Positioning and troubleshooting system based on distributed architecture

Abstract

The present invention relates to the technical field of complex system fault locating, and in particular to a positioning and troubleshooting system based on a distributed architecture, comprising: a fault identification module, a fault analysis module, a diffusion suppression module, and a fuse module. By setting up the fault identification module, the fault analysis module, the diffusion suppression module, and the fuse module, several categories of abnormal data are monitored, corresponding suspected fault information is identified, and the information flow direction of the suspected fault information is confirmed to determine the source of the fault and the scope of the fault impact when the fault finally occurs, thereby effectively identifying the relevant distributed devices that have failed, and effectively reducing the problem of troubleshooting failure caused by not processing the equipment that failed earlier.

Description

Technical Field

[0001] The present invention relates to the technical field of complex system fault location, and in particular to a location and troubleshooting system based on a distributed architecture. Background Art

[0002] In recent years, with the continuous expansion of enterprise businesses, the number of services provided within enterprises has increased, and the number of deployed systems has also continued to climb. As a result, the complexity of interactions between these systems has increased dramatically. When a problem arises, it is often necessary to query multiple systems and consult with multiple stakeholders to locate the cause, a process that is both labor-intensive and time-consuming. Reducing this investment in this area would free up significant time for R&D personnel, allowing them to focus on more valuable work.

[0003] Chinese Patent Publication No.: CN118885324B discloses a server system and a method for locating a faulty device, a computer system, a program product, and a storage medium. The method includes: in response to detecting a link failure, triggering a system management interrupt; parsing the advanced error reporting register of the faulty device to determine the fault information of the faulty device; determining the device asset information of the faulty device based on the fault information of the faulty device; in response to the device asset information of the faulty device not containing the silkscreen information of the faulty device, determining the physical location of the faulty device based on the fault information of the faulty device and the allocation relationship table. By implementing the server system disclosed in the embodiment of this application and its method, device, system, computer program product, and readable storage medium for locating a faulty device, the utilization rate of the server hardware resources can be greatly improved; the device with PCIe failure in the entire cabinet can be quickly located, the normal operation of the business can be restored in a timely manner, and the maintenance pressure of the operation and maintenance personnel can be reduced.

[0004] It can be seen that the above invention is difficult to troubleshoot a more complex distributed architecture, and when the system is running, the equipment faults detected are closer to the end, making it difficult to locate and trace the starting point of the fault. Summary of the Invention

[0005] To this end, the present invention provides a positioning and troubleshooting system based on a distributed architecture to overcome the problem in the prior art that it is difficult to troubleshoot a more complex distributed architecture, and when the system is running, the equipment faults detected are close to the end, making it difficult to locate and trace the starting point of the fault, resulting in the accumulation of system faults, thereby reducing the troubleshooting success rate.

[0006] To achieve the above objectives, the present invention provides a positioning and troubleshooting system based on a distributed architecture, comprising:

[0007] The fault identification module collects data from each distributed device according to the collection frequency, and identifies and generates corresponding fault categories and corresponding suspected fault information based on the collected data;

[0008] a fault analysis module that responds to the suspected fault information, extracts information flow characteristics of upstream and downstream links based on the call information of the distributed device, calculates a fault characterization coefficient based on the physical address corresponding to the distributed device and the information flow characteristics, and determines the corresponding fault tendency;

[0009] a diffusion suppression module, which is connected to the fault identification module and the fault analysis module respectively, and adjusts the acquisition frequency, and performs fault prediction and information flow diffusion prediction based on the data of the fault identification module;

[0010] The fusing module is connected to the diffusion suppression module and is used to calculate the corresponding scope impact index based on the fault prediction result and the information flow diffusion prediction result, and issue a corresponding early warning signal.

