Switch fault elimination method and device, equipment, storage medium and product

Abstract

The invention relates to the technical field of communication, and discloses a switch fault elimination method and device, equipment, a storage medium and a product, and the method comprises the steps: monitoring a multi-network-layer performance index of a switch through integrating a plurality of network protocols, building a fault prediction model based on a machine learning algorithm, and identifying the multi-network-layer performance index by using a fault prediction model to obtain an identification result, and when the identification result is an abnormal mode, performing fuzzy query by using a media access control address and an internet protocol address to obtain a fault source, and removing the fault source according to a preset repair strategy. According to the method, multiple network protocols are integrated, the multi-network-layer performance indexes of the switch are comprehensively monitored, the fault is identified by using the model constructed by the machine learning algorithm, the fault source is positioned through the media access control address and the internet protocol address, and the fault is eliminated according to the preset repair strategy, so that the operation and maintenance efficiency of the switch is effectively improved; and the fault influence range is reduced.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a switch troubleshooting method, device, equipment, storage medium and product. Background Art

[0002] At present, traditional network switches mainly rely on log recording and manual analysis when troubleshooting. Although this method is effective, it has some obvious defects, such as strong manual dependence, technicians need to have rich experience to correctly interpret logs, resulting in a long troubleshooting time; lack of real-time performance, logs are usually viewed only after the fault occurs, and real-time monitoring and rapid response are impossible; information redundancy, large amount of log information, and often contain a lot of irrelevant information, making it more difficult to locate the problem, and lack of intelligence. Summary of the invention

[0003] The main purpose of this application is to provide a switch troubleshooting method, device, equipment, storage medium and product, aiming to solve the technical problem that the existing technology relies on manual labor, lacks network adaptability, and leads to low efficiency of switch troubleshooting.

[0004] To achieve the above object, the present application proposes a switch troubleshooting method, the method comprising: Monitor the multi-network layer performance indicators of switches by integrating multiple network protocols; Establishing a fault prediction model based on a machine learning algorithm, and using the fault prediction model to identify the multi-network layer performance indicators to obtain an identification result; When the identification result is an abnormal mode, a fuzzy query is performed using the media access control address and the Internet Protocol address to obtain the fault source, and the fault source is eliminated according to a preset repair strategy.

[0005] In one embodiment, when the identification result is an abnormal mode, the steps of using the media access control address and the Internet Protocol address to perform fuzzy query to obtain the fault source and eliminating the fault source according to a preset repair strategy include: When the identification result is an abnormal mode, an Ethernet forwarding mechanism of a media access control address and an Internet Protocol address is constructed by parsing the multi-network layer performance indicators; Using the forwarding table items of the Ethernet forwarding mechanism, combined with multi-source data, a fuzzy query is performed on the network management system to obtain the fault source; Combined with automated operation and maintenance tools and self-healing network architecture, select the corresponding repair strategy from the preset repair strategies to eliminate the fault source.

[0006] In one embodiment, the step of combining the automated operation and maintenance tool and the self-healing network architecture to select a corresponding repair strategy from preset repair strategies to eliminate the fault source includes: Achieve self-healing network architecture through network redundancy and router optimization technology; Select an automated operation and maintenance tool based on network scale and operation and maintenance requirements, and configure the triggering conditions of the automated operation and maintenance tool; By integrating the automated operation and maintenance tool and the self-healing network architecture, a corresponding repair strategy is selected from preset repair strategies to eliminate the fault source.

[0007] In one embodiment, after the step of monitoring the multi-network layer performance indicators of the switch by integrating multiple network protocols, the method further includes: Creating a database of media access control addresses and Internet protocol addresses, and updating the database according to the multi-network layer performance indicators; Based on the association database, the network is tested through a connectivity test data packet to obtain a visual connectivity check report; Based on the historical network data and the visual connectivity check report, a fault alarm model is constructed by training an anomaly detection algorithm.

