Network analysis method, device, system and equipment and storage medium

Abstract

The invention discloses a network analysis method and device, electronic equipment and a storage medium, and the method is applied to a controller, and comprises the steps: obtaining rule information inputted by a user, and converting the rule information into a rule template which can be recognized by a preset rule engine; configuration information of each network device is acquired, the configuration information is issued to the corresponding network device, and the configuration information is used for indicating whether the corresponding network device starts a flow-following detection service or not; and receiving service data reported by the network device starting the flow detection service, and forwarding the service data to a network management platform, the network management platform being used for analyzing the service data based on the rule template by calling a preset rule engine to obtain a network analysis result. The expandability of the rule template allows a user to define analysis rules from multiple dimensions such as time delay, packet loss rate, bandwidth utilization rate and the like, and different scene requirements are flexibly adapted in combination with a rule engine of a network management platform, so that intelligent analysis of network quality is realized, and the efficiency and precision of network analysis are remarkably improved.

Description

Technical Field

[0001] This application belongs to the field of communications, and particularly relates to a network analysis method, apparatus, system, device, and storage medium. Background Art

[0002] With the accelerating development of new technologies and new services such as cloud computing, big data, Internet Plus, Internet of Things, and artificial intelligence, a new metropolitan area network centered on the Spine-Leaf architecture has gradually emerged. Among them, the dedicated line service is an important service in the new metropolitan area network, which refers to a network connection method that provides point-to-point data transmission services for users through specific transmission media, and usually has high commercial value with high returns and high profits.

[0003] In the prior art, for the network quality analysis of dedicated line services in the new metropolitan area network, it mainly relies on traditional network monitoring tools and methods, including traffic monitoring based on SNMP (Simple Network Management Protocol), Ping (Packet Internet Groper) testing, Traceroute path tracing, and other means.

[0004] However, traditional monitoring means can often only measure certain specific aspects of the network, such as latency, packet loss rate, etc., and cannot comprehensively evaluate the performance and quality of the network. Moreover, various factors in the network environment, such as transmission media, device performance, network topology, etc., may affect the network analysis results, resulting in inaccurate network analysis results. Summary of the Invention

[0005] The purpose of the embodiments of this application is to provide a network analysis method, apparatus, system, device, and storage medium, which can solve the problem that the current traditional monitoring means cannot comprehensively evaluate the performance and quality of the network, and the network analysis results are inaccurate.

[0006] In a first aspect, the embodiments of this application provide a network analysis method, which is applied to a controller. The method includes:

[0007] Obtain the rule information input by the user, and convert the rule information into a rule template recognizable by a preset rule engine;

[0008] Obtain the configuration information of each network device, and send the configuration information to the corresponding network device. The configuration information is used to indicate whether the corresponding network device enables the flow detection service;

[0009] Receive the service data reported by the network device that enables the in-flow detection service, and forward the service data to the network management platform, where the network management platform is used to parse the service data based on the rule template by invoking the preset rule engine to obtain the network analysis result.

[0010] Optionally, after converting the rule information into a rule template recognizable by the preset rule engine, it further includes:

[0011] Store the rule template in the preset rule library so that the network management platform can obtain the rule template from the preset rule library.

[0012] Optionally, the sending the configuration information to the corresponding network device includes:

[0013] Encapsulate the configuration information into a configuration template according to the preset network management protocol;

[0014] Send the configuration template to the corresponding network device so that the network device can determine whether to enable the in-flow detection service based on the configuration template.

[0015] Optionally, the forwarding the service data to the network management platform includes:

[0016] Forward the service data to the network management platform through the Kafka message middleware.

[0017] In a second aspect, an embodiment of the present application provides a network analysis method applied to a network management platform. The method includes:

[0018] Obtain the rule information input by the user and the configuration information of each network device;

[0019] Send the rule information and the configuration information to the controller, where the controller is used to convert the rule information into a rule template recognizable by the preset rule engine and is also used to configure whether the corresponding network device reports service data based on the configuration information;

[0020] Receive the service data sent by the controller, and invoke the preset rule engine to parse the service data based on the rule template to obtain the network analysis result.

[0021] Optionally, the obtaining the rule information input by the user includes:

[0022] Interact with the user through a visual interface to obtain the rule information input by the user.

[0023] Optionally, the invoking the preset rule engine to parse the service data based on the rule template to obtain the network analysis result includes:

[0024] Parse the service data according to the performance index algorithm to obtain performance index data;

[0025] Invoke the preset rule engine, match the performance index data based on the rule template, and obtain a network analysis result.

