A method and system for automatically discovering the entire network topology

Abstract

The present invention relates to the field of network security, and discloses a method and system for automatic discovery of the topology of the entire network, the method comprising: analyzing the resource functions and resource attributes of a resource object, constructing a description language of the resource object, and determining a description method of the resource object; determining the resource object type of the resource object, constructing an inheritance relationship of the resource object type, and analyzing the association relationship of the resource object type, and constructing a resource object model of the resource object; constructing an automatic discovery algorithm of the network, and constructing a network topology model of the network; using a preset graph database technology to analyze the entire topology structure, adjusting the network configuration of the network topology model, and constructing an autonomous mechanism of the network topology model, mapping the network configuration and the autonomous mechanism to the network topology model, integrating the optimized network topology model and the resource object model into a resource object management model, and realizing the full life cycle management of the resource object. The present invention can improve the effect of automatic discovery of the topology of the entire network.

Description

Technical Field

[0001] The present invention relates to the field of network security, and in particular to a method and system for automatically discovering the topology of a whole network. Background Art

[0002] Automatic discovery of the entire network topology refers to the process of automatically detecting nodes and connection relationships in the network through network protocols and algorithms, and generating a network topology map. This can help to intuitively understand the operating status of current network devices, accurately locate fault points in the network, and provide basic data for analyzing network problems, thereby optimizing network performance.

[0003] At present, the method of automatic discovery of the entire network topology is mainly based on the discovery method of SNMP (Simple Network Management Protocol). This method obtains information by accessing the MIB library in network devices such as switches and routers, resulting in an unstable discovery rate. In many cases, the discovery rate is so low that it cannot be used. Or it only pursues a certain goal of automatic topology discovery, such as speed, while ignoring other key factors such as accuracy, making it difficult for the algorithm to meet actual needs, resulting in poor discovery results. Summary of the invention

[0004] The present invention provides a method and system for automatically discovering the topology of the entire network, the main purpose of which is to improve the effect of automatically discovering the topology of the entire network.

[0005] To achieve the above object, the present invention provides a method for automatically discovering the topology of the entire network, comprising:

[0006] Acquire a resource object of a network, analyze the resource function and resource attributes of the resource object, wherein the resource attributes include: static attributes and dynamic attributes, construct a description language of the resource object based on the resource function and the resource attributes, and determine a description method of the resource object according to the description language;

[0007] According to the resource function and the resource attribute, determine the resource object type of the resource object, construct the inheritance relationship of the resource object type, and analyze the association relationship of the resource object type; according to the inheritance relationship and the association relationship, construct the model architecture of the resource object; analyze the business logic of the resource object; according to the business logic, use a preset model-driven development tool to construct a code generation module of the model architecture; based on the description method, the model architecture, the business logic and the code generation module, construct an initial model of the resource object; test the initial model to obtain a model test result; according to the test result, analyze the model accuracy and model stability of the initial model; when the model accuracy and the model stability meet the preset accuracy threshold and stability threshold at the same time, use the initial model as the resource object model;

[0008] Constructing an automatic discovery algorithm for the network, identifying devices and device information in the network based on the automatic discovery algorithm, constructing a network topology map of the network based on the devices and the device information, analyzing device connection relationships in the network topology map, and constructing a network topology model of the network based on the network topology map and the device connection relationships;

[0009] Identify the full topology structure of the network topology model, analyze the full topology structure using a preset graph database technology to obtain a topology structure analysis result, adjust the network configuration of the network topology model based on the topology structure analysis result, and construct an autonomous mechanism for the network topology model, map the network configuration and the autonomous mechanism to the network topology model, and obtain an optimized network topology model;

[0010] The optimized network topology model and the resource object model are integrated into a resource object management model, and based on the resource object management model, the full life cycle management of the resource object is achieved.

[0011] Optionally, constructing the description language of the resource object based on the resource function and the resource attribute includes:

[0012] Analyzing management requirements of the resource objects;

[0013] Determine the standardized attribute naming and data type of the resource object according to the resource function, the resource attribute and the management requirement;

[0014] According to the attribute naming and the data type, construct a description language mechanism of the resource object, wherein the description language mechanism includes: grammar rules, data structure and attribute definition;

[0015] Testing the description language mechanism to obtain a mechanism test result, and constructing an update mechanism for the description language mechanism according to the mechanism test result;

[0016] Based on the description language mechanism and the update mechanism, a description language of the resource object is constructed.