[0011] Furthermore, the fault analysis module is used to extract the information flow characteristics of the upstream and downstream links, including:

[0012] Used to identify the link stability in the target interface call to generate several stable links;

[0013] It is used to track several characteristic points in each stable link and determine whether the corresponding stable link is a continuous call sequence based on the information flow characteristics of each characteristic point;

[0014] If there is an information flow feature at any characteristic point in the stable link, the stable link is determined to be a continuous call sequence;

[0015] Wherein, the characteristic point is a check code preset in each information;

[0016] For a single feature point, the corresponding information flow feature is repeated in sequence in any continuous call sequence at a time interval not higher than that corresponding to the acquisition frequency;

[0017] The link stability includes the packet loss rate and transmission rate of the link.

[0018] Furthermore, the fault identification module includes an address collection unit for collecting target interface addresses, a parameter collection unit for collecting target interface parameters, a load collection unit for collecting target interface loads, and a call collection unit for collecting target interface calls;

[0019] When the parameter collection unit, the load collection unit or the call collection unit collects corresponding data and detects an abnormality, the fault identification module generates the suspected fault information.

[0020] Furthermore, the fault analysis module determines the fault tendency based on the comparison result between the fault characterization coefficient and the preset reference fault characterization coefficient standard threshold, including:

[0021] If the fault characterization coefficient exceeds a reference fault characterization coefficient standard threshold, the fault analysis module determines that the target interface has a fault tendency;

[0022] If the fault characterization coefficient does not exceed the reference fault characterization coefficient standard threshold, it is determined that the target interface has no fault tendency.

[0023] Furthermore, the fault analysis module is further configured to select a standard threshold value of the benchmark fault characterization coefficient, wherein:

[0024] The fault analysis module selects corresponding reference fault characterization coefficient standard thresholds within different time ranges.

[0025] Furthermore, the diffusion suppression module adjusts the acquisition frequency of the fault identification module based on the fault tendency and the fault characterization coefficient, wherein:

[0026] The acquisition frequency is proportional to the fault characterization coefficient.

[0027] Furthermore, the diffusion suppression module performs fault prediction based on target interface calls, including:

[0028] Used to extract several abnormal paths in target interface calls;

[0029] Comparing the address changes of each abnormal path in adjacent cycle calls collected by the fault identification module at the current collection frequency, determining each address change as a diffusion direction, and determining the diffusion speed of the fault for recording;

[0030] Used to predict the address corresponding to the diffusion position of each abnormal path after a predetermined time based on the diffusion direction and diffusion speed;

[0031] It is used to mark the diffused abnormal path in the target interface call and connect the peripheral abnormal paths to obtain a fault prediction distribution map;

[0032] The distributed devices of the fault prediction distribution map are used to calculate the fault prediction distribution map, and the distributed devices of the fault prediction distribution map are determined as the fault prediction results.

[0033] Furthermore, the diffusion suppression module predicts the information flow diffusion situation based on the target interface call, including:

[0034] Used to extract several information flow points in the target interface call;

[0035] to compare the address changes of each information flow point in adjacent cycle calls collected by the fault identification module at the current collection frequency to determine the diffusion direction and diffusion speed of the information flow;

[0036] To predict the diffusion position of each peripheral information flow point after a predetermined time based on the diffusion direction and diffusion speed of information flow;

[0037] Used to mark the peripheral information flow points after diffusion in the target interface call, and connect the peripheral information flow points to obtain a predicted distribution map of information flow diffusion;

[0038] Calculating the area of ​​the information flow diffusion prediction distribution map, and determining the area of ​​the information flow diffusion prediction distribution map as the information flow diffusion prediction result;

[0039] The area of ​​the distribution diagram is the area corresponding to the corresponding distributed devices that complete the fault information transmission and / or execution in the distribution diagram.

[0040] Furthermore, for a single distributed device, when each of its corresponding interfaces receives data, the distributed device processes the data and transmits the processing result to the next distributed device;

[0041] The speed at which information flows is related to the processing speed of each distributed device.

[0042] Furthermore, the fuse module divides the warning signal level based on the range impact index, wherein:

[0043] If the scope impact index is greater than the baseline scope impact index standard threshold, it is classified as a high-risk warning signal level;

[0044] If the range impact index is less than or equal to the benchmark range impact index standard threshold, it is classified as a low-risk warning signal level.