[0026] In a third aspect, an embodiment of the present application provides a network analysis device, which is applied to a controller. The device includes:

[0027] A conversion module, configured to obtain rule information input by a user and convert the rule information into a rule template recognizable by a preset rule engine;

[0028] A configuration module, configured to obtain configuration information of each network device and send the configuration information to the corresponding network device. The configuration information is used to indicate whether the corresponding network device enables the flow monitoring service;

[0029] A forwarding module, configured to receive service data reported by a network device that enables the flow monitoring service and forward the service data to a network management platform. The network management platform is used to parse the service data based on the rule template by invoking the preset rule engine to obtain a network analysis result.

[0030] In a fourth aspect, an embodiment of the present application provides a network analysis device, which is applied to a network management platform. The device includes:

[0031] An acquisition module, configured to obtain rule information input by a user and configuration information of each network device;

[0032] A sending module, configured to send the rule information and the configuration information to a controller. The controller is used to convert the rule information into a rule template recognizable by a preset rule engine and is also used to configure whether the corresponding network device reports service data based on the configuration information;

[0033] An analysis module, configured to receive service data sent by the controller and invoke the preset rule engine to parse the service data based on the rule template to obtain a network analysis result.

[0034] In a fifth aspect, an embodiment of the present application provides a network analysis system, including a network management platform and a controller, where:

[0035] The network management platform is configured to obtain rule information input by a user and configuration information of each network device; send the rule information and the configuration information to the controller;

[0036] The controller is configured to convert the rule information into a rule template recognizable by a preset rule engine; obtain the configuration information of each network device, and send the configuration information to the corresponding network device, where the configuration information is used to indicate whether the corresponding network device enables the flow detection service; receive the service data reported by the network device that enables the flow detection service, and forward the service data to the network management platform;

[0037] The network management platform is further configured to call the preset rule engine, and parse the service data based on the rule template to obtain a network analysis result.

[0038] In a sixth aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory. The memory stores a program or instruction that can run on the processor. When the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.

[0039] In a seventh aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0040] In an eighth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is configured to run a program or instruction to implement the method described in the first aspect.

[0041] In a ninth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method described in the first aspect.

[0042] In the present application, the controller obtains the rule information input by the user, and converts the rule information into a rule template recognizable by a preset rule engine; obtains the configuration information of each network device, and sends the configuration information to the corresponding network device, where the configuration information is used to indicate whether the corresponding network device enables the flow detection service; receives the service data reported by the network device that enables the flow detection service, and forwards the service data to the network management platform, and the network management platform is configured to call the preset rule engine to implement parsing the service data based on the rule template to obtain a network analysis result.

[0043] As can be seen from the above, in the present application, the controller converts the rule information input by the user into a rule template recognizable by a preset rule engine, enabling the network management platform to achieve automated parsing of service data by invoking the rule engine. Moreover, the controller instructs whether to enable the flow detection service for network devices by sending configuration information to the network devices, enabling the network devices with the flow detection service enabled to collect and report service data in real time. Therefore, no manual intervention is required from service data collection to network analysis based on service data, and the scalability of the rule template allows users to define analysis rules from multiple dimensions such as delay, packet loss rate, and bandwidth utilization rate. Combining with the rule engine of the network management platform, different scenario requirements can be flexibly adapted, thereby realizing intelligent analysis of network quality, and significantly improving the efficiency and accuracy of network analysis. Description of the Drawings

[0044] Figure 1 is a flowchart of a network analysis method shown according to an exemplary embodiment;

[0045] Figure 2 is a flowchart of a network analysis method shown according to an exemplary embodiment;

[0046] Figure 3 is a logical flowchart of a network analysis method shown according to an exemplary embodiment;

[0047] Figure 4 is an example schematic diagram of a network analysis method shown according to an exemplary embodiment;

[0048] Figure 5 is an example schematic diagram of a network analysis method shown according to an exemplary embodiment;

[0049] Figure 6 is a block diagram of a network analysis device shown according to an exemplary embodiment;

[0050] Figure 7 is a block diagram of a network analysis device shown according to an exemplary embodiment;

[0051] Figure 8 is a flowchart of a network analysis system shown according to an exemplary embodiment;

[0052] Figure 9 is a block diagram of an electronic device shown according to an exemplary embodiment;

[0053] Figure 10 is a schematic diagram of the hardware structure of an electronic device shown according to an exemplary embodiment. Detailed Embodiments

[0054] Next, the technical solutions in the embodiments of the present application will be clearly described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0055] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are usually of the same category, and do not limit the number of objects. For example, the first object can be one or multiple. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / " generally means an "or" relationship between the associated objects before and after.

