Network management system and method based on rule control

Abstract

The embodiment of the invention relates to the technical field of network operation and maintenance, in particular to a network management system and method based on rule control. The rule engine module is introduced into the network management system, the operation and maintenance efficiency is remarkably improved through an automatic and intelligent rule engine, errors caused by human intervention are reduced, the safety and stability of the whole network are improved, and the operation and maintenance efficiency is improved. Based on cooperative work of a dynamic management and control mechanism of rules, application of a machine learning algorithm in equipment management, a real-time data analysis and alarm feedback mechanism, visual display of a user interface and other technologies, an efficient and flexible network operation and maintenance system is jointly formed. A rule-based dynamic management and control mechanism ensures the safety and compliance of operation, and the application of a machine learning algorithm enables the equipment management to be more intelligent, and the rule and decision process can be continuously optimized according to historical data.

Description

Technical Field

[0001] The present invention relates to the field of network operation and maintenance technology, and in particular to a network management system and method based on rule control. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention recited in the claims. No admission is made that the description herein is prior art by inclusion in this section.

[0003] As enterprise networks continue to expand and become more complex, network operation and management are facing more and more challenges. Traditional network operation and maintenance systems usually rely on manual monitoring and manual operations, which is not only inefficient but also prone to errors. Summary of the invention

[0004] The present invention solves many problems faced by traditional network operation and maintenance systems that usually rely on manual monitoring and manual operation, proposes network management based on rule control, and realizes intelligent analysis of network status.

[0005] In order to achieve the above object, the present invention adopts the following technical solution.

[0006] First, on the one hand, the present invention provides a network management system based on rule control, including a network monitoring module and a rule engine module, wherein the network monitoring module is used to monitor the operating status and performance data of network equipment in real time, and transmit the operating status and performance data to the rule engine module, and the rule engine module is used to set and manage the rule set of network equipment, and perform status evaluation on the network equipment according to the rule set and the operating status and performance data of the network equipment.

[0007] In some embodiments, the rule set includes a network device rule set, which includes security configuration standards, access standards, performance indicators, status classification sets, status danger level sets and / or status alarm levels of the network device.

[0008] In some embodiments, the network management system also includes a remote control module for operation and maintenance personnel to remotely configure, modify and / or troubleshoot network equipment. The remote control module is electrically connected to the rule engine module and is used to transmit received operation instructions to the rule engine module, and the rule engine module evaluates the safety and compliance of the operation instructions.

[0009] Furthermore, the rule set also includes a command rule set, and the command rule set includes an operation requirement, a command classification set, a command danger level set and / or a command warning level.

[0010] In some embodiments of the present invention, the rule engine module includes a storage module and a self-learning module. The storage module is used to store the status evaluation results of the network device and / or the evaluation results of the operation instructions. The self-learning module is used to perform self-learning according to the evaluation results and adjust the rule set according to the self-learning results.

[0011] In some embodiments, the system also includes a display module connected to the rule engine module, which is used to visualize the data output by the rule engine module and display the operating status, traffic distribution, performance indicators, network topology, alarm information and / or operational rectification suggestions of network equipment.

[0012] On the other hand, the present invention also provides a network management method based on rule control, which is implemented based on the above-mentioned network management system, including: a network monitoring module obtains the operating status and performance data of the network device in real time, and transmits the operating status and performance data to a rule engine module; the rule engine module analyzes and judges according to the rule set, evaluates whether the network device status complies with the rules, and generates a corresponding network device status evaluation result. If it complies with the rules, it outputs a compliant result; if it does not comply with the rules, it generates an alarm message, wherein the rule set includes a network device rule set, and the network device rule set includes security configuration standards, access standards, performance indicators, status requirements, status classification sets, status danger level sets and / or status alarm levels of network devices.

[0013] Furthermore, the above method also includes: the remote control module obtains the operation instruction and transmits it to the rule engine module; the rule engine module evaluates the security and compliance of the operation instruction according to the rule set, and generates an evaluation result. If it is a low-risk operation, an authorization application window pops up; if it is a high-risk operation, the execution is refused and an alarm message is output, and corresponding rectification suggestions are given, wherein the rule set also includes a command rule set, and the command rule set includes operation requirements, command classification set, command danger level set and / or command alarm level.