[0008] In one embodiment, after the step of building a fault alarm model by training an anomaly detection algorithm based on historical network data and the visual connectivity check report, the method further includes: Detecting faults in the multi-network layer performance indicators by setting alarm thresholds and rules of the fault alarm model; When the fault alarm model identifies the fault, matching the fault with historical cases in the information database to obtain a matching result; A corresponding solution is extracted according to the matching result, the switch configuration is adjusted according to the solution, and a repair action record and a repair log are generated.

[0009] In one embodiment, the step of establishing a fault prediction model based on a machine learning algorithm, identifying the multi-network layer performance indicators using the fault prediction model, and obtaining the identification result further includes: Implementing a visualization dashboard module by integrating the network topology diagram, the multi-network layer performance indicators, alarm information and abnormal prediction information; An intelligent recommendation solution module is implemented by integrating the fault prediction model and the fault alarm model; When the visualization dashboard module has an abnormal mode and / or a fault, the abnormal mode and / or the fault is eliminated according to the intelligent recommendation solution module.

[0010] In addition, to achieve the above purpose, the present application also proposes a switch fault troubleshooting device, the switch fault troubleshooting device comprising: Data collection module, used to monitor the multi-network layer performance indicators of the switch by integrating multiple network protocols; A fault prediction module, used to establish a fault prediction model based on a machine learning algorithm, and use the fault prediction model to identify the multi-network layer performance indicators to obtain an identification result; The troubleshooting module is used to perform fuzzy query using the media access control address and the Internet Protocol address to obtain the fault source when the identification result is an abnormal mode, and eliminate the fault source according to a preset repair strategy.

[0011] In addition, to achieve the above-mentioned purpose, the present application also proposes a switch troubleshooting device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the switch troubleshooting method as described above.

[0012] In addition, to achieve the above purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and stores a computer program on the storage medium. When the computer program is executed by a processor, the steps of the switch troubleshooting method described above are implemented.

[0013] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, wherein the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the switch fault troubleshooting method described above are implemented.

[0014] The technical solution proposed in this application integrates multiple network protocols to monitor the multi-network layer performance indicators of the switch, establishes a fault prediction model based on a machine learning algorithm, uses the fault prediction model to identify the multi-network layer performance indicators, obtains the identification result, and when the identification result is an abnormal mode, uses the media access control address and the Internet Protocol address to perform fuzzy query to obtain the source of the fault, and eliminates the source of the fault according to the preset repair strategy. Because this application integrates multiple network protocols, comprehensively monitors the multi-network layer performance indicators of the switch, identifies faults using a model built by a machine learning algorithm, locates the source of the fault through the media access control address and the Internet Protocol address, and eliminates the fault according to the preset repair strategy, it effectively improves the operation and maintenance efficiency of the switch and reduces the scope of fault impact. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0017] Figure 1 A flowchart of the first embodiment of the switch troubleshooting method of the present application is provided; Figure 2 This is a schematic diagram of the switch troubleshooting method module for this application; Figure 3 A flow chart of the switch troubleshooting method according to the present invention; Figure 4 A flowchart of the third embodiment of the switch troubleshooting method of the present application is provided; Figure 5 This is a schematic diagram of the module structure of the switch troubleshooting device according to an embodiment of the present application; Figure 6 This is a schematic diagram of the device structure of the hardware operating environment involved in the switch troubleshooting method in the embodiment of the present application.

[0018] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0020] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0021] The current existing technologies rely on manual analysis of logs and data, which results in a slow and error-prone troubleshooting process, and cannot meet the needs of rapid recovery of network services. Many existing products only analyze after a fault occurs, lack real-time monitoring of network status, and cannot detect potential problems and issue early warnings in a timely manner. They are not flexible enough to adapt to the changing fault modes in complex network environments, and information redundancy and noise interference increase the complexity of troubleshooting.

[0022] Therefore, in order to overcome the above-mentioned defects, the present application provides a solution by integrating multiple network protocols, comprehensively monitoring the multi-network layer performance indicators of the switch, identifying faults using a model built using a machine learning algorithm, locating the source of the fault through the media access control address and the Internet Protocol address, and troubleshooting based on preset repair strategies, thereby effectively improving the operation and maintenance efficiency of the switch and reducing the scope of fault impact.