[0056] First, the nouns mentioned in the present application are explained:

[0057] Drools (JBoss Rules, an open-source business rule engine): is an open-source business rule engine that is easy to access enterprise strategies, easy to adjust, and easy to manage. It conforms to industry standards, is fast and efficient. Business analysts or reviewers can use it to easily view business rules to check whether the encoded rules execute the required business rules.

[0058] IFIT (In-situ Flow Information Telemetry) is a detection technology that directly detects network performance indicators by feature-tagging real network traffic flows. IFIT can significantly improve the timeliness and effectiveness of network operation and maintenance, and promote the development of intelligent operation and maintenance.

[0059] In the related art, for the analysis of the network quality of dedicated line services in a new metropolitan area network, it mainly relies on traditional network monitoring tools and methods, including SNMP-based traffic monitoring, Ping tests, Traceroute path tracing, etc.

[0060] However, traditional monitoring means can often only measure certain specific aspects of the network, such as latency, packet loss rate, etc., and cannot comprehensively evaluate the performance and quality of the network. Moreover, various factors in the network environment, such as transmission media, device performance, network topology, etc., may affect the network analysis results, resulting in inaccurate network analysis results.

[0061] Based on this, the present application proposes a network analysis method to solve the above problems. The following will, in conjunction with the accompanying drawings, explain in detail the network analysis method provided by the embodiments of the present application through specific embodiments and their application scenarios.

[0062] Figure 1 FIG. is a flowchart of a network analysis method shown according to an exemplary embodiment, applied to a controller. The network analysis method includes the following steps.

[0063] In step S11, obtain the rule information input by the user and convert the rule information into a rule template recognizable by a preset rule engine.

[0064] After obtaining the rule information input by the user, the controller can convert the rule information into a format or template recognizable by the preset rule engine, that is, the rule template. The rule template is used to define the structure, logic, and conditions of a certain or certain rules for network analysis. For example, it may include various conditions such as thresholds, relationships, combinations, etc. of performance metric data. The preset rule engine can be a Drools rule engine or other rule engines, and is not specifically limited.

[0065] Among them, the rule information input by the user usually includes specific requirements and standards for network traffic analysis, including but not limited to:

[0066] Monitoring objects, that is, the user may wish to monitor specific service data, such as data packets of specific IP addresses, ports, or protocols; analysis metrics, that is, the user may be concerned about certain specific network performance metrics, such as throughput, latency, jitter, or packet loss rate; alarm conditions, that is, the user may set certain conditions, and when the service data meets these conditions, it is determined that the network is abnormal; data format, that is, the user may specify the data format they hope to receive.

[0067] In this step, the process of converting the rule information into a rule template recognizable by the preset rule engine usually includes the following steps:

[0068] First, the rule information input by the user can be parsed to understand the user's intentions and requirements.

[0069] Then, the parsed rule information can be mapped to a preset template, where the preset template is predefined and used to describe various possible rule conditions and operations.

[0070] Furthermore, an executable rule template can be generated according to the mapping result, and the rule template will be used by the rule engine for actual network traffic monitoring and analysis work.

[0071] In step S12, obtain the configuration information of each network device and send the configuration information to the corresponding network device. The configuration information is used to indicate whether the corresponding network device enables the flow monitoring service.

[0072] In this step, communication with the network management platform can be carried out through a network management protocol (such as SNMP) to obtain the configuration information. Then, the configuration information is sent to the network device through the network management protocol to configure the network device using the built-in command-line interface or management interface.

[0073] Among them, the sent configuration information needs to clearly indicate whether the network device enables the flow monitoring service, and may also need to include specific parameter settings of the flow monitoring service, such as the sampling rate, detection period, etc. The flow monitoring service is particularly important in large networks, data centers, and cloud computing environments, which can help users monitor network performance in real time, discover potential security threats, and perform fault troubleshooting and repair in a timely manner.

[0074] Furthermore, after the configuration information is sent, it is necessary to confirm whether the network device has successfully received and applied these configuration information. For example, the effectiveness of the configuration can be confirmed through the response information or log returned by the network device.

[0075] When the configuration information indicates that the network device enables the flow monitoring service, the network device will start to monitor and analyze network traffic in real time, including sampling, parsing, and statistics of the traffic to generate service data. When the configuration information indicates that the network device disables the flow monitoring service, the network device will stop the real-time monitoring and analysis of network traffic.

[0076] In step S13, receive the service data reported by the network device that enables the flow monitoring service and forward the service data to the network management platform. The network management platform is used to parse the service data based on a rule template by calling a preset rule engine to obtain a network analysis result.

[0077] After the network device enables the flow monitoring service, it will monitor and analyze network traffic in real time according to preset rules and policies to obtain service data. That is to say, the service data contains various information of network traffic, such as source address, destination address, protocol type, traffic size, number of data packets, etc. The network device will report this service data to the controller in a predetermined format and period.