[0014] Furthermore, the above method also includes: the rule engine module stores the status evaluation results of the network device and / or the evaluation results of the operation instructions, performs self-learning according to the evaluation results, and updates the rule set according to the self-learning results.

[0015] Furthermore, the above method also includes: the rule engine module transmits the status evaluation result of the network device and / or the evaluation result of the operation instruction to the display module, and the display module visualizes and displays the data output by the rule engine module.

[0016] Beneficial effects of the present invention:

[0017] The present invention introduces a rule engine module into the network management system, significantly improves the operation and maintenance efficiency through an automated and intelligent rule engine, reduces errors caused by human intervention, improves the security and stability of the overall network, and works together to form an efficient and flexible network operation and maintenance system based on a rule-based dynamic control mechanism, the application of machine learning algorithms in device management, real-time data analysis and alarm feedback mechanisms, and visual display of user interfaces. The dynamic control mechanism based on rules ensures the safety and compliance of operations, while the application of machine learning algorithms makes device management more intelligent and can continuously optimize the decision-making process based on historical data. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 Schematic diagram of a network management system based on rule control according to Embodiment 1 of the present invention;

[0020] Figure 2 It is a schematic diagram of a network management method based on rule control according to Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0021] With the continuous expansion and complexity of enterprise networks, network operation and management are facing more and more challenges. Traditional network operation and maintenance systems usually rely on manual monitoring and manual operation, which is not only inefficient but also prone to errors. In order to solve these problems, the present invention proposes an innovative integrated management system, which realizes intelligent analysis of network status by introducing rule engine function.

[0022] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0023] It should be noted that, under the premise of no conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments, which also fall within the scope of protection of the present invention.

[0024] In the description of the present invention, the following terms need to be explained:

[0025] As for directional words, the terms "center", "lateral", "longitudinal", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicating directions and positional relationships in the specification and claims of this application are based on the directions or positional relationships shown in the drawings and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and should not be understood as limiting the specific scope of protection of the present invention.

[0026] The terms "first", "second", etc. in the description and claims of the present application are used to distinguish similar objects and are not necessarily used to describe a particular sequence or order.

[0027] The terms "including" and "having" and any variations thereof in the specification and claims of this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0028] When an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or there may be an intermediate element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element. When an element is referred to as being "provided with" another element, it may be provided on the surface or inside of the element.

[0029] Unless explicitly stated otherwise, throughout the specification and claims, the term “comprise” or variations such as “include” or “comprising”, etc., will be understood to include the stated elements or components but not to exclude other elements or components.

[0030] The term "electrical connection" in the specification and claims of this application may refer to a circuit connection with physical contact or a communication connection, which may be a wired communication connection or a wireless communication connection.

[0031] Example 1

[0032] First, this embodiment provides a network management system based on rule control, such as Figure 1As shown, it includes a network monitoring module and a rule engine module. The network monitoring module is used to monitor the operating status and performance data of the network equipment in real time, and transmit the operating status and performance data to the rule engine module. The rule engine module is used to set and manage the rule set of the network equipment, and perform status evaluation on the network equipment according to the rule set and the operating status and performance data of the network equipment.

[0033] Network equipment is the infrastructure of this system. It mainly uses switches, firewalls, servers and other network devices to form a modern enterprise network through traditional Ethernet technologies such as VLAN, OSPF, VRRP, etc., and uses SNMP, sF l ow, SSH and other protocols to monitor and manage network equipment in real time.

[0034] The rule engine module is the core part of this embodiment, responsible for intelligent processing of network equipment management and operation and maintenance decisions. By introducing the random forest model in machine learning, the rule engine can effectively improve the accuracy and intelligence level of equipment status assessment. This module sets and manages rule sets for various types of network equipment, including network equipment rule sets, which include network equipment rule sets, security configuration standards, access standards, performance indicators, status classification sets, status danger level sets and / or status alarm levels, status alarm methods, etc. for network equipment. The system flexibly configures rules according to the characteristics and usage scenarios of different devices. Through long-term continuous learning and optimization, the rule engine module can adapt to the ever-changing network environment and provide enterprises with more efficient and secure operation and maintenance solutions.