[0017] Optionally, constructing the inheritance relationship of the resource object type includes:

[0018] Identifying type commonalities and type characteristics between the resource object types;

[0019] Constructing a type base class of the resource object type according to the type commonality;

[0020] According to the type characteristics, construct a type subclass of the resource object type;

[0021] Determine inheritance functions of the type subclass and the type base class;

[0022] Analyzing the number of subclass commonalities and the number of subclass characteristics of the subclasses of the type;

[0023] determining the maximum number of characteristics of the subclass characteristics, and calculating the difference in the number of characteristics between subclasses of the type;

[0024] According to the number of commonalities of the subclasses, the maximum number of characteristics and the difference in the number of characteristics between the subclasses, the inter-subclass relationship coefficient of the type subclass is calculated using the following formula;

[0025]

[0026] in, represents the relationship coefficient between subclasses, Indicates the number of subclass commonalities, represents the maximum number of features, It indicates the difference in the number of features between subclasses;

[0027] According to the inter-subclass relationship coefficient, construct an inheritance hierarchy structure of the resource object type;

[0028] An inheritance relationship of the resource object type is constructed based on the type base class, the type subclass, the inheritance function and the inheritance hierarchy.

[0029] Optionally, the automatic discovery algorithm for building the network includes:

[0030] Analyze the network size, network complexity, and network management requirements of the network;

[0031] Identifying the community of the network using a preset community discovery algorithm according to the network size, the network complexity and the network management requirements;

[0032] Analyzing the network nodes of the network according to the community to determine the total number of nodes, the number of connected edges and the network adjacency matrix of the network nodes;

[0033] Based on the number of connection edges, determining a total number of connection edges of the network;

[0034] The modularity of the community is calculated using the following formula according to the total number of nodes, the total number of connected edges, the network nodes, the number of connected edges, and the network adjacency matrix:

[0035]

[0036] in, represents modularity, represents the total number of connected edges in the network, Indicates the total number of nodes, Representation Node and The network adjacency matrix between nodes, Representation Node The number of connected edges, Representation Node The number of connected edges, Representation Node community, Representation Node community, represents the indicator function, when 1 when it is, otherwise 0;

[0037] Determining a network protocol of the network according to the modularity;

[0038] Based on the network protocol, construct the algorithm logic of the network;

[0039] According to the network protocol and algorithm logic, the automatic discovery algorithm of the network is constructed using a preset multi-threaded programming technology.

[0040] Optionally, constructing a network topology diagram of the network based on the device and the device information includes:

[0041] Extracting a network planning document of the network;

[0042] Determining a topology of the network according to the device, the device information and the network planning document;

[0043] Determining a topology drawing tool for constructing the network topology map;

[0044] Analyze the placement, connection line direction and connection line style of the device;

[0045] Determine a topological layout of the device according to the placement position, the direction of the connection line, and the style of the connection line;

[0046] According to the topological structure and the topological map layout, the network topological map of the network is constructed using the topological map drawing tool.

[0047] Optionally, the using a preset graph database technology to analyze the full topology structure to obtain a topology structure analysis result includes:

[0048] Determine the node type and edge type of the full topology structure;

[0049] Analyzing node attributes of the node type and analyzing edge attributes of the edge type;

[0050] According to the node attributes and the edge attributes, the full topology structure is queried using the graph database technology to obtain a topology structure query result;

[0051] Analyze the network performance indicators and network health status of the full topology structure according to the topology structure query result;

[0052] Based on the network performance indicators and network health status, using the graph database technology to analyze future failure modes of the full topology structure;

[0053] Analyzing a network optimization report of the full topology structure according to the future failure mode;

[0054] The network performance indicator, the network health status, the future failure mode and the network optimization report are integrated into a topology structure analysis result of the full topology structure.

[0055] Optionally, the autonomous mechanism for constructing the network topology model includes:

[0056] identifying autonomy requirements and autonomy goals of the network topology model;

[0057] According to the autonomy requirements and autonomy goals, construct an autonomy algorithm for the network topology model, wherein the autonomy algorithm includes: automatic discovery, performance monitoring, fault prediction and repair;

[0058] an autonomous technique for determining said network topology model;

[0059] Constructing an initial autonomous mechanism of the network topology model according to the autonomous technology and autonomous algorithm;

[0060] Testing the initial autonomous mechanism to obtain an autonomous test result, and analyzing the autonomous performance of the initial autonomous mechanism according to the autonomous test result;

[0061] According to the autonomous performance, the initial autonomous mechanism is optimized to obtain an autonomous mechanism.