[0078] Then, the controller can forward the service data reported by the network device to the network management platform, and this process involves the selection of network communication protocols and data transmission mechanisms. In practical applications, the network device may send the service data to the network management platform through the TCP / IP (Transmission Control Protocol / Internet Protocol) protocol, or may use other dedicated network management protocols such as SNMP. In addition, to ensure the reliability and integrity of the data, the network device may process the service data using mechanisms such as encryption and checksum, and this application does not make any limitations on this.

[0079] In one implementation, after converting the rule information into a rule template recognizable by a preset rule engine, it further includes:

[0080] Storing the rule template in a preset rule library so that the network management platform can obtain the rule template from the preset rule library.

[0081] That is to say, the controller analyzes and interprets the rule information, converts it into a rule template recognizable by the preset rule engine, and then stores the rule template in the preset rule library. The preset rule library is a database or storage system specifically used to store and manage rule templates, and usually contains various types of rule templates.

[0082] Among them, the storage process may involve steps such as data formatting, encryption, and verification to ensure the accuracy and security of the data. At the same time, the preset rule library can also provide rich management functions, such as adding, deleting, modifying, querying rule templates, version control, permission management, etc.

[0083] In this way, the network management platform can conveniently obtain these rule templates from the preset rule library, and then perform subsequent network traffic monitoring and analysis tasks.

[0084] In one implementation, sending the configuration information to the corresponding network device includes:

[0085] Encapsulating the configuration information into a configuration template according to a preset network management protocol;

[0086] Sending the configuration template to the corresponding network device so that the network device can determine whether to enable the flow detection service based on the configuration template.

[0087] That is to say, before sending the configuration information to the network device, the controller needs to encapsulate it into a format that meets the requirements of the preset network management protocol. This process usually involves operations such as encoding, encrypting, and packing the configuration information to ensure the security and integrity of the information during transmission. The encapsulated configuration information is called a configuration template.

[0088] A configuration template usually contains configuration instructions and parameter settings that network devices need to follow. These instructions and parameters are used to guide the device on how to enable or disable the flow detection service, as well as how to perform traffic monitoring and analysis, etc., so that the network device can determine whether to enable the flow detection service based on the configuration template.

[0089] In one implementation, forwarding service data to the network management platform includes:

[0090] Forwarding service data to the network management platform through the Kafka message middleware.

[0091] That is to say, the controller encapsulates the generated service data into a format that the Kafka message middleware can recognize and sends it to the Kafka message middleware through the network. After receiving the service data sent by the controller, the Kafka message middleware will parse and verify it to ensure the integrity and accuracy of the data. Then, the Kafka message middleware forwards the parsed service data to the network management platform. The network management platform performs further analysis and processing based on the received data, such as generating a network analysis report, triggering an alarm mechanism, etc.

[0092] Among them, Kafka is a distributed stream processing platform mainly used to build real-time data pipelines and stream applications, and can process high-throughput data streams. It can be understood that the amount of service data generated by network devices is usually large, while the processing capacity of the network management platform may be limited. Therefore, the Kafka message middleware can be used as a data buffer to temporarily store this service data so that the network management platform can process the service data as needed. Moreover, the Kafka message middleware supports the persistent storage of service data. Even if a network device or the network management platform fails, it can ensure the integrity and recoverability of the service data, providing strong support for the persistent storage and fault recovery of service data.

[0093] Figure 2 It is a flowchart of a network analysis method shown according to an exemplary embodiment, which is applied to the network management platform. This network analysis method includes the following steps.

[0094] In step S21, obtain the rule information input by the user and the configuration information of each network device.

[0095] In step S22, send the rule information and configuration information to the controller. The controller is used to convert the rule information into a rule template recognizable by a preset rule engine and is also used to configure whether the corresponding network device reports service data based on the configuration information.

[0096] In step S23, receive the service data sent by the controller and call the preset rule engine to parse the service data based on the rule template to obtain the network analysis result.

[0097] The above steps S21 - S23 are similar to S11 - S13 in the previous embodiment and will not be elaborated here.

[0098] In one implementation, obtaining the rule information input by the user includes:

[0099] Interacting with the user through a visual interface to obtain the rule information input by the user.

[0100] That is to say, the network management platform can provide the user with a visual interface that can customize the network performance index matching rules. In the visual interface, there are dedicated areas or controls to receive the rule information input by the user. These rule information may include the classification criteria of network traffic, priority settings, access control policies, etc. The user can input this rule information by entering text, selecting options, or adjusting parameters, etc.

