Dynamic Host Configuration Protocol status codes, and Transmission Control Protocol connection phase status codes.

5. The method for locating the root cause of network failure according to claim 1, characterized in that, The failure cause diagnosis model defines a mapping relationship between various condition combinations and failure cause labels; the step of inputting the confidence level of the signal and the error code into the preset failure cause diagnosis model to obtain standardized failure cause labels includes: After combining the confidence level of the signal with the error code, the failure reason label is determined based on the mapping relationship.

6. The network failure root cause localization method according to claim 5, characterized in that, The mapping relationship includes: When the error code indicates a password error, it is mapped to a password error label; When the error code indicates that the wireless network frequency band is 5GHz and the confidence level of the signal is lower than the first threshold, the frequency band does not support the tag. When the error code indicates a Dynamic Host Configuration Protocol (DHCP) allocation failure, it is mapped to a DHCP service exception label.

7. The method for locating the root cause of network failure according to claim 1, characterized in that, The method further includes: The anonymized failure reason label, the confidence level of the signal, and the error code are uploaded to the cloud server; The cloud server performs cluster analysis on the collected data and optimizes and updates the failure cause diagnosis model based on the analysis results.

8. A network failure root cause location device, characterized in that, include: The network signal strength acquisition module is used to scan the signals of wireless access points in the current environment and collect the strength values ​​of the signals multiple times. A signal confidence processing module is used to evaluate the confidence level of the signal based on the intensity values ​​of the signal multiple times. The error code determination module is used to capture error codes returned by the device during the network connection attempt process; The network failure root cause localization module is used to input the confidence level of the signal and the error code into a preset failure cause diagnosis model, and map them to obtain standardized failure cause labels to realize network failure root cause localization. The repair suggestion module is used to generate repair prompts based on the failure reason tags.

9. An electronic device, characterized in that, The device includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the network failure root cause localization method according to any one of claims 1 to 7.

10. A readable storage medium, characterized in that, The readable storage medium stores computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the network failure root cause localization method according to any one of claims 1 to 7.

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