[0045] Compared with the existing technology, the beneficial effect of the present invention lies in that, by setting up a fault identification module, a fault analysis module, a diffusion suppression module and a fuse module, several categories of abnormal data are monitored, the corresponding suspected fault information is identified, and the information flow direction of the suspected fault information is confirmed to determine the source of the fault and the scope of the fault impact when the fault finally occurs, thereby effectively identifying the relevant distributed devices that have failed, and effectively reducing the problem of troubleshooting failure caused by not handling the equipment that failed earlier.

[0046] Furthermore, by identifying the transmission route, we can determine the transmission problems caused by data transmission. At the same time, we can determine the abnormal paths that may be caused by the transmission problems. By setting and monitoring several characteristic points, we can evaluate the reliability of the transmission link, thereby effectively avoiding troubleshooting failures caused by link problems, thereby effectively improving the accuracy of distributed architecture positioning.

[0047] Furthermore, the fault identification module is used to collect the interface address, interface parameters, interface load and calling method of each distributed device, and the collected and running data of each distributed device are verified. The information of the fault is confirmed based on the verification result, and the transmission path of the fault information is obtained through the transmission direction of the interface. When the fault is confirmed, the transmission direction of the interface can be used to confirm the location of the fault, thereby further improving the accuracy of distributed architecture positioning.

[0048] Furthermore, the distributed devices covered by a single fault are confirmed based on the load generated by the anomaly, and the fault severity of the fault is predicted based on the extent of the anomaly. While effectively avoiding the overall failure caused by large-scale distributed equipment failure, it also effectively improves the problem of difficulty in determining the actual location of the fault when a distributed architecture failure is caused by several devices, thereby further improving the accuracy of distributed architecture positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a schematic structural diagram of the positioning and troubleshooting system of the present invention;

[0050] Figure 2 This is a schematic diagram of the structure of a fault identification module according to an embodiment of the present invention;

[0051] Figure 3 This is a fault prediction distribution diagram of a distributed device according to an embodiment of the present invention;

[0052] Figure 4 Schematic diagram of the distribution of the scope affected by the fault in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0054] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0055] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0056] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0057] See also Figure 1 As shown, it is a structural diagram of the positioning and troubleshooting system of the present invention, including:

[0058] The fault identification module collects data from each distributed device according to the collection frequency, and identifies and generates corresponding fault categories and corresponding suspected fault information based on the collected data;

[0059] The fault analysis module responds to suspected fault information and extracts the information flow characteristics of upstream and downstream links based on the call information of distributed devices. It calculates the fault characterization coefficient based on the physical address of the distributed devices and the information flow characteristics to determine the corresponding fault tendency;

[0060] The diffusion suppression module is connected to the fault identification module and the fault analysis module respectively, and adjusts the acquisition frequency to perform fault prediction and information flow diffusion prediction based on the data of the fault identification module;

[0061] The fusing module is connected to the diffusion suppression module and is used to calculate the corresponding scope impact index based on the fault prediction results and the information flow diffusion prediction results, and issue a corresponding early warning signal.

[0062] By setting up a fault identification module, a fault analysis module, a diffusion suppression module and a fuse module, several categories of abnormal data are monitored, the corresponding suspected fault information is identified, and the information flow direction of the suspected fault information is confirmed to determine the source of the fault and the scope of the fault impact when the fault finally occurs, thereby effectively identifying the relevant distributed devices that have failed, and effectively reducing the problem of troubleshooting failure caused by not handling the equipment that failed earlier. Embodiment 1:

[0063] Collect data such as CPU usage, memory usage, and disk I / O from each server at a regular interval. If a server's CPU usage exceeds 90% repeatedly, its memory usage exceeds 80%, and its disk I / O wait time increases significantly, the server may be experiencing a performance bottleneck and a suspected failure message will be generated.

[0064] In response to suspected fault information, the server's call information within the distributed system is extracted, such as which services it provides data to as an upstream provider and which services it receives data from as a downstream provider. The information flow characteristics of the upstream and downstream links are analyzed. The fault characterization coefficient is calculated by combining the server's physical address and information flow characteristics, such as data transmission rate and packet loss rate, to determine whether the server's fault tendency is due to aging hardware or improper system configuration.