[0101] Furthermore, during the process of the user inputting the rule information, a real - time feedback and verification mechanism can be provided to help the user promptly discover and correct input errors, ensuring the accuracy and effectiveness of the rule information.

[0102] Generally, the layout of the visual interface should be clear and concise, avoiding excessive redundant information from interfering with the user's sight. Important information and functions should be placed in prominent positions for the user to quickly find and use. Moreover, the interaction method should conform to the user's operation habits. For example, controls such as drop - down menus, buttons, and sliders can be used to receive the user's input, while providing instant feedback and prompts.

[0103] In this way, a more intuitive and user - friendly operation experience can be provided to better meet the user's needs and expectations.

[0104] In one implementation, call a preset rule engine to parse the service data based on a rule template to obtain a network analysis result, including:

[0105] Parse the service data according to the performance index algorithm to obtain performance index data;

[0106] Call a preset rule engine to match the performance index data based on the rule template to obtain a network analysis result.

[0107] It can be understood that service data usually contains various information such as network traffic, device status, and user behavior. In order to extract valuable information for network analysis from this service data, certain performance index algorithms are required. These algorithms may include but are not limited to:

[0108] Traffic statistics algorithm: used to calculate key indicators such as the total amount, rate, and distribution of network traffic.

[0109] Performance monitoring algorithm: used to evaluate performance metrics such as the response time, throughput, and packet loss rate of network devices.

[0110] Security analysis algorithm: used to detect security threats such as abnormal behaviors and malicious attacks in the network.

[0111] By applying these performance metric algorithms, the original business data is converted into a series of quantified performance metric data, providing a basis for subsequent rule matching.

[0112] After obtaining the performance metric data, the next step is to call a preset rule engine for rule matching. The rule engine is a system for executing rules, which can evaluate the performance metric data according to a preset rule template and generate corresponding network analysis results.

[0113] Specifically, after calling the rule engine, the performance metric data can be matched one by one according to the rule template. If a certain performance metric data meets the conditions in the rule template, the rule engine will generate a corresponding network analysis result.

[0114] The network analysis results may contain various information, such as evaluation results in aspects such as the network status, performance, and security. These results can help network administrators understand the operating conditions of the network and timely discover potential problems.

[0115] Figure 3 It is a logical flowchart of a network analysis method shown according to an exemplary embodiment. It includes the following steps:

[0116] Step 1, customize and set network performance good or bad rules through a network performance metric rule visualization management tool. If not set, the default rules will be used.

[0117] Step 2, the controller analyzes and interprets the network performance good or bad rules and converts them into natural language rule templates that drools can recognize.

[0118] Step 3, the controller stores the rule template in a preset rule library.

[0119] Step 4, the Xincheng dedicated line network management platform specifies that the Xincheng device configures the flow detection function and issues the configuration to the controller.

[0120] Step 5, the controller encapsulates the flow detection netconf configuration template.

[0121] Step 6, the controller issues the encapsulated configuration template to the specified Xincheng device.

[0122] Step 7, the flow detection configuration of the Xincheng device takes effect and the device has the flow detection function.

[0123] Step 8, the Xincheng device generates flow detection service data.

[0124] Step 9, the Xincheng device reports the in-line detection service data to the controller.

[0125] Step 10, the controller receives the in-line detection service data.

[0126] Step 11, the controller sends the in-line detection service data to the Xincheng dedicated line network management platform through kafka.

[0127] Step 12, the network management platform calculates the performance index value according to the performance index algorithm and stores it in the performance index library.

[0128] Steps 13 - 14, the performance index matches the index rule library to automatically generate a network quality analysis report.

[0129] Figure 4 It is an example schematic diagram of a network analysis method shown according to an exemplary embodiment, corresponding to a custom index rule library and an in-line detection configuration process, specifically including:

[0130] 101: Set custom multi-dimensional index rules through the Xincheng dedicated line network management network performance index rule visualization interface;

[0131] 102: The controller converts the set visualization rules into a natural language rule template recognizable by drools and stores the rule template in a preset rule library

[0132] 103: Return the response result of rule setting success / failure.

[0133] 104: The Xincheng dedicated line network management platform issues the in-line detection configuration to the controller;

[0134] 105: The controller encapsulates the in-line detection configuration according to the netconf configuration template rules;

[0135] 106: The controller issues the encapsulated in-line detection configuration to the Xincheng device;

[0136] 107: After receiving the in-line detection configuration, the in-line detection function of the Xincheng device becomes effective;

[0137] 108 - 110: The Xincheng device returns a success / failure response configuration template to the controller, the controller parses the response configuration template, and returns the response result to the Xincheng dedicated line network management platform.