[0035] The network monitoring module can use SNMP, SF low and other monitoring management protocols to monitor the operating status and performance data of network devices in real time. It can collect and integrate real-time data from various network devices, such as traffic, bandwidth usage, device load, etc., and transmit these data to the rule engine module, which will evaluate the status of network devices based on its internal rule set and the operating status and performance data of the above network devices. At the same time, the network monitoring module can also warn and notify abnormal events to ensure that administrators can discover and handle network failures in a timely manner.

[0036] The network management system of this embodiment builds an automated and intelligent network operation and maintenance solution through the combination of the rule engine module and the network monitoring module. The rule engine module is the core of the system, and can learn a large amount of historical data through a machine learning algorithm model to provide the system with more accurate and reasonable rules and rule judgment analysis. Specifically, optionally, this embodiment can also introduce a computing power model on the rule engine module, and use the powerful computing power and learning ability of computing power to enable the integrated management system to more accurately and accurately identify abnormal behaviors, dynamically adjust and optimize the rule set. The overall intelligence level of the integrated management system is further improved, so that abnormal behaviors and potential threats can be detected more effectively. For newly connected devices, the system will automatically check whether its configuration meets the preset standards. If not, it will issue an alarm and issue reasonable rectification suggestions. For existing devices managed by the remote management module, the system will perform a rule check on the input command content, and determine whether the input can be executed based on the preset rules and the machine learning rule library.

[0037] The automation and intelligent rule engine significantly improves operation and maintenance efficiency, reduces errors caused by human intervention, and improves the security and stability of the overall network. The flexibility and scalability of the system also enable it to adapt to the ever-changing network environment, providing an efficient, secure and reliable network management solution for modern enterprise networks.

[0038] Existing technologies have obvious shortcomings in terms of intelligence and security. In terms of intelligence, traditional network monitoring technology can often only provide basic equipment status information, such as the online status of the equipment, simple performance indicators, etc. However, with the increasing complexity and variability of the network environment, this simple monitoring method can no longer meet the requirements for intelligent analysis and processing capabilities of deep, multi-dimensional network data. In terms of security, permission management technology also faces challenges. Traditional permission management technology can usually only achieve basic role permission division, that is, assigning different permissions according to the user's role. In a complex and changeable network environment, this simple permission management method can no longer meet the needs of refined management, and cannot effectively prevent security risks such as information leakage and data tampering.

[0039] Optionally, in some embodiments, the network management system further includes a remote control module for operation and maintenance personnel to remotely configure, modify and / or troubleshoot network equipment. The remote control module is electrically connected to the rule engine module and is used to transmit the received operation instructions to the rule engine module, and the rule engine module evaluates the security and compliance of the operation instructions. The remote control module is mainly responsible for providing a secure remote connection, allowing operation and maintenance personnel to configure, modify and troubleshoot network equipment. This management method does not require the identity or ID of the operator, but only needs to analyze the input operation instructions. As long as the instructions are compliant and safe, the instructions will be executed, thereby fundamentally avoiding the cumbersome management procedures such as identification, management, and update of the operator's identity, and also avoiding the situation where the system is illegally invaded for dangerous operations and the system cannot identify the operator's identity information being forged or the verification password being stolen. The loss caused to the system in this case is unimaginable and irreversible, such as deleting data, copying data, and disclosing data. In this embodiment, all remote operations must be reviewed by the rule engine to ensure compliance with security policies, thereby avoiding potential risks. It is also necessary to record all operation logs of network devices in real time and save the operation steps and the results returned by the operation in the form of video.