[0065] Connected to the Fault Identification and Analysis Modules, this module adjusts the frequency of data collection for the server from once per minute to every 30 seconds based on the fault characterization coefficient determined by the fault propensity, allowing for more timely monitoring of fault developments. Furthermore, the module performs fault prediction based on data from the Fault Identification Module, analyzing the flow and spread of information and predicting potential delays or unavailability for multiple downstream services that rely on the server if not addressed promptly.

[0066] The Fuse Module, connected to the Spread Suppression Module, calculates the corresponding scope impact index based on the fault prediction results and the information flow and spread prediction results. If the server failure is predicted to affect multiple critical business services, a high-priority warning signal is issued, notifying operations and maintenance personnel to take immediate measures, such as restarting the server, adjusting system configuration, or replacing hardware, to prevent further spread of the fault.

[0067] In the above embodiment, the acquisition frequency may be 50 Hz. Example 2:

[0068] The system collects voltage, current, and power data from distributed power generation equipment and substation equipment on the power grid at a constant frequency. When voltage fluctuations at a substation exceed a set threshold, and when current changes abnormally, the system identifies a possible electrical fault at the substation and generates a suspected fault message.

[0069] In response to suspected fault information, the system extracts information about the substation's upstream and downstream links within the power grid, such as its power reception from upstream power generation equipment and its power distribution to downstream users, and analyzes information flow characteristics. Combining the substation's physical location with information flow characteristics, such as line impedance and power factor, the system calculates the fault characterization coefficient to determine whether the fault is caused by aging internal components or external environmental factors (such as lightning strikes or heavy rain).

[0070] Based on the fault characterization coefficient determined by the fault tendency, the frequency of data collection for the substation is adjusted to more accurately monitor the development of the fault. Based on the data from the fault identification module, fault prediction and information flow and diffusion are predicted. Analysis shows that if not handled promptly, it could cause a power outage in a localized area of ​​the power grid, affecting the normal power supply of multiple nearby users.

[0071] Based on the fault prediction results and the predicted information flow and diffusion, a range impact index is calculated. If the predicted power outage is widespread, an emergency warning signal is issued, notifying the grid dispatch center to take measures, such as adjusting grid operation and activating backup power sources, to mitigate the impact of the fault on grid operations and user electricity consumption.

[0072] In the above embodiment, the frequency of collection may be 1 minute / time. Example 3:

[0073] The system collects operational data from distributed automation equipment on the production line at a set frequency, such as the motion accuracy of the robotic arm, sensor detection data, and the execution status of controller instructions. If the motion accuracy of a robotic arm falls below the standard value multiple times in a row, and the deviation of the material position detected by the sensor increases, the system identifies a possible mechanical or sensor failure in the robotic arm and generates a suspected failure message.

[0074] The Fault Analysis Module responds to suspected fault information by extracting the robot's call information within the production line, such as the preceding and following equipment in the production process, and analyzing the information flow characteristics of the upstream and downstream links. Combining the robot's physical address and information flow characteristics, such as the real-time and accuracy of data transmission, it calculates the fault characterization coefficient to determine whether the fault is caused by wear of the robot's mechanical structure or sensor failure.

[0075] Diffusion Suppression Module: Based on the fault characterization coefficient determined by the fault tendency, the frequency of data collection for the robot arm is adjusted to obtain fault-related information more promptly. Based on the data from the Fault Identification Module, fault prediction and information flow and diffusion are predicted. Analysis shows that if not addressed promptly, the production rhythm of the entire production line may be disrupted, affecting the normal operation of subsequent processes.

[0076] The Fuse Module calculates the scope impact index based on the fault prediction results and the information flow and diffusion prediction results. If the fault is predicted to cause a large-scale production halt, a high-risk warning signal is issued, notifying production management to take measures such as suspending the production line and organizing maintenance personnel for emergency repairs to prevent further production losses caused by the fault.

[0077] In the above embodiment, the frequency of collection may be 5 minutes per time.

[0078] In implementation, the frequency of acquisition can be determined by the operating frequency of the distributed equipment when it is working. Generally, it is related to the operating rate of a single process.