[0023] It should be noted that the execution subject of each embodiment of the present application may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a switch troubleshooting device, etc. The following embodiments are described below taking a switch troubleshooting device as an example.

[0024] Based on this, the present application embodiment provides a switch troubleshooting method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the switch troubleshooting method of the present application.

[0025] In this embodiment, the switch fault troubleshooting method includes steps S10 to S30: Step S10, monitoring the multi-network layer performance indicators of the switch by integrating multiple network protocols.

[0026] It should be noted that the network protocol is a set of rules, standards or conventions established for data exchange in computer networks. It is the basis for data communication in computer networks and ensures that different devices can correctly and efficiently transmit and receive data. These rules or conventions detail how data is formatted, transmitted, interpreted and processed, thereby achieving seamless communication in the network. In order to comprehensively monitor the multi-network layer performance indicators of the switch, it is necessary to integrate multiple network protocols, such as Simple Network Management Protocol (SNMP), Network Monitoring Function Protocol (NetFlow), etc.

[0027] It is understandable that by simultaneously monitoring the performance indicators of different layers such as the physical layer, data link layer, network layer, and transport layer, the bottlenecks and failure points in the network can be more accurately located. When selecting multi-network layer performance indicators, it is necessary to pay attention to the key performance indicators of the switch, such as traffic, latency, and packet loss rate.

[0028] Step S20, establishing a fault prediction model based on a machine learning algorithm, and using the fault prediction model to identify the multi-network layer performance indicators to obtain an identification result.

[0029] It should be noted that machine learning is a branch of artificial intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. Machine learning algorithms are at the core of this learning process, analyzing and processing input data to discover patterns, regularities, and relationships in the data, thereby being able to predict future results or make decisions. A fault prediction model is a model built on a machine learning algorithm that analyzes data to predict possible future faults and identify abnormal patterns in the data.

[0030] In order to improve the response speed of abnormal modes and / or faults, after step S20, the following may also be included: Implementing a visualization dashboard module by integrating the network topology diagram, the multi-network layer performance indicators, alarm information and abnormal prediction information; An intelligent recommendation solution module is implemented by integrating the fault prediction model and the fault alarm model; When the visualization dashboard module has an abnormal mode and / or a fault, the abnormal mode and / or the fault is eliminated according to the intelligent recommendation solution module.

[0031] It should be noted that the network topology diagram refers to the graphical representation of each node in the network (such as computers, routers, switches, etc.) and the connection relationship between them, which can intuitively understand the physical or logical structure of the network and facilitate network planning, management and troubleshooting. Alarm information refers to the prompt information automatically generated by the system when one or some parameters in the network reach the preset threshold. Abnormal prediction information refers to information that predicts possible abnormal situations in the network in the future based on historical data and machine learning algorithms.

[0032] like Figure 2 As shown, the visualization dashboard module can display the network status area, display the network topology diagram, and mark the status of each node (normal / abnormal); the performance indicator area displays key performance indicators such as real-time traffic, latency, and packet loss rate; the abnormal alarm area displays abnormal alarm information, including the abnormal type, occurrence time, etc.; the fault prediction area displays the fault prediction results, including possible fault types, predicted time, etc.

[0033] The intelligent recommended solution module can display the fault details area, showing detailed information of the current fault, including fault type, impact scope, etc.; the solution area provides solution suggestions based on the fault type and historical processing experience, including steps, required resources, etc.; the historical case area displays historical processing cases of similar faults for reference by operation and maintenance personnel.

[0034] It should be understood that the visualization dashboard module and the intelligent recommendation solution module are interactively designed in the web page, and users can quickly understand the network status and fault information through the visualization dashboard module. Clicking on an abnormal alarm or fault prediction result can jump to the fault details area to view detailed information. In the solution area, users can select a recommended solution or refer to historical cases for manual processing.

[0035] Step S30, when the identification result is an abnormal mode, a fuzzy query is performed using the media access control address and the Internet Protocol address to obtain the fault source, and the fault source is eliminated according to a preset repair strategy.