[0040] The remote control module introduces a remote rule control function to the system. Accordingly, in order to improve the security of the system, the rule engine module also introduces operation instruction judgment. Accordingly, the rule set also includes a command rule set, which includes operation requirements, command classification sets, command danger level sets and / or command alarm levels. This rule-based management and control mechanism effectively improves the security and efficiency of network operation and maintenance, and prevents situations where there is no authority or there is authority but malicious or misoperation. When the system detects a high-risk operation, it can immediately refuse to execute and issue an alarm to reduce potential security risks, while low-risk operations can apply for authorization after triggering the rules to ensure the flexibility and timeliness of operation and maintenance operations. In addition, the network monitoring module continuously collects and analyzes the status and performance data of network equipment. Combined with the real-time visual interface provided by the large-screen display module, operation and maintenance personnel can more intuitively monitor the network operation status and process alarm information, so as to quickly respond and make decisions.

[0041] Specifically, the judgment of low-risk operation and high-risk operation is relative and dynamically changing. The operations allowed under different states of the device are different, and the risk level of the same operation under different states may also be different. That is to say, the rule engine module will dynamically analyze and judge the operation instructions transmitted by the remote control module based on the operating status and performance data of the network device uploaded by the network monitoring module at this time for each operation instruction. The rule engine module can also actively obtain the operating status and performance data of the network device at this time after receiving the operation instruction. The specific operation includes: receiving the operation instruction, disassembling and analyzing the operation instruction, the operation instruction at least includes the target device code, action content, execution time, and execution duration, and then obtaining the content of the entire device status rule set, analyzing the content and sorting of the task queue of the target device in a certain period of time in the future, and obtaining the current operating status and performance parameters of the target device and related devices. The related device is a device that needs or may need to interact with the target device or replace each other. According to the current operating status and performance parameters of the target device and related devices, as well as the content and sorting of the task queue of the target device in a certain period of time in the future, the operation instruction is analyzed to determine whether the instruction can be executed and the risk level, and then output to the display large screen for display.

[0042] In order to facilitate the operation and maintenance personnel to quickly and easily understand the equipment status and operation instruction judgment, in some embodiments, the system also includes a display module, which mainly provides an intuitive visual interface for the data output by the rule engine module, and displays the status, alarm information and operation and maintenance log of the network equipment in real time. By displaying network traffic, performance indicators and alarm information through charts and graphics, it helps the operation and maintenance personnel to quickly grasp the network operation status, handle alarm events in a timely manner, and improve management efficiency. Specifically, the display module of this embodiment is a large-screen display module, which displays the operation status, traffic distribution, performance indicators, network topology, alarm information and / or operation rectification suggestions of network equipment to the administrator in a visual manner through the large screen.

[0043] Traditional network management systems usually rely on static rules, which are prone to misjudgment and delayed response. Therefore, in some implementations, through dynamic learning and adaptive adjustment, the system can analyze device status and user operations in real time, thereby making more accurate decisions and effectively reducing potential security risks. Specifically, a storage module and a self-learning module can be set in the rule engine module. The storage module is used to store the status evaluation results of network devices and / or the evaluation results of operation instructions. The self-learning module is used to perform self-learning based on the evaluation results and adjust the rule set based on the self-learning results. All device status evaluation results and related parameters, as well as all operations and evaluation demerits, will be recorded in the rule engine module for long-term and continuous learning, and the rule set will be updated in time according to each learning result to improve the system's adaptability.

[0044] On the other hand, this embodiment also provides a network management method based on rule control, which is implemented based on the above network management system. Figure 2 As shown, the specific steps include:

[0045] S1: The network monitoring module obtains the operating status and performance data of the network device in real time, and transmits the operating status and performance data to the rule engine module;

[0046] S2: The rule engine module analyzes and judges according to the rule set, evaluates whether the network device status complies with the rules, and generates a status evaluation result of the corresponding network device. If it complies with the rules, it outputs the compliance result; if it does not comply with the rules, it generates an alarm message, wherein the rule set includes a network device rule set, and the network device rule set includes security configuration standards, access standards, performance indicators, status classification sets, status danger level sets and / or status alarm levels of network devices.