[0079] Specifically, the fault analysis module is used to extract the information flow characteristics of upstream and downstream links, including:

[0080] Used to identify the link stability in the target interface call to generate several stable links;

[0081] It is used to track several characteristic points in each stable link and determine whether the corresponding stable link is a continuous call sequence based on the information flow characteristics of each characteristic point;

[0082] If there is any characteristic point of information flow feature in the stable link, the stable link is determined to be a continuous call sequence;

[0083] Among them, the characteristic point is the check code preset in each information;

[0084] For a single feature point, its corresponding information flow feature is repeated in sequence in any continuous call sequence at a time interval not higher than the time interval corresponding to the acquisition frequency;

[0085] Link stability includes the link's packet loss rate and transmission rate.

[0086] By identifying the transmission route, we can determine the transmission problems caused by data transmission. At the same time, we can determine the abnormal paths that may be caused by the transmission problems. By setting and monitoring several characteristic points, we can evaluate the reliability of the transmission link, thereby effectively avoiding troubleshooting failures caused by link problems, thereby effectively improving the accuracy of distributed architecture positioning.

[0087] See also Figure 2 , which is a schematic diagram of the structure of a fault identification module according to an embodiment of the present invention. The fault identification module includes an address collection unit for collecting the address of the target interface, a parameter collection unit for collecting the parameters of the target interface, a load collection unit for collecting the load of the target interface, and a call collection unit for collecting calls of the target interface;

[0088] When the parameter collection unit, the load collection unit or the call collection unit collects corresponding data and an abnormality occurs, the fault identification module generates suspected fault information.

[0089] The fault identification module is used to collect the interface address, interface parameters, interface load and calling method of each distributed device, verify the collected and running data of each distributed device, and confirm the fault information based on the verification results. The transmission path of the fault information is obtained through the transmission direction of the interface. When the fault is confirmed, the transmission direction of the interface can be used to confirm the location of the fault, thereby further improving the accuracy of distributed architecture positioning.

[0090] Specifically, the fault analysis module determines the fault tendency based on the comparison result between the fault characterization coefficient and the preset reference fault characterization coefficient standard threshold, including:

[0091] If the fault characterization coefficient exceeds the standard threshold of the baseline fault characterization coefficient, the fault analysis module determines that the target interface has a fault tendency;

[0092] If the fault characterization coefficient does not exceed the standard threshold of the benchmark fault characterization coefficient, it is determined that the target interface has no fault tendency.

[0093] Specifically, the fault analysis module is also used to select a standard threshold value of a benchmark fault characterization coefficient, wherein:

[0094] The fault analysis module selects corresponding standard thresholds of the benchmark fault characterization coefficient within different time ranges.

[0095] Specifically, the diffusion suppression module adjusts the acquisition frequency of the fault identification module based on the fault tendency and the fault characterization coefficient, wherein the acquisition frequency is proportional to the fault characterization coefficient.

[0096] Specifically, the diffusion suppression module performs fault prediction based on target interface calls, including:

[0097] Used to extract several abnormal paths in target interface calls;

[0098] Compare the address changes of each abnormal path in adjacent cycle calls collected by the fault identification module at the current collection frequency, determine each address change as the diffusion direction, and determine the diffusion speed of the fault and record it;

[0099] Used to predict the address corresponding to the diffusion position of each abnormal path after a predetermined time based on the diffusion direction and diffusion speed;

[0100] It is used to mark the diffused abnormal paths in the target interface call and connect the peripheral abnormal paths to obtain the fault prediction distribution map;

[0101] The distributed devices used to calculate the fault prediction distribution map are determined as the fault prediction results.