[0062] Optionally, implementing the full life cycle management of the resource object based on the resource object management model includes:

[0063] Identify resource object information of the resource object using an automatic discovery algorithm corresponding to the resource object management model;

[0064] Analyzing the current performance and current health status of the resource object according to the resource object information;

[0065] Based on the current performance and the current health status, calculating the life cycle of the resource object;

[0066] According to the life cycle, construct a life cycle management solution for the resource object;

[0067] Based on the lifecycle management solution, the full lifecycle management of the resource object is achieved.

[0068] In order to solve the above problems, the present invention also provides a system for automatically discovering the topology of the entire network, the system comprising:

[0069] A description method determination module, used to obtain a resource object of a network, analyze the resource function and resource attributes of the resource object, wherein the resource attributes include: static attributes and dynamic attributes, construct a description language of the resource object based on the resource function and the resource attributes, and determine the description method of the resource object according to the description language;

[0070] A resource object model construction module, used to determine the resource object type of the resource object according to the resource function and the resource attribute, construct the inheritance relationship of the resource object type, and analyze the association relationship of the resource object type, construct the model architecture of the resource object according to the inheritance relationship and the association relationship, analyze the business logic of the resource object, and construct the code generation module of the model architecture using a preset model-driven development tool according to the business logic, construct an initial model of the resource object based on the description method, the model architecture, the business logic and the code generation module, test the initial model to obtain a model test result, analyze the model accuracy and model stability of the initial model according to the test result, and when the model accuracy and the model stability meet the preset accuracy threshold and stability threshold at the same time, use the initial model as the resource object model;

[0071] An automatic discovery algorithm module, used to construct an automatic discovery algorithm for the network, identify devices and device information in the network based on the automatic discovery algorithm, construct a network topology map of the network based on the devices and the device information, analyze device connection relationships in the network topology map, and construct a network topology model of the network based on the network topology map and the device connection relationships;

[0072] A network topology model optimization module, used to identify the full topology structure of the network topology model, analyze the full topology structure using a preset graph database technology to obtain a topology structure analysis result, adjust the network configuration of the network topology model based on the topology structure analysis result, and construct an autonomous mechanism for the network topology model, map the network configuration and the autonomous mechanism to the network topology model, and obtain an optimized network topology model;

[0073] The full life cycle management module is used to integrate the optimized network topology model and the resource object model into a resource object management model, and based on the resource object management model, implement the full life cycle management of the resource object.

[0074] The embodiment of the present invention can ensure the uniformity and consistency of the description language of the resource object by constructing the description language of the resource object based on the resource function and the resource attribute; optionally, the embodiment of the present invention can abstract the common attributes and methods into the parent class by constructing the inheritance relationship of the resource object type, so that the management of the resource object is more modular and standardized, and is easy to maintain and expand; the embodiment of the present invention can make each resource object type and the relationship between them independently managed and maintained by constructing the resource object model based on the inheritance relationship, the association relationship and the description method, thereby improving the reusability and maintainability of the code; the embodiment of the present invention can automatically identify the devices and services in the network by constructing the automatic discovery algorithm of the network, thereby reducing the workload of manual configuration and improving the effect of network configuration; the embodiment of the present invention can realize the automation and intelligence of network management by constructing the autonomous mechanism of the network topology model, and improve the performance and security of the network. Finally, the embodiment of the present invention can continuously optimize the performance of the resource object by realizing the full life cycle management of the resource object based on the resource object management model. Therefore, the present invention can improve the effect of automatic discovery of the whole network topology. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 A schematic diagram of a process flow of a method for automatically discovering the entire network topology provided by an embodiment of the present invention;

[0076] Figure 2 A functional module diagram of a system for automatically discovering the entire network topology provided by an embodiment of the present invention;

[0077] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0078] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0079] The embodiment of the present application provides a method for automatic discovery of the topology of the entire network. The execution subject of the method for automatic discovery of the topology of the entire network includes but is not limited to at least one of the electronic devices such as the server, the terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for automatic discovery of the topology of the entire network can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0080] Reference Figure 1 FIG. 1 is a flow chart of a method for automatically discovering the topology of a whole network provided by an embodiment of the present invention. In this embodiment, the method for automatically discovering the topology of a whole network includes:

[0081] S1. Acquire a resource object of a network, analyze the resource function and resource attributes of the resource object, wherein the resource attributes include: static attributes and dynamic attributes, construct a description language of the resource object based on the resource function and the resource attributes, and determine a description method of the resource object according to the description language.