[0047] When the system includes a remote control module and has a remote operation instruction judgment function, the above method also includes:

[0048] S3: The remote control module obtains the operation instruction and transmits it to the rule engine module; the rule engine module evaluates the security and compliance of the operation instruction according to the rule set and generates an evaluation result. If it is a low-risk operation, an authorization application window pops up; if it is a high-risk operation, the execution is refused and an alarm message is output, and corresponding rectification suggestions are given, wherein the rule set also includes a command rule set, and the command rule set includes operation requirements, command classification set, command danger level set and / or command alarm level.

[0049] When the system has a self-learning function, the method further includes:

[0050] S4: The rule engine module stores the status evaluation results of the network device and / or the evaluation results of the operation instructions, performs self-learning according to the evaluation results, and adjusts the rule set according to the self-learning results.

[0051] The rule engine module receives data from the network monitoring module and the remote control module in real time. This data may include the operation data of the equipment, the operation records of the operation and maintenance personnel, etc. After receiving this data, the rule engine module analyzes and judges according to the rule set, evaluates whether the equipment status complies with the rules, whether the command has risks, and generates corresponding analysis results. For operations that do not comply with the rules or have risks, the module will generate alarm information and give corresponding rectification suggestions. All operations will be recorded in the rule engine module for long-term continuous learning.

[0052] When the system includes a display module, the method further includes:

[0053] S5: The rule engine module transmits the status assessment results of the network device and / or the assessment results of the operation instruction to the display module, and the display module performs visual processing and display on the data output by the rule engine module. The device status assessment results and the data that conforms to the rules will also be sorted by the rule engine module and fed back to the large-screen display module. The rectification suggestions generated after the high-risk operation is rejected will also be fed back to the large-screen display module.

[0054] After receiving the data fed back by the rule engine module, the large-screen display module performs visualization processing. Through charts and graphs, the operating status, traffic distribution, performance indicators, network topology and alarm information of network devices are displayed in real time. When the system detects situations that do not comply with the rules or high-risk commands, the large-screen display module will present the alarm information and rectification suggestions in an intuitive way. At the same time, the alarm information and rectification suggestions will also be sent to relevant operation and maintenance personnel through preset methods (such as pop-up windows, WeChat, SMS or email) to ensure that they can respond and handle them in a timely manner.

[0055] When the operation and maintenance personnel optimize the configuration of the network equipment, the above method also includes:

[0056] S6: Operation and maintenance personnel optimize the configuration of network equipment;

[0057] After receiving the alarm information and rectification suggestions, the operation and maintenance personnel will analyze and make decisions based on the detailed data provided by the large-screen display module. They will optimize and adjust the network equipment through the remote control module to ensure that the equipment configuration meets the safety and performance standards and correct the existing risks and problems. The optimized equipment status and configuration will be collected again by the network monitoring module and fed back to the rule engine for re-evaluation to ensure that the equipment is always in the best operating state.

[0058] Specifically, when the system judges the operation instructions of the operation and maintenance personnel, the judgment of low-risk operations and high-risk operations is relative and dynamically changing. The operations allowed under different states of the equipment are different, and the risk level of the same operation under different states may also be different. That is to say, the rule engine module will dynamically analyze and judge the operation instructions transmitted by the remote control module based on the operation status and performance data of the network device uploaded by the network monitoring module at this time for each operation instruction, and can also actively obtain the operation status and performance data of the network device at this time after receiving the operation instruction. The specific operation includes: receiving the operation instruction, disassembling and analyzing the operation instruction, the operation instruction at least includes the target device code, action content, execution time, and execution duration, and then obtaining the content of the entire device status rule set, analyzing the content and sorting of the task queue of the target device in a certain period of time in the future, and obtaining the current operation status and performance parameters of the target device and related devices. The related equipment is a device that needs or may need to interact with the target device or replace each other. According to the current operation status and performance parameters of the target device and related devices, as well as the content and sorting of the task queue of the target device in a certain period of time in the future, the operation instruction is analyzed to determine whether the instruction can be executed and the risk level, and then output to the display large screen for display. For example, the content of the operation instruction is that device A needs to be shut down and replaced, and the system obtains that there is important information to be transmitted in the task queue of device A. Then the system obtains that device A is seriously heated at this time, exceeding the preset threshold. However, combined with the content of the task queue, device A cannot be shut down at this time, otherwise important information will be lost. The system will actively obtain the heating status of device B, which is the replacement of device A. If the status of device B is normal, it will switch to device B, and simultaneously transmit the task queue of device A to device B, and device B will take over to complete the work of device A. If device B is also seriously heated, or is about to reach the preset threshold of heating, the system will start the heat dissipation device near device A to dissipate heat for device A to ensure that device A completes the current transmission task. Optionally, the system can also further analyze the execution time and execution duration in the instruction. For example, assuming that the current heating temperature of device A has not exceeded the standard, but according to the execution time and execution duration in the operation instruction, the heating of device A may exceed the threshold during the execution time or execution duration. At this time, the system should reject the instruction, and judge the time and duration when the instruction can be executed according to the heating condition of device A or the progress of task transmission, and form an improvement plan and send it to the operator.