[0036] It should be noted that the Media Access Control (MAC) address of the data link layer is usually assigned by the network interface card (NIC) when it is manufactured and is globally unique. It usually consists of six groups of hexadecimal numbers, for example: 00:1A:2B:3C:4D:5E. The media access control address is used to identify devices in the local network and transmit data frames. When data is transmitted within the same local area network, the switch uses the media access control address to determine the forwarding target of the data frame to ensure that the data can reach the destination device correctly. The Internet Protocol (IP) address is the address of the network layer, which is responsible for identifying the logical address of the device in the network. It usually consists of four groups of decimal numbers, such as 192.168.1.1. The Internet Protocol address is used for communication between different networks.

[0037] Preset repair strategies refer to a series of pre-defined repair solutions for specific faults or problems based on historical experience and best practices during network operation and maintenance. These strategies usually include specific operation steps, required resources, expected results, etc. When the identification result is an abnormal mode, select the appropriate solution from the preset repair strategy to quickly troubleshoot the fault.

[0038] This embodiment integrates multiple network protocols to monitor the multi-network layer performance indicators of the switch, establishes a fault prediction model based on a machine learning algorithm, uses the fault prediction model to identify the multi-network layer performance indicators, obtains the identification result, and when the identification result is an abnormal mode, uses the media access control address and the Internet Protocol address to perform fuzzy query to obtain the fault source, and eliminates the fault source according to the preset repair strategy. Because this application integrates multiple network protocols, comprehensively monitors the multi-network layer performance indicators of the switch, identifies faults using a model built by a machine learning algorithm, locates the fault source through the media access control address and the Internet Protocol address, and eliminates the fault according to the preset repair strategy, it effectively improves the switch operation and maintenance efficiency and reduces the scope of fault impact.

[0039] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 3 , the step S30 may include steps S301 to S303: Step S301, when the identification result is an abnormal mode, an Ethernet forwarding mechanism of a media access control address and an Internet Protocol address is constructed by parsing the multi-network layer performance indicators.

[0040] It is understandable that once an abnormal pattern is identified, the system needs to deeply analyze the performance indicators of multiple network layers, which may include the signal quality of the physical layer, the frame error rate of the data link layer, the routing table status of the network layer, the connection status of the transport layer, etc. After analyzing the performance indicators of multiple network layers, in order to establish the correct data forwarding path between the media access control address and the Internet Protocol address, an Ethernet forwarding mechanism is constructed.

[0041] It should be noted that the Ethernet forwarding mechanism is the process used by the switch to forward data frames to the correct port according to the destination media access control address. When building the Ethernet forwarding mechanism, the system needs to consider factors such as network topology, routing strategy, and flow control.

[0042] Step S302, using the forwarding table entries of the Ethernet forwarding mechanism and combining multi-source data to perform fuzzy query on the network management system to obtain the fault source.

[0043] It should be noted that the Ethernet forwarding mechanism relies on forwarding table entries to guide the forwarding of data packets. These table entries usually include source MAC address, destination MAC address, port number, virtual local area network (VLAN) information, etc.

[0044] In order to ensure the comprehensiveness of fuzzy queries, it is necessary to combine multi-source data, which can include network traffic data, data collected by traffic analysis tools; multi-network layer performance indicators; log and alarm data, log and alarm information from network devices, security systems or applications; configuration and status data, which is the configuration information and current status of network devices.

[0045] It should be understood that the information in the forwarding table entries is used to find data packets or flows related to the abnormal pattern, and by matching the source MAC address, destination MAC address, port number, VLAN tag and other information, the device or port that may be involved in the fault is located, and the information in the forwarding table entries is correlated with multi-source data for analysis to identify the association between the abnormal pattern and a specific device, port or flow. Then, machine learning or data mining technology is used to perform pattern recognition and anomaly detection on the multi-source data to further improve the accuracy of fault location.