[0082] The embodiment of the present invention can monitor all resource objects in the network in real time by acquiring the resource objects of the network to ensure the normal operation of the network. The resource objects refer to various entities that can be identified, monitored, managed and operated in a network or data center environment, and the resource objects can be hardware, software, services or any other components that play a role in the network.

[0083] The embodiment of the present invention analyzes the resource functions and resource attributes of the resource object, wherein the resource attributes include static attributes and dynamic attributes that can provide data support for subsequent analysis. The resource function refers to the operation that the resource object can perform or the service provided. The resource attribute refers to the parameter or variable that describes the characteristics of the resource object, and defines the state, configuration, performance and function of the resource object. The static attribute refers to the attribute determined when the resource object is created or configured. These attributes usually remain unchanged during the life cycle of the resource object unless explicit management changes are made, such as ID, name, version, etc. The dynamic attribute refers to the attribute that changes over time or is dynamically updated during the life cycle of the resource object. These attributes reflect the state, performance and environmental conditions of the resource, such as performance indicators, connectivity, event logs, etc.

[0084] Optionally, as an embodiment of the present invention, the analysis of the resource type and resource attributes of the resource object can be performed through network scanning technology, which refers to a series of technologies used to discover and enumerate devices and services in the network, such as: Nmap, Zenmap, SNMP Scanner, etc.

[0085] Furthermore, the embodiment of the present invention can ensure the uniformity and consistency of the description language of the resource object by constructing the description language of the resource object based on the resource function and the resource attribute. The description language refers to a language or format used to define and describe the resource object.

[0086] As an embodiment of the present invention, the step of constructing the description language of the resource object based on the resource function and the resource attribute includes:

[0087] Analyzing management requirements of the resource objects;

[0088] Determine the standardized attribute naming and data type of the resource object according to the resource function, the resource attribute and the management requirement;

[0089] According to the attribute naming and the data type, construct a description language mechanism of the resource object, wherein the description language mechanism includes: grammar rules, data structure and attribute definition;

[0090] Testing the description language mechanism to obtain a mechanism test result, and constructing an update mechanism for the description language mechanism according to the mechanism test result;

[0091] Based on the description language mechanism and the update mechanism, a description language of the resource object is constructed.

[0092] The management requirements refer to the requirements for describing and managing resource objects according to the specific goals and tasks of network management, such as resource monitoring, configuration management, fault management, performance management, etc. The attribute naming refers to the standardized names defined for the resource object attributes, and the data types refer to the standardized types of attribute values, such as integers, floating point numbers, strings, Boolean values, etc. The description language mechanism refers to the language specification used to describe resource objects. The grammar rules refer to the organization of elements and structures in the description language, including the relationship and order between elements. The data structure refers to the layout and organization of data elements in the description language, such as lists, dictionaries, objects, etc. The attribute definition refers to the specific description of the resource object attributes, including the attribute name, data type, value range, etc. The mechanism test results refer to the results obtained after testing the description language mechanism, including test success and failure. The update mechanism refers to the process of modifying and updating the description language mechanism according to the mechanism test results.

[0093] Optionally, the description language mechanism for constructing the resource object according to the attribute naming and data type can be constructed by constructing a description language parser to parse the description language template, thereby constructing the description language mechanism. The description language parser refers to a software component or tool for reading and parsing texts or files written in a specific description language and converting them into a data structure that can be understood and operated by a computer.

[0094] Optionally, the update mechanism for constructing the description language mechanism according to the mechanism test result may be constructed by a continuous integration and continuous deployment method.

[0095] The embodiment of the present invention can achieve consistency management of resource objects by determining the description method of the resource object according to the description language, ensuring that the configuration and state of the resource object meet expectations. The description method refers to using a specific description language or format to define the attributes of the resource object, which allows the information of the resource object to be parsed and processed by automated tools and systems.

[0096] S2. Determine the resource object type of the resource object according to the resource function and the resource attribute, construct the inheritance relationship of the resource object type, and analyze the association relationship of the resource object type, and construct the resource object model of the resource object based on the inheritance relationship, the association relationship and the description method.

[0097] The embodiment of the present invention can help achieve interoperability and compatibility of resources between different systems by determining the resource object type according to the resource function and the resource attribute. The resource object type refers to the classification or type of resource objects in an information system, database or software application.

[0098] Optionally, as an embodiment of the present invention, the resource object type of the resource object determined according to the resource function and the resource attribute can be determined by business process analysis, wherein the business process analysis refers to an analysis method for determining the resource object type according to rules and logic in a business process.