[0059] In actual application, before implementing the above method, a suitable rule engine module should be designed, including:

[0060] S01: Rule engine module initialization and training

[0061] The rule engine module initialization requires setting detailed general rule sets for various types of network devices. The rule set includes the device's security configuration standards, performance indicators, and operation requirements. The various commands in the rule set are classified, and the danger level is set according to their potential risks. Different alarm methods are set, such as information pop-ups, WeChat notifications, and email notifications.

[0062] In order to make the rule engine module more suitable for the existing network environment, the rule engine module needs to be trained and learned.

[0063] First, in the data collection and preprocessing phase, the system continuously monitors and collects the status and performance data of network devices, while recording the history of operation and maintenance operations. These raw data are cleaned, converted, and standardized to ensure that their format is uniform and suitable for input into machine learning models. This process is the basis for building an effective model and ensuring the accuracy of subsequent analysis.

[0064] Next, we enter the model training phase, where the rule engine module uses the random forest algorithm to train the preprocessed historical data. By analyzing the features and labels in the data, the random forest model can learn the potential patterns and relationships of different operations. During the model training process, the system will continuously adjust the algorithm parameters and select the best features to optimize the model performance, thereby improving its prediction and classification capabilities in operation and maintenance operations.

[0065] Finally, the rule engine module enters the rule generation and integration phase. At this stage, the prediction or classification results of the machine learning model are converted into rules and threshold conditions that can be recognized by the rule engine module. These rules generated based on machine learning are combined with the original business rules to form a more comprehensive rule set. The integrated rule set plays a synergistic role in the system's decision-making process to improve the accuracy and flexibility of judgment.

[0066] When a new device is added to the system, the method further includes:

[0067] S02: The network device is added to the network monitoring module and the remote control module;

[0068] Newly connected network devices are first added to the network monitoring module for real-time monitoring. The network monitoring module continuously collects device status information, including configuration, operating status, traffic, and performance indicators. At the same time, the device is added to the remote control module, allowing operation and maintenance personnel to manage the device through a secure remote connection. The remote control module provides a command input interface and ensures that all commands are reviewed by the rule engine module.

[0069] It is worth noting that the steps of the above method do not limit the implementation order of the various parts of the method of the present invention, but are only one of the implementation methods. Other implementation orders are also within the protection scope of the present invention.

[0070] The present invention introduces an intelligent rule engine module, which significantly improves the decision-making ability and flexibility of network equipment management by integrating machine learning technology - random forest model. The present invention covers various components of the system and their functions, including rule-based dynamic control mechanism, application of machine learning algorithm in equipment management, real-time data analysis and alarm feedback mechanism, and visual display of user interface. These components work together to form an efficient and flexible network operation and maintenance system. The rule-based dynamic control mechanism ensures the safety and compliance of operations, while the application of machine learning algorithm makes equipment management more intelligent and can continuously optimize the decision-making process based on historical data.