[0138] Figure 5 It is an example schematic diagram of a network analysis method shown according to an exemplary embodiment, corresponding to the rule automatic matching process, specifically including:

[0139] 201: The Xincheng device generates in-line detection service data;

[0140] 202: The new town device reports the service data of the flow - through detection to the controller;

[0141] 203: The controller collects the detection data through the Telemetry protocol;

[0142] 204: The controller sends the detection data to the new town dedicated line network management platform through the kafka middleware;

[0143] 205: The new town dedicated line network management platform parses the detection data and calculates the performance index data according to the performance index algorithm;

[0144] 206: The new town to new network management platform matches the calculated performance index data with the index rule library and can automatically form a network quality report.

[0145] As can be seen from the above, in the technical solution provided by the embodiment of the present application, by converting the rule information input by the user into a rule template recognizable by the preset rule engine, the network management platform can realize the automatic parsing of service data by calling the rule engine. Moreover, the controller sends the configuration information to the network device to indicate whether the network device enables the flow - through detection service, so that the network device that enables the flow - through detection service collects and reports the service data in real time. Therefore, from the collection of service data to the network analysis based on the service data, no manual intervention is required, and the scalability of the rule template allows the user to define analysis rules from multiple dimensions such as delay, packet loss rate, and bandwidth utilization rate. Combined with the rule engine of the network management platform, it can flexibly adapt to different scenario requirements, thereby realizing the intelligent analysis of network quality, and significantly improving the efficiency and accuracy of network analysis.

[0146] In the network analysis method provided by the embodiment of the present application, the execution subject can be a network analysis device. In the embodiment of the present application, taking the method of the network analysis device for terminal access as an example, the device of the network analysis method provided by the embodiment of the present application is described.

[0147] Figure 6 It is a block diagram of a network analysis device shown according to an exemplary embodiment, applied to a controller, and includes:

[0148] A conversion module 301, configured to obtain the rule information input by the user and convert the rule information into a rule template recognizable by the preset rule engine;

[0149] A configuration module 302, configured to obtain the configuration information of each network device and send the configuration information to the corresponding network device, where the configuration information is used to indicate whether the corresponding network device enables the flow - through detection service;

[0150] The forwarding module 303 is configured to receive service data reported by a network device that enables the in-flow detection service, and forward the service data to the network management platform, which is configured to parse the service data based on the rule template by invoking the preset rule engine to obtain a network analysis result.

[0151] Figure 7 FIG. is a block diagram of a network analysis device shown according to an exemplary embodiment, which is applied to a network management platform. The device includes:

[0152] The obtaining module 401 is configured to obtain rule information input by a user and configuration information of each network device;

[0153] The sending module 402 is configured to send the rule information and the configuration information to a controller, which is configured to convert the rule information into a rule template recognizable by a preset rule engine, and is further configured to configure whether a corresponding network device reports service data based on the configuration information;

[0154] The parsing module 403 is configured to receive service data sent by the controller, and invoke the preset rule engine to parse the service data based on the rule template to obtain a network analysis result.

[0155] As can be seen from the above, in the technical solution provided by the embodiment of the present application, by converting the rule information input by the user into a rule template recognizable by a preset rule engine, the network management platform can implement automated parsing of service data by invoking the rule engine. Moreover, the controller instructs whether the network device enables the in-flow detection service by sending configuration information to the network device, so that the network device that enables the in-flow detection service collects and reports service data in real time. Therefore, no manual intervention is required from collecting service data to network analysis based on service data, and the scalability of the rule template allows the user to define analysis rules from multiple dimensions such as latency, packet loss rate, and bandwidth utilization rate. Combined with the rule engine of the network management platform, different scenario requirements can be flexibly adapted, thereby realizing intelligent analysis of network quality, and significantly improving the efficiency and accuracy of network analysis.

[0156] In the network analysis method provided by the embodiment of the present application, the execution subject may be a terminal access terminal. In the embodiment of the present application, the method of terminal access executed by the terminal access terminal is taken as an example to illustrate the device of the network analysis method provided by the embodiment of the present application.

[0157] Figure 8 FIG. is a flowchart of a network analysis system shown according to an exemplary embodiment. The system includes a network management platform and a controller, where:

[0158] The network management platform is configured to obtain rule information input by a user and configuration information of each network device; send the rule information and the configuration information to the controller;

[0159] A controller, configured to convert rule information into a rule template recognizable by a preset rule engine; obtain configuration information of each network device, and send the configuration information to the corresponding network device, where the configuration information is used to indicate whether the corresponding network device enables the in-flow detection service; receive service data reported by the network device that enables the in-flow detection service, and forward the service data to the network management platform;

[0160] The network management platform is further configured to call the preset rule engine to parse the service data based on the rule template to obtain a network analysis result.