[0099] The embodiment of the present invention can abstract the common properties and methods into the parent class by constructing the inheritance relationship of the resource object type, so that the management of resource objects is more modular and standardized, and is easy to maintain and expand. Among them, the inheritance relationship refers to a core concept in object-oriented programming (OOP), which describes that one type (usually called a subclass or derived class) can inherit the properties (variables) and methods (functions) of another type (usually called a parent class or base class).

[0100] As an embodiment of the present invention, the step of constructing the inheritance relationship of the resource object type includes:

[0101] Identifying type commonalities and type characteristics between the resource object types;

[0102] Constructing a type base class of the resource object type according to the type commonality;

[0103] According to the type characteristics, construct a type subclass of the resource object type;

[0104] Determine inheritance functions of the type subclass and the type base class;

[0105] Analyzing the number of subclass commonalities and the number of subclass characteristics of the subclasses of the type;

[0106] determining the maximum number of characteristics of the subclass characteristics, and calculating the difference in the number of characteristics between subclasses of the type;

[0107] According to the number of commonalities of the subclasses, the maximum number of characteristics and the difference in the number of characteristics between the subclasses, the inter-subclass relationship coefficient of the type subclass is calculated using the following formula;

[0108]

[0109] in, represents the relationship coefficient between subclasses, Indicates the number of subclass commonalities, represents the maximum number of features, It indicates the difference in the number of features between subclasses;

[0110] According to the inter-subclass relationship coefficient, construct an inheritance hierarchy structure of the resource object type;

[0111] An inheritance relationship of the resource object type is constructed based on the type base class, the type subclass, the inheritance function and the inheritance hierarchy.

[0112] The type commonality refers to the properties and methods shared between different resource object types. The type characteristics refer to the properties and methods unique to each resource object type. The type base class refers to an abstract class that contains the properties and methods common to all type subclasses. It is the root of the inheritance hierarchy and provides a basis for type subclasses to inherit and extend. The type subclass refers to a class derived from the base class, which inherits the properties and methods of the type base class and adds new type characteristics. The inheritance function refers to the mechanism by which the type subclass inherits properties and methods from the base class. The inheritance hierarchy refers to a tree structure formed from the type base class to the type subclass and then to a more specific type subclass. The number of subclass commonalities refers to the number of properties (including properties and methods) shared by two subclasses. The number of subclass characteristics refers to the number of properties unique to a single subclass. The maximum number of properties refers to the total number of properties of the subclass with more properties among the two subclasses. The difference in the number of properties between subclasses refers to the difference in the number of properties of the two subclasses.

[0113] Optionally, the identification of type commonalities and type characteristics between the resource object types may be obtained by a method of identifying repeated code and logic.

[0114] Optionally, the determination of the inherited functions of the type subclass and the type base class can be determined by abstraction and encapsulation, wherein the abstraction refers to decomposing complex things into simpler and easier to understand parts. In programming, abstraction involves hiding internal implementation details and only providing external interfaces. Encapsulation refers to encapsulating data and methods for operating data (i.e., behaviors) in a class.

[0115] The embodiment of the present invention can help clarify the interaction mode between resource objects by analyzing the association relationship of the resource object type, so as to more clearly understand the overall architecture of the system. The association relationship refers to a connection between different classes in object-oriented programming (OOP), such as dependency, aggregation, and combination.

[0116] Optionally, as an embodiment of the present invention, the analysis of the association relationship of the resource object type may be analyzed by a domain driven design method, wherein the domain driven design refers to a method of identifying the association relationship of resource object types through aggregate roots and boundaries.

[0117] The embodiment of the present invention constructs the resource object model of the resource object based on the inheritance relationship, the association relationship and the description method, so that each resource object type and the relationship between them can be managed and maintained independently, thereby improving the reusability and maintainability of the code. Wherein, the resource object model refers to a model constructed for describing and managing resource objects.

[0118] As an embodiment of the present invention, the resource object model of the resource object is constructed based on the inheritance relationship, the association relationship and the description method, including:

[0119] Constructing a model architecture of the resource object according to the inheritance relationship and the association relationship;

[0120] Analyze the business logic of the resource object; and construct a code generation module of the model architecture using a preset model-driven development tool according to the business logic;

[0121] Based on the description method, the model architecture, the business logic and the code generation module, construct an initial model of the resource object;

[0122] Testing the initial model to obtain a model test result, and analyzing the model accuracy and model stability of the initial model according to the test result;

[0123] When the model accuracy and the model stability meet the preset accuracy threshold and stability threshold at the same time, the initial model is used as the resource object model.