[0071] In order to improve the applicability of the system and make it applicable to a variety of devices, in some implementations, the compatibility of devices can be expanded to support more types of network devices and protocols, and the adaptability and expansibility of the system can be enhanced through modular design and open interfaces. For example, network devices are classified according to device type or protocol, and rule sets are also divided according to the classification of network devices to form rule sets with different rule contents. Different rule sets are used to manage different categories of devices, thereby improving compatibility.

[0072] In order to improve the real-time performance, monitoring capability, monitoring range and processing efficiency of the system, in some implementations, edge computing technology is introduced to deploy the Agent of the network monitoring module on the edge node of the network device that needs to be monitored, greatly enhancing the real-time performance and efficiency of the monitoring capability of the integrated management system. Edge computing technology allows data processing and analysis to be performed closer to the data source. Compared with the traditional centralized data processing method, the deployment of edge nodes can significantly reduce data transmission delays and improve the response speed and processing speed of the network management system.

[0073] Finally, it should be pointed out that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the above embodiments, a person skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features can be replaced by equivalents, and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A network management system based on rule control, characterized in that: It includes a network monitoring module and a rule engine module. The network monitoring module is used to monitor the operating status and performance data of network equipment in real time and transmit the operating status and performance data to the rule engine module. The rule engine module is used to set and manage the rule set of network equipment and perform status evaluation on the network equipment according to the rule set and the operating status and performance data of the network equipment.

2. The network management system according to claim 1, characterized in that: The rule set includes a network device rule set, and the network device rule set includes security configuration standards, access standards, performance indicators, status classification sets, status danger level sets and / or status alarm levels of network devices.

3. The network management system according to claim 2, characterized in that: The network management system also includes a remote control module for operation and maintenance personnel to remotely configure, modify and / or troubleshoot network equipment. The remote control module is electrically connected to the rule engine module and is used to transmit received operation instructions to the rule engine module, which evaluates the safety and compliance of the operation instructions.

4. The network management system according to claim 3, characterized in that: The rule set also includes a command rule set, which includes an operation requirement, a command classification set, a command danger level set and / or a command warning level.

5. The network management system according to claim 4, characterized in that: The rule engine module includes a storage module and a self-learning module. The storage module is used to store the status evaluation results of the network device and / or the evaluation results of the operation instructions. The self-learning module is used to perform self-learning according to the evaluation results and adjust the rule set according to the self-learning results.

6. The network management system according to claim 5, characterized in that: The system also includes a display module, which is connected to the rule engine module and is used to visualize the data output by the rule engine module to display the operating status, traffic distribution, performance indicators, network topology, alarm information and / or operational rectification suggestions of network devices.

7. A network management method based on rule control, implemented based on the network management system according to any one of claims 1 to 6, characterized in that: include: The network monitoring module obtains the operating status and performance data of the network equipment in real time, and transmits the operating status and performance data to the rule engine module; The rule engine module analyzes and judges according to the rule set, evaluates whether the network device status complies with the rules, and generates a status evaluation result of the corresponding network device. If it complies with the rules, it outputs the compliance result; if it does not comply with the rules, it generates an alarm message, wherein the rule set includes a network device rule set, and the network device rule set includes security configuration standards, access standards, performance indicators, status requirements, status classification sets, status danger level sets and / or status alarm levels of network devices.

8. The network management method according to claim 7, characterized in that: Also includes: The remote control module obtains the operation instruction and transmits it to the rule engine module; The rule engine module evaluates the security and compliance of the operation instructions according to the rule set and generates an evaluation result. If it is a low-risk operation, an authorization application window will pop up. If it is a high-risk operation, the execution will be refused and an alarm message will be output, and corresponding rectification suggestions will be given. The rule set also includes a command rule set, which includes operation requirements, command classification sets, command danger level sets and / or command alarm levels.

9. The network management method according to claim 8, characterized in that: Also includes: The rule engine module stores the status evaluation results of the network device and / or the evaluation results of the operation instructions, performs self-learning according to the evaluation results, and updates the rule set according to the self-learning results.

10. The network management method according to claim 9, characterized in that: Also includes: The rule engine module transmits the status evaluation result of the network device and / or the evaluation result of the operation instruction to the display module, and the display module performs visual processing and display on the data output by the rule engine module.

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