[0102] See also Figure 3 As shown, it is a fault prediction distribution diagram of a distributed device according to an embodiment of the present invention, which includes four data transmission links:

[0103] (1) Distributed device α → distributed device A1 → distributed device ω1 → distributed device α;

[0104] (2) Distributed device α → distributed device A1 → distributed device B2 → distributed device ω2 → distributed device α;

[0105] (3) Distributed device α → distributed device A2 → distributed device B1 → distributed device ω2 → distributed device α;

[0106] (4) Distributed device α → distributed device A2 → distributed device B2 → distributed device ω2 → distributed device α;

[0107] In the above transmission links, distributed devices α, distributed devices A1, and distributed devices A2 involve at least two different transmission links at the back end of their transmission links. It is not difficult to see that when a failure occurs in the above distributed devices, their fault prediction distribution diagrams will involve a large number of corresponding distributed devices.

[0108] The distributed devices B1 and B2 involve only one transmission link at the back end of their transmission links. When the distributed devices B1 and B2 fail, the number of distributed devices involved is relatively small.

[0109] In practice, the above-mentioned means can be used to quickly predict the corresponding fault prediction distribution map.

[0110] Specifically, the diffusion suppression module predicts the information flow and diffusion based on the target interface call, including:

[0111] Used to extract several information flow points in the target interface call;

[0112] To compare the address changes of each information flow point in the adjacent cycle calls collected by the fault identification module at the current collection frequency to determine the diffusion direction and diffusion speed of the information flow;

[0113] To predict the diffusion position of each peripheral information flow point after a predetermined time based on the diffusion direction and diffusion speed of information flow;

[0114] It is used to mark the peripheral information flow points after diffusion in the target interface call, and connect the peripheral information flow points to obtain the predicted distribution map of information flow diffusion;

[0115] Calculating the area of ​​the information flow diffusion prediction distribution map, and determining the area of ​​the information flow diffusion prediction distribution map as the information flow diffusion prediction result;

[0116] The area of ​​the distribution diagram is the area corresponding to the corresponding distributed devices that complete the fault information transmission and / or execution in the distribution diagram.

[0117] The distributed devices covered by a single fault are confirmed based on the load generated by the anomaly, and the fault severity of the fault is predicted based on the extent of the anomaly. This effectively avoids the overall failure caused by large-scale distributed device failures, and effectively improves the problem of difficulty in determining the actual location of the fault when a distributed architecture failure is caused by several devices, thereby further improving the accuracy of distributed architecture positioning.

[0118] Specifically, for a single distributed device, when each of its corresponding interfaces receives data, the distributed device processes the data and transmits the processing result to the next distributed device;

[0119] The speed at which information flows is related to the processing speed of each distributed device.

[0120] Specifically, the fuse module divides the warning signal level based on the scope impact index, where:

[0121] If the scope impact index is greater than the baseline scope impact index standard threshold, it is classified as a high-risk warning signal level;

[0122] If the range impact index is less than or equal to the benchmark range impact index standard threshold, it is classified as a low-risk warning signal level.

[0123] See also Figure 4 As shown in FIG, which is a schematic diagram of the distribution range of the fault impact of an embodiment of the present invention. In the figure, when the distributed device A2 fails, the distributed device B2, the distributed device B1 and the distributed device ω2 are all affected;

[0124] On this basis, when it is identified that the distributed device ω2 has a fault and the distributed device A2 has a suspected fault, it can be located that the impact range of the fault includes the above range.