[0124] Among them, the model architecture refers to the organizational structure of the resource object model, including: hierarchy, association relationship and inheritance relationship. The business logic refers to the code that processes business rules and operations in the resource object model. The model-driven development tool refers to a software tool for creating, managing and generating code. The code generation module refers to a module for generating a specific code structure according to business logic. The initial model refers to the first resource object model version built based on the model architecture and business logic. The model test results refer to the results of the test activities conducted on the initial model, including the execution of test cases, test coverage, defect reports, etc. The model accuracy refers to the consistency between the model test results and the expected results, which reflects the correctness of the model when processing business logic and data. The model stability refers to the ability of the model to maintain its functions and performance under different operating environments and conditions, which reflects the reliability and stability of the model in long-term use. The preset accuracy threshold refers to the minimum requirement for the prediction accuracy of the model on the test data. The stability threshold refers to the minimum requirement for the model performance to remain consistent over a period of time.

[0125] Optionally, the analyzing the business logic of the resource object may be performed by a business process analysis method.

[0126] S3. Construct an automatic discovery algorithm for the network, identify devices and device information in the network based on the automatic discovery algorithm, construct a network topology map of the network based on the devices and the device information, analyze the device connection relationships in the network topology map, and construct a network topology model of the network based on the network topology map and the device connection relationships.

[0127] The embodiment of the present invention can automatically identify devices and services in the network by constructing the automatic discovery algorithm of the network, thereby reducing the workload of manual configuration and improving the effect of network configuration. The automatic discovery algorithm refers to an algorithm or mechanism for automatically identifying and discovering network devices and services in the network.

[0128] As an embodiment of the present invention, the automatic discovery algorithm for constructing the network includes:

[0129] Analyze the network size, network complexity, and network management requirements of the network;

[0130] Identifying the community of the network using a preset community discovery algorithm according to the network size, the network complexity and the network management requirements;

[0131] Analyzing the network nodes of the network according to the community to determine the total number of nodes, the number of connected edges and the network adjacency matrix of the network nodes;

[0132] Based on the number of connection edges, determining a total number of connection edges of the network;

[0133] The modularity of the community is calculated using the following formula according to the total number of nodes, the total number of connected edges, the network nodes, the number of connected edges, and the network adjacency matrix:

[0134]

[0135] in, represents modularity, represents the total number of connected edges in the network, Indicates the total number of nodes, Representation Node and The network adjacency matrix between nodes, Representation Node The number of connected edges, Representation Node The number of connected edges, Representation Node community, Representation Node community, represents the indicator function, when 1 when it is, otherwise 0;

[0136] Determining a network protocol of the network according to the modularity;

[0137] Based on the network protocol, construct the algorithm logic of the network;

[0138] According to the network protocol and algorithm logic, the automatic discovery algorithm of the network is constructed using a preset multi-threaded programming technology.

[0139] Among them, the network scale refers to the number of devices, nodes and connections in the network. The network complexity refers to the complexity of the network topology, device types and network services. The network management requirements refer to the goals of network management, including monitoring, troubleshooting, security and scalability. The preset community discovery algorithm refers to an algorithm for identifying closely connected sub-communities (communities) existing in the network. The community refers to a sub-community composed of closely connected nodes. The network node refers to the basic unit in the network, which can be a device, individual, organization or other entity in the actual network. The total number of nodes refers to the number of all nodes in the network. The number of connection edges refers to the number of connection edges of nodes in the network. The network adjacency matrix is ​​a two-dimensional array used to represent the connection relationship between each node in the network. The modularity refers to a standard for measuring the quality of community division in the network structure.

[0140] The network protocol refers to the rules and standards used for communication between devices in the network. The algorithm logic refers to the steps and processes of algorithm execution, including device scanning, service identification and topology construction. The multi-threaded programming technology refers to the programming technology that uses the multi-threaded capabilities provided by the operating system to perform multiple tasks simultaneously. The initial automatic discovery algorithm refers to the first automatic discovery algorithm version built based on the network protocol and algorithm logic. The running test results refer to the results obtained after running the initial automatic discovery algorithm, including the number of discovered devices, time consumption, etc. The algorithm logic refers to the time and resources required for the algorithm to complete the network scan. The algorithm accuracy refers to the degree of match between the devices and services discovered by the algorithm and the actual network.

[0141] Optionally, the algorithm logic for constructing the network based on the network protocol can be constructed by a protocol analysis method.