[0046] In addition, fuzzy query can also be integrated with the real-time monitoring system to provide intelligent analysis of network status. The system can automatically analyze whether there is a potential fault based on historical data and current network status, and actively prompt the operation and maintenance personnel to check or adjust. It can also classify the log installation business, and then further control the error log and troubleshooting (debug) log separately and feedback to the user in a timely manner, so as to solve the fault errors of specific business.

[0047] Step S303: In combination with the automated operation and maintenance tool and the self-healing network architecture, a corresponding repair strategy is selected from preset repair strategies to eliminate the fault source.

[0048] It should be noted that automated operation and maintenance tools refer to software or systems that can automatically perform operation and maintenance tasks, monitor network status, analyze performance data, and take corresponding maintenance measures, such as intelligent operation and maintenance (AIOps). Common automated operation and maintenance tools include automated deployment tools, monitoring and alarm systems, performance analysis tools, etc. Self-healing network architecture is a network architecture that can self-detect, self-diagnose, and self-repair. It mainly uses advanced network technology and algorithms to monitor network status in real time, detect potential problems or failures, and automatically trigger corresponding repair mechanisms to restore normal network operation.

[0049] The step S303 may further include: Achieve self-healing network architecture through network redundancy and router optimization technology; Select an automated operation and maintenance tool based on network scale and operation and maintenance requirements, and configure the triggering conditions of the automated operation and maintenance tool; By integrating the automated operation and maintenance tool and the self-healing network architecture, a corresponding repair strategy is selected from preset repair strategies to eliminate the fault source.

[0050] It should be noted that network redundancy refers to adding additional devices or paths to the network to improve the reliability and fault tolerance of the network. By deploying redundant devices (such as routers, switches, etc.) and redundant links, it can be ensured that when a network device or link fails, the traffic can be automatically transferred to other available paths. By optimizing the configuration of routers, such as adjusting routing policies and enabling Quality of Service (QoS) functions, the reasonable distribution of network traffic and the setting of priorities can be ensured.

[0051] It is understandable that for large networks, you may need to deploy powerful and scalable automated operation and maintenance platforms, such as Ansible, Chef, Puppet, etc., to support complex configuration management and automated deployment tasks. For small networks, you can choose some lightweight automated operation and maintenance tools, such as Shell scripts, Python scripts, etc., to meet basic automated operation and maintenance needs.

[0052] It should be noted that the trigger conditions of automated operation and maintenance tools refer to the automatic execution of corresponding operation and maintenance tasks when specific conditions are met. These conditions can be set based on various factors such as network status, performance indicators, security events, etc. For example, it can be configured to automatically trigger troubleshooting and repair tasks when network latency exceeds a certain threshold, or automatically trigger security response and defense measures when a security attack is detected.

[0053] It should be understood that the integration of automated operation and maintenance tools and self-healing network architecture can be achieved through API interfaces, message queues, etc. Through integration, automated operation and maintenance tools can receive fault alarm information sent by the self-healing network architecture in real time, and automatically perform corresponding repair tasks according to preset repair strategies.

[0054] This embodiment analyzes multi-network layer performance indicators and constructs an Ethernet forwarding mechanism when a network mode is identified as abnormal. It uses the forwarding table items of the Ethernet forwarding mechanism to perform fuzzy queries on the network management system in combination with multi-source data. It combines automated operation and maintenance tools and a self-healing network architecture, selects the most appropriate strategy from preset repair strategies to eliminate the source of the fault, and achieves strong troubleshooting flexibility and scalability, which can adapt to network environments of different scales and requirements.

[0055] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 4 , the step S10 may include steps S111 to S113: Step S111, creating a correlation database of media access control addresses and Internet protocol addresses, and updating the correlation database according to the multi-network layer performance indicators.

[0056] It should be appreciated that by associating the MAC address with the IP address, it is easier to track and manage devices in the network and determine the location and status of a particular device in the network.