[0125] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0126] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A positioning and troubleshooting system based on a distributed architecture, characterized in that: include: The fault identification module is used to collect data from each distributed device according to the collection frequency, and identify and generate corresponding fault categories and corresponding suspected fault information based on the collected data; The data of each distributed device collected by the fault identification module includes target interface address, target interface load, target interface parameters and target interface call; a fault analysis module, which responds to the suspected fault information, extracts information flow characteristics of upstream and downstream links based on the call information of the distributed device, calculates a fault characterization coefficient based on the physical address corresponding to the distributed device and the information flow characteristics, and determines the corresponding fault tendency; a diffusion suppression module, which is connected to the fault identification module and the fault analysis module respectively, and adjusts the acquisition frequency, and performs fault prediction and information flow diffusion prediction based on the data of the fault identification module; a fusing module connected to the diffusion suppression module, configured to calculate a corresponding scope impact index based on the fault prediction result and the information flow diffusion prediction result, and issue a corresponding warning signal; The fault analysis module is used to extract the information flow characteristics of the upstream and downstream links, including: Used to identify the link stability in the target interface call to generate several stable links; It is used to track several characteristic points in each stable link and determine whether the corresponding stable link is a continuous call sequence based on the information flow characteristics of each characteristic point; If there is an information flow feature at any characteristic point in the stable link, the stable link is determined to be a continuous call sequence; Wherein, the characteristic point is a check code preset in each information; For a single feature point, the corresponding information flow feature is repeated in sequence in any continuous call sequence at a time interval not higher than that corresponding to the acquisition frequency; The link stability includes the packet loss rate and transmission rate of the link; The diffusion suppression module performs fault prediction based on target interface calls, including: Used to extract several abnormal paths in target interface calls; Comparing the address changes of each abnormal path in adjacent cycle calls collected by the fault identification module at the current collection frequency, determining each address change as a diffusion direction, and determining the diffusion speed of the fault for recording; Used to predict the address corresponding to the diffusion position of each abnormal path after a predetermined time based on the diffusion direction and diffusion speed; It is used to mark the diffused abnormal path in the target interface call and connect the peripheral abnormal paths to obtain a fault prediction distribution map; for calculating each distributed device of the fault prediction distribution map, and determining each distributed device of the fault prediction distribution map as a fault prediction result; The diffusion suppression module predicts the information flow diffusion situation based on the target interface call, including: Used to extract several information flow points in the target interface call; to compare the address changes of each information flow point in adjacent cycle calls collected by the fault identification module at the current collection frequency to determine the diffusion direction and diffusion speed of the information flow; To predict the diffusion position of each peripheral information flow point after a predetermined time based on the diffusion direction and diffusion speed of information flow; Used to mark the peripheral information flow points after diffusion in the target interface call, and connect the peripheral information flow points to obtain a predicted distribution map of information flow diffusion; It is used to calculate the area of ​​the information flow diffusion prediction distribution map, and determine the area of ​​the information flow diffusion prediction distribution map as the information flow diffusion prediction result.

2. The distributed architecture-based positioning and troubleshooting system according to claim 1, characterized in that: The fault identification module includes an address collection unit for collecting target interface addresses, a parameter collection unit for collecting target interface parameters, a load collection unit for collecting target interface loads, and a call collection unit for collecting target interface calls; When the parameter collection unit, the load collection unit or the call collection unit collects corresponding data and detects an abnormality, the fault identification module generates the suspected fault information.

3. The distributed architecture-based positioning and troubleshooting system according to claim 2, characterized in that: The fault analysis module determines the fault tendency based on the comparison result between the fault characterization coefficient and the preset reference fault characterization coefficient standard threshold, including: If the fault characterization coefficient exceeds a reference fault characterization coefficient standard threshold, the fault analysis module determines that the target interface has a fault tendency; If the fault characterization coefficient does not exceed the reference fault characterization coefficient standard threshold, it is determined that the target interface has no fault tendency.

4. The distributed architecture-based positioning and troubleshooting system according to claim 3, characterized in that: The fault analysis module is further configured to select a standard threshold value of the reference fault characterization coefficient, wherein: The fault analysis module selects corresponding reference fault characterization coefficient standard thresholds within different time ranges.

5. The distributed architecture-based positioning and troubleshooting system according to claim 4, characterized in that: The diffusion suppression module adjusts the acquisition frequency of the fault identification module based on the fault tendency and the fault characterization coefficient, wherein, The acquisition frequency is proportional to the fault characterization coefficient.

6. The distributed architecture-based positioning and troubleshooting system according to claim 5, characterized in that: For a single distributed device, when each of its corresponding interfaces receives data, the distributed device processes the data and transmits the processing result to the next distributed device; The speed at which information flows is related to the processing speed of each distributed device.

7. The distributed architecture-based positioning and troubleshooting system according to claim 6, characterized in that: The fuse module divides the warning signal level based on the range impact index, wherein: If the scope impact index is greater than the baseline scope impact index standard threshold, it is classified as a high-risk warning signal level; If the range impact index is less than or equal to the benchmark range impact index standard threshold, it is classified as a low-risk warning signal level.

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