[0142] The embodiment of the present invention can understand the performance and health status of network devices by identifying the devices and device information in the network based on the automatic discovery algorithm, thereby performing more effective resource allocation and performance optimization. The devices refer to various hardware and software entities in the network. The device information refers to various data and parameters related to the devices in the network, which are used to describe and identify the characteristics, status and configuration of the devices.

[0143] The embodiment of the present invention can more quickly identify key components and paths in the network by constructing a network topology map of the network based on the device and the device information, thereby more effectively managing and maintaining the network. The network topology map refers to a diagram that graphically represents the connection relationship between devices in the network.

[0144] As an embodiment of the present invention, constructing a network topology diagram of the network based on the device and the device information includes:

[0145] Extracting a network planning document of the network;

[0146] Determining a topology of the network according to the device, the device information and the network planning document;

[0147] Determining a topology drawing tool for constructing the network topology map;

[0148] Analyze the placement, connection line direction and connection line style of the device;

[0149] Determine a topological layout of the device according to the placement position, the direction of the connection line, and the style of the connection line;

[0150] According to the topological structure and the topological map layout, the network topological map of the network is constructed using the topological map drawing tool.

[0151] Among them, the network planning document is a document that records in detail the network's physical layout, logical structure, equipment list, IP address allocation, network configuration parameters and other information. The topology structure refers to the physical and logical relationship between elements such as devices, connections, subnets, etc. in the network. The topology drawing tool is a software tool used to draw network topology diagrams, such as Microsoft Visio, Lucidchart, etc. The placement position refers to the position and direction of the device node in the topology diagram. The connection line direction refers to the direction and direction of the connection line in the topology diagram. The connection line style refers to the visual elements such as the shape, color, thickness, etc. of the connection line. The topology layout refers to the overall layout and arrangement of all elements (devices, connections, network components, etc.) in the topology diagram.

[0152] Optionally, the determining of the topology of the network based on the device, the device information and the network planning document can be determined by simulating the network using a network simulation and emulation tool, such as GNS3, Boson NetSim, etc.

[0153] By analyzing the device connection relationship of the network topology diagram, the embodiment of the present invention can visually see all the devices in the network and the connection mode between them, so as to better understand the structure and layout of the network. The device connection relationship refers to the mode and state of interconnection between different devices in the network through network media (such as cables, optical fibers, wireless signals, etc.). The device connection relationship includes: physical connection relationship and logical connection relationship.

[0154] Optionally, as an embodiment of the present invention, the analyzing of the device connection relationship of the network topology diagram may be performed through a mathematical model.

[0155] The embodiment of the present invention can improve the visualization of the network, simplify the network management process, enhance the scalability and security of the network, and support automated management and network planning by constructing the network topology model of the network based on the network topology diagram and the device connection relationship. The network topology model refers to a model that graphically represents the connection relationship between devices in the network.

[0156] S4. Identify the full topology structure of the network topology model, analyze the full topology structure using a preset graph database technology to obtain a topology structure analysis result, adjust the network configuration of the network topology model based on the topology structure analysis result, and construct an autonomous mechanism for the network topology model, map the network configuration and the autonomous mechanism to the network topology model, and obtain an optimized network topology model.

[0157] The embodiment of the present invention can obtain a complete view of all devices in the network and the connections between them by identifying the full topology structure of the network topology model, wherein the full topology structure refers to a complete description of all devices in the network and the connection relationship between them.

[0158] Optionally, as an embodiment of the present invention, the full topology structure of the network topology model can be identified through blockchain technology, wherein the blockchain technology refers to a distributed ledger technology that jointly maintains an unalterable ledger through multiple nodes in the network, recording all transactions and status changes.

[0159] The embodiment of the present invention analyzes the full topology structure by using a preset graph database technology to obtain a topology structure analysis result, which can improve the effect and accuracy of network management. The graph database technology refers to a database management system specifically used to store, query and analyze graph data. The topology structure analysis result refers to a series of data obtained after an in-depth analysis of the network topology model, such as network performance indicators, network health status, etc.

[0160] As an embodiment of the present invention, the full topology structure is analyzed by using a preset graph database technology to obtain a topology structure analysis result, including:

[0161] Determine the node type and edge type of the full topology structure;

[0162] Analyzing node attributes of the node type and analyzing edge attributes of the edge type;

[0163] According to the node attributes and the edge attributes, the full topology structure is queried using the graph database technology to obtain a topology structure query result;

[0164] Analyze the network performance indicators and network health status of the full topology structure according to the topology structure query result;

[0165] Based on the network performance indicators and network health status, using the graph database technology to analyze future failure modes of the full topology structure;

[0166] Analyzing a network optimization report of the full topology structure according to the future failure mode;

[0167] The network performance indicator, the network health status, the future failure mode and the network optimization report are integrated into a topology structure analysis result of the full topology structure.