[0057] Exemplarily, the steps of creating an associated database may be: obtaining MAC address and IP address mapping information from the configuration of network devices (such as routers, switches, servers, etc.); using network management tools (such as SNMP, DHCP server logs, etc.) to collect dynamically assigned IP addresses and corresponding MAC addresses; creating a database containing at least two fields: MAC address and IP address, and other related fields may be added, such as device name, device type, network segment, VLAN information, etc., for more detailed network management; importing MAC address and IP address mapping information collected from network devices or network management tools into the database; and indexing the MAC address and IP address fields to speed up queries.

[0058] Based on the performance analysis results, update the relevant information in the associated database. For example, if the network performance corresponding to a certain IP address is severely degraded, a record can be added to the database to mark the performance problem of the IP address. If a device with a certain MAC address is replaced or moved, the MAC address and IP address mapping information in the database can be updated.

[0059] Step S112: Based on the association database, the network is tested by a connectivity test data packet to obtain a visual connectivity check report.

[0060] It should be noted that connectivity test packets are packets used to test the connectivity between devices in a network. These packets usually contain specific source addresses, destination addresses, and possible test data. When these packets are transmitted in the network, they can help identify problems such as paths, delays, and packet loss in the network, and evaluate network connectivity by sending and receiving these packets.

[0061] Step S113, building a fault alarm model by training an anomaly detection algorithm based on historical network data and the visual connectivity check report.

[0062] It should be noted that anomaly detection algorithm is a machine learning algorithm that can identify data points that are significantly different from normal behavior patterns. Common anomaly detection algorithms include statistical-based methods (such as Z-score, IQR, etc.), distance-based methods (such as K-nearest neighbor, local outlier factor, etc.), and machine learning-based methods (such as support vector machines, neural networks, etc.).

[0063] It is understandable that the anomaly detection algorithm is trained using pre-processed historical network data and visual connectivity check reports and extracted features. During the training process, the algorithm learns the characteristics of normal network behavior and builds a baseline model.

[0064] After step S113, the following steps may also be included: Detecting faults in the multi-network layer performance indicators by setting alarm thresholds and rules of the fault alarm model; When the fault alarm model identifies the fault, matching the fault with historical cases in the information database to obtain a matching result; A corresponding solution is extracted according to the matching result, the switch configuration is adjusted according to the solution, and a repair action record and a repair log are generated.

[0065] It is understandable that for multiple network layer performance indicators (such as latency, jitter, packet loss rate, bandwidth utilization, etc.), setting reasonable alarm thresholds and rules in the fault alarm model can be based on the normal operating range and historical data of the network to determine when abnormal modes and failures occur in network performance.

[0066] The fault alarm model continuously monitors network performance indicators and detects faults in real time based on the set thresholds and rules. Once a performance indicator is detected to be out of the normal range, an alarm is triggered immediately. For example, if an IP address fails to respond to an Address Resolution Protocol (ARP) request, the system will prompt whether the port of the MAC address is disabled or blocked, or whether there is a VLAN configuration error, or whether the access control list (ACL) configuration, Qosbuffer is full and packet loss, or the transition table entry is missing. Match the characteristics of the current fault (such as fault type, impact range, performance indicators, etc.) with historical cases in the information database. Among them, the information database stores past network faults and their solutions.

[0067] It should be understood that, based on the matching results, the solution that best matches the current fault is extracted from the information database. These solutions may include adjusting the switch configuration, restarting the device, optimizing the network path, etc. Based on the extracted solution, the switch configuration is automatically adjusted. This may involve changing the routing policy, adjusting the port speed, enabling or disabling specific functions, etc.

[0068] During the fault repair process, the system generates a repair action record and a repair log. The repair action record describes in detail the entire process of fault detection, matching historical cases, extracting solutions, and adjusting switch configurations. The repair log records key information such as the timestamp of each step, the person who performed the operation, and the results of the operation.

[0069] This embodiment creates an associated database of media access control addresses and Internet Protocol addresses and updates it in real time, uses connectivity test data packets to conduct a comprehensive test of the network, and implements fault alarm model detection of faults by setting alarm thresholds and rules. When a fault is identified, the relevant information of the fault is matched with historical cases to ensure timely response to the fault, thereby realizing intelligent detection and repair of switch faults.