[0161] As can be seen from the above, in the technical solution provided by the embodiment of the present application, by converting the rule information input by the user into a rule template recognizable by the preset rule engine, the network management platform can implement automatic parsing of service data by calling the rule engine. Moreover, the controller sends configuration information to the network device to indicate whether the network device enables the in-flow detection service, so that the network device that enables the in-flow detection service collects and reports service data in real time. Therefore, no manual intervention is required from collecting service data to network analysis based on service data, and the scalability of the rule template allows users to define analysis rules from multiple dimensions such as delay, packet loss rate, and bandwidth utilization rate. Combined with the rule engine of the network management platform, different scenario requirements can be flexibly adapted, thereby realizing intelligent analysis of network quality, and significantly improving the efficiency and accuracy of network analysis.

[0162] The network analysis device in the embodiment of the present application may be an electronic device or a component in an electronic device, such as an integrated circuit or a chip. The electronic device may be a terminal or other devices other than the terminal. Exemplarily, the electronic device may be a mobile phone, a tablet computer, a laptop computer, a handheld computer, a vehicle-mounted electronic device, a Mobile Internet Device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc. It may also be a server, a Network Attached Storage (NAS), a personal computer (PC), a television (TV), a teller machine, or a self-service machine, etc. The embodiment of the present application does not make a specific limitation.

[0163] The network analysis device provided by the embodiment of the present application can implement Figures 1 to 5The various processes implemented by the method embodiments will not be elaborated here to avoid repetition.

[0164] Optionally, as Figure 9 shown, an embodiment of the present application further provides an electronic device 500, including a processor 501 and a memory 502. A program or instruction that can run on the processor 501 is stored on the memory 502. When the program or instruction is executed by the processor 501, it implements the various steps of the above network analysis method embodiment and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0165] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0166] Figure 10 It is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present application.

[0167] The electronic device 1000 includes but is not limited to: a radio frequency unit 1001, a network module 1002, an audio output unit 1003, an input unit 1004, a sensor 1005, a display unit 1006, a user input unit 1007, an interface unit 1008, a memory 1009, and a processor 1010, etc.

[0168] Those skilled in the art can understand that the electronic device 1000 may further include a power supply (such as a battery) for powering each component. The power supply can be logically connected to the processor 1010 through a power management system, so as to implement functions such as management of charging, discharging, and power consumption management through the power management system. Figure 10 The electronic device structure shown in does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0169] As can be seen from the above, the technical solution provided by the embodiment of the present application converts the rule information input by the user into a rule template recognizable by the preset rule engine, enabling the network management platform to realize automatic parsing of service data by calling the rule engine. Moreover, the controller issues configuration information to the network device to indicate whether the network device starts the flow detection service, so that the network device that starts the flow detection service can collect and report service data in real time. Therefore, from the collection of service data to the network analysis based on service data, no manual intervention is required, and the scalability of the rule template allows users to define analysis rules from multiple dimensions such as delay, packet loss rate, and bandwidth utilization rate, and flexibly adapt to different scenario requirements in combination with the rule engine of the network management platform, so as to realize intelligent analysis of network quality, and the efficiency and accuracy of network analysis are significantly improved.

[0170] It should be understood that in the embodiments of the present application, the input unit 1004 may include a Graphics Processing Unit (GPU) 10041 and a microphone 10042. The graphics processor 10041 processes the image data of static pictures or videos obtained by an image capturing device (such as a camera) in a video capture mode or an image capture mode. The display unit 1006 may include a display panel 10061, and the display panel 10061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1007 includes at least one of a touch panel 10071 and other input devices 10072. The touch panel 10071 is also referred to as a touch screen. The touch panel 10071 may include two parts, a touch detection device and a touch controller. The other input devices 10072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be elaborated herein.

[0171] The memory 1009 can be used to store software programs and various data. The memory 1009 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data. Among them, the first storage area may store an operating system, application programs or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 1009 may include a volatile memory or a non-volatile memory, or the memory 1009 may include both a volatile memory and a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDR SDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synch link dynamic random access memory (SLDRAM), and a direct rambus random access memory (DRRAM). The memory 109 in the embodiments of the present application includes but is not limited to these and any other suitable types of memories.

[0172] The processor 1010 may include one or more processing units; optionally, the processor 1010 integrates an application processor and a modem processor. Among them, the application processor mainly processes operations related to the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communication signals, such as a baseband processor. It can be understood that the above modem processor may not be integrated into the processor 1010 either.

[0173] The embodiments of the present application also provide a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements each process of the above-mentioned embodiment of the network analysis method and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0174] Among them, the processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media such as computer read-only memory ROM, random access memory RAM, magnetic disks, or optical discs.