[0070] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the switch troubleshooting method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0071] This application also provides a switch troubleshooting device, please refer to Figure 5, the switch troubleshooting device comprises: A data collection module 10, for monitoring the multi-network layer performance indicators of the switch by integrating multiple network protocols; A fault prediction module 20 is used to establish a fault prediction model based on a machine learning algorithm, and use the fault prediction model to identify the multi-network layer performance indicators to obtain an identification result; The fault elimination module 30 is used to perform fuzzy query using the media access control address and the Internet Protocol address to obtain the fault source when the identification result is an abnormal mode, and eliminate the fault source according to a preset repair strategy.

[0072] The switch troubleshooting device provided by the present application adopts the switch troubleshooting method in the above embodiment, which can solve the technical problem that the prior art relies on manual work and lacks network adaptability, resulting in low efficiency of switch troubleshooting. Compared with the prior art, the beneficial effects of the switch troubleshooting device provided by the present application are the same as the beneficial effects of the switch troubleshooting method provided by the above embodiment, and other technical features in the switch troubleshooting device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0073] The present application provides a switch troubleshooting device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the switch troubleshooting method in the above-mentioned embodiment 1.

[0074] Reference below Figure 6 , which shows a schematic diagram of the structure of a switch troubleshooting device suitable for implementing the embodiment of the present application. The switch troubleshooting device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions: tablet computers), PMPs (Portable Media Players: portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The switch troubleshooting device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0075] like Figure 6As shown, the switch troubleshooting device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the switch troubleshooting device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the switch troubleshooting device to communicate with other devices wirelessly or wired to exchange data. Although the switch troubleshooting device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0076] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0077] The switch troubleshooting device provided by the present application adopts the switch troubleshooting method in the above embodiment, which can solve the technical problem that the prior art relies on manual work and lacks network adaptability, resulting in low efficiency of switch troubleshooting. Compared with the prior art, the beneficial effects of the switch troubleshooting device provided by the present application are the same as the beneficial effects of the switch troubleshooting method provided by the above embodiment, and the other technical features in the switch troubleshooting device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0078] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0079] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0080] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the switch troubleshooting method in the above embodiment.

[0081] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0082] The computer-readable storage medium may be included in the switch troubleshooting device; or may exist independently without being assembled into the switch troubleshooting device.

[0083] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the switch troubleshooting device, the switch troubleshooting device: monitors the multi-network layer performance indicators of the switch by integrating multiple network protocols, establishes a fault prediction model based on a machine learning algorithm, uses the fault prediction model to identify the multi-network layer performance indicators to obtain an identification result, and when the identification result is an abnormal mode, uses the media access control address and the Internet Protocol address to perform fuzzy query to obtain the fault source, and eliminates the fault source according to a preset repair strategy.

[0084] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0085] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0086] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0087] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned switch troubleshooting method, and can solve the technical problem that the prior art relies on manual work and lacks network adaptability, resulting in low efficiency in switch troubleshooting. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the switch troubleshooting method provided by the above-mentioned embodiment, and will not be elaborated here.

[0088] The present application also provides a computer program product, including a computer program, wherein when the computer program is executed by a processor, the steps of the switch fault troubleshooting method as described above are implemented.

[0089] The computer program product provided by the present application can solve the technical problem that the prior art relies on manual work and lacks network adaptability, resulting in low efficiency in troubleshooting of switches. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the switch troubleshooting method provided by the above embodiment, and will not be elaborated here.

[0090] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or directly / indirectly applied in other related technical fields, are included in the patent protection scope of the present application.

Claims

1. A switch troubleshooting method, characterized in that: The method comprises the following steps: Monitor the multi-network layer performance indicators of switches by integrating multiple network protocols; Establishing a fault prediction model based on a machine learning algorithm, and using the fault prediction model to identify the multi-network layer performance indicators to obtain an identification result; When the identification result is an abnormal mode, a fuzzy query is performed using the media access control address and the Internet Protocol address to obtain the fault source, and the fault source is eliminated according to a preset repair strategy.