[0175] Another embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement each process of the above embodiment of the network analysis method, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0176] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip.

[0177] The embodiments of the present application provide a computer program product. The program product is stored in a storage medium and is executed by at least one processor to implement each process of the above embodiment of the network analysis method, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0178] It should be noted that in this article, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article, or device. Without more limitations, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article, or device including that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the reverse order according to the functions involved. For example, the described methods may be executed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0179] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence or the part that contributes to the prior art, can be embodied in the form of a computer software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present application.

[0180] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them belong to the protection scope of the present application.

Claims

1. A network analysis method, characterized in that, Applied to a controller, the method includes: Obtain the rule information input by the user and convert the rule information into a rule template recognizable by a preset rule engine; Obtain the configuration information of each network device and send the configuration information to the corresponding network device. The configuration information is used to indicate whether the corresponding network device enables the flow monitoring service; Receive the service data reported by the network device that enables the flow monitoring service and forward the service data to the network management platform. The network management platform is used to parse the service data based on the rule template by invoking the preset rule engine to obtain a network analysis result.

2. The network analysis method according to claim 1, wherein After converting the rule information into a rule template recognizable by a preset rule engine, it further includes: Store the rule template in a preset rule library so that the network management platform can obtain the rule template from the preset rule library.

3. The network analysis method according to claim 1, characterized in that Sending the configuration information to the corresponding network device includes: Encapsulate the configuration information into a configuration template according to a preset network management protocol; Send the configuration template to the corresponding network device so that the network device determines whether to enable the flow monitoring service based on the configuration template.

4. The network analysis method according to claim 1, wherein Forwarding the service data to the network management platform includes: Forward the service data to the network management platform through a Kafka message middleware.

5. A network analysis method, characterized in that, Applied to a network management platform, the method includes: Obtain the rule information input by the user and the configuration information of each network device; Send the rule information and the configuration information to the controller. The controller is used to convert the rule information into a rule template recognizable by a preset rule engine and is also used to configure whether the corresponding network device reports service data based on the configuration information; Receive the service data sent by the controller and invoke the preset rule engine to parse the service data based on the rule template to obtain a network analysis result.

6. The network analysis method according to claim 5, wherein Obtaining the rule information input by the user includes: Interact with the user through a visual interface to obtain the rule information input by the user.

7. The network analysis method according to claim 5, wherein Invoking the preset rule engine to parse the service data based on the rule template to obtain a network analysis result includes: Parse the service data according to a performance index algorithm to obtain performance index data; Invoke the preset rule engine to match the performance index data based on the rule template to obtain a network analysis result.

8. A network analysis device, characterized in that, Applied to a controller, the device includes: A conversion module, configured to obtain the rule information input by the user and convert the rule information into a rule template recognizable by a preset rule engine; A configuration module, configured to obtain the configuration information of each network device and send the configuration information to the corresponding network device. The configuration information is used to indicate whether the corresponding network device enables the flow monitoring service; A forwarding module, configured to receive the service data reported by the network device that enables the flow monitoring service and forward the service data to the network management platform. The network management platform is used to parse the service data based on the rule template by invoking the preset rule engine to obtain a network analysis result.

9. A network analysis device, characterized in that, Applied to a network management platform, the device includes: An acquisition module, configured to acquire rule information input by a user and configuration information of each network device; A sending module, configured to send the rule information and the configuration information to a controller, where the controller is configured to convert the rule information into a rule template recognizable by a preset rule engine, and is further configured to configure whether a corresponding network device reports service data based on the configuration information; An analysis module, configured to receive service data sent by the controller, and call the preset rule engine to analyze the service data based on the rule template to obtain a network analysis result.

10. A network analysis system, characterized in that, It includes a network management platform and a controller, where: The network management platform is configured to acquire rule information input by a user and configuration information of each network device; send the rule information and the configuration information to the controller; The controller is configured to convert the rule information into a rule template recognizable by a preset rule engine; acquire configuration information of each network device, and send the configuration information to the corresponding network device, where the configuration information is used to indicate whether the corresponding network device enables the flow monitoring service; receive service data reported by the network device that enables the flow monitoring service, and forward the service data to the network management platform; The network management platform is further configured to call the preset rule engine to analyze the service data based on the rule template to obtain a network analysis result.

11. An electronic device, characterized in that, It includes: A processor; A memory for storing executable instructions of the processor; Wherein, the processor is configured to execute the instructions to implement the network analysis method according to any one of claims 1 to 7.

12. A readable storage medium, characterized in that, A program or instructions are stored on the readable storage medium, and when the program or instructions are executed by the processor, the steps of the network analysis method according to any one of claims 1-7 are implemented.

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