2. The switch troubleshooting method according to claim 1, characterized in that: When the identification result is an abnormal mode, the steps of using the media access control address and the Internet Protocol address to perform fuzzy query to obtain the fault source and eliminating the fault source according to the preset repair strategy include: When the identification result is an abnormal mode, an Ethernet forwarding mechanism of a media access control address and an Internet Protocol address is constructed by parsing the multi-network layer performance indicators; Using the forwarding table items of the Ethernet forwarding mechanism, combined with multi-source data, a fuzzy query is performed on the network management system to obtain the fault source; Combined with automated operation and maintenance tools and self-healing network architecture, select the corresponding repair strategy from the preset repair strategies to eliminate the fault source.

3. The switch troubleshooting method according to claim 2, characterized in that: The step of combining the automated operation and maintenance tool and the self-healing network architecture to select a corresponding repair strategy from the preset repair strategies to eliminate the fault source includes: Achieve self-healing network architecture through network redundancy and router optimization technology; Select an automated operation and maintenance tool based on network scale and operation and maintenance requirements, and configure the triggering conditions of the automated operation and maintenance tool; By integrating the automated operation and maintenance tool and the self-healing network architecture, a corresponding repair strategy is selected from preset repair strategies to eliminate the fault source.

4. The switch troubleshooting method according to any one of claims 1 to 3, characterized in that: After the step of monitoring the multi-network layer performance indicators of the switch by integrating multiple network protocols, the method further includes: Creating a database of media access control addresses and Internet protocol addresses, and updating the database according to the multi-network layer performance indicators; Based on the association database, the network is tested through a connectivity test data packet to obtain a visual connectivity check report; Based on the historical network data and the visual connectivity check report, a fault alarm model is constructed by training an anomaly detection algorithm.

5. The switch troubleshooting method according to claim 4, characterized in that: After the step of building a fault alarm model by training an anomaly detection algorithm based on historical network data and the visual connectivity check report, the method further includes: Detecting faults in the multi-network layer performance indicators by setting alarm thresholds and rules of the fault alarm model; When the fault alarm model identifies the fault, matching the fault with historical cases in the information database to obtain a matching result; A corresponding solution is extracted according to the matching result, the switch configuration is adjusted according to the solution, and a repair action record and a repair log are generated.

6. The switch troubleshooting method according to any one of claims 1 to 3, characterized in that: After the step of establishing a fault prediction model based on a machine learning algorithm, identifying the multi-network layer performance indicators using the fault prediction model, and obtaining an identification result, the method further includes: Implementing a visualization dashboard module by integrating the network topology diagram, the multi-network layer performance indicators, alarm information and abnormal prediction information; An intelligent recommendation solution module is implemented by integrating the fault prediction model and the fault alarm model; When the visualization dashboard module has an abnormal mode and / or a fault, the abnormal mode and / or the fault is eliminated according to the intelligent recommendation solution module.

7. A switch troubleshooting device, characterized in that: The switch troubleshooting device comprises: Data collection module, used to monitor the multi-network layer performance indicators of the switch by integrating multiple network protocols; A fault prediction module, used to establish a fault prediction model based on a machine learning algorithm, and use the fault prediction model to identify the multi-network layer performance indicators to obtain an identification result; The troubleshooting module is used to perform fuzzy query using the media access control address and the Internet Protocol address to obtain the fault source when the identification result is an abnormal mode, and eliminate the fault source according to a preset repair strategy.

8. A switch troubleshooting device, characterized in that: The switch troubleshooting device comprises: a memory, a processor, and a switch troubleshooting program stored in the memory and executable on the processor. When the switch troubleshooting program is executed by the processor, the switch troubleshooting method according to any one of claims 1 to 6 is implemented.

9. A storage medium, characterized in that: The storage medium stores a switch fault troubleshooting program, and when the switch fault troubleshooting program is executed by the processor, the switch fault troubleshooting method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises a switch fault troubleshooting program, and when the switch fault troubleshooting program is executed by a processor, the switch fault troubleshooting method according to any one of claims 1 to 6 is implemented.

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