[0168] Among them, the node type refers to different entities in the network, such as devices, users, services, etc. The edge type refers to the relationship between nodes, such as the connection between devices, the association between services and devices, etc. The node attribute is additional information attached to the node, such as device model, IP address, MAC address, etc. The edge attribute is additional information attached to the edge, such as link bandwidth, connection status, etc. The topology query result refers to the topology information obtained by querying the graph database, including detailed data of nodes and edges. The network performance index refers to the key parameters for measuring network performance, such as latency, bandwidth, packet loss rate, etc. The network health status refers to the current status of network equipment, including equipment performance, link status, etc. The future failure mode refers to the predicted potential failure mode. The network optimization report refers to the network optimization suggestions and strategies proposed based on the future failure mode.

[0169] Optionally, the querying of the entire topology structure using the graph database technology according to the node attributes and the edge attributes may be performed by using a query language in the graph database technology, such as Cypher or Gremlin.

[0170] The embodiment of the present invention can reduce network bottlenecks, increase data transmission speed, and thus improve overall network performance by adjusting the network configuration of the network topology model based on the topology structure analysis result. The network configuration refers to a series of parameter settings for network devices (such as switches, routers, firewalls, etc.) in the network in order to achieve specific functions and performance requirements.

[0171] Optionally, the network configuration of the network topology model is adjusted based on the topology structure analysis result by using automation scripts and configuration management tools, such as Ansible, Puppet, Chef, etc., to automate the change of network configuration.

[0172] The embodiment of the present invention can realize automation and intelligence of network management by constructing the autonomous mechanism of the network topology model, and improve the performance and security of the network. Among them, the self-management and self-optimization capabilities of network equipment and management systems are realized through automation and intelligence.

[0173] As an embodiment of the present invention, the autonomous mechanism for constructing the network topology model includes:

[0174] identifying autonomy requirements and autonomy goals of the network topology model;

[0175] According to the autonomy requirements and autonomy goals, construct an autonomy algorithm for the network topology model, wherein the autonomy algorithm includes: automatic discovery, performance monitoring, fault prediction and repair;

[0176] an autonomous technique for determining said network topology model;

[0177] Constructing an initial autonomous mechanism of the network topology model according to the autonomous technology and autonomous algorithm;

[0178] Testing the initial autonomous mechanism to obtain an autonomous test result, and analyzing the autonomous performance of the initial autonomous mechanism according to the autonomous test result;

[0179] According to the autonomous performance, the initial autonomous mechanism is optimized to obtain an autonomous mechanism.

[0180] Among them, the autonomous requirements refer to the functional and performance requirements that the network topology model must meet when achieving autonomy. The autonomous goals refer to the specific goals achieved through the autonomous mechanism, such as automated management, real-time response, prediction and prevention of faults, etc. The autonomous algorithm refers to the core logic and process used to implement the autonomous mechanism. The automatic discovery means that the network topology model can automatically identify and track changes in devices and connections in the network. The performance monitoring means that the network topology model can monitor the performance indicators of network devices, such as latency, bandwidth, packet loss rate, etc. The fault prediction means that the network topology model can predict possible faults of network devices or links. The repair means that the network topology model can automatically or semi-automatically repair faults, such as restoring links or reconfiguring devices. The autonomous technology refers to the tools and platforms used to implement the autonomous mechanism, such as automated scripts, machine learning, artificial intelligence, etc. The initial autonomous mechanism refers to the first version of the autonomous mechanism built based on the autonomous algorithm and autonomous technology.

[0181] Optionally, the autonomous algorithm for constructing the network topology model according to the autonomous requirements and autonomous goals can be constructed through microservice architecture and containerization, wherein the microservice architecture refers to a software architecture style that decomposes an application into a set of small, loosely coupled services. Each service runs in its own process and is coordinated and integrated through a lightweight communication mechanism (usually HTTP RESTful API or message queue). The containerization refers to a technology for quickly deploying and adjusting autonomous algorithms to adapt to changing needs, such as Docker.

[0182] The embodiment of the present invention maps the network configuration and the autonomous mechanism to the network topology model to obtain an optimized network topology model, which can ensure that the network can meet current and future business needs and improve the overall performance and security of the network. The optimized network topology model refers to a model that significantly improves network performance, security and reliability by adjusting the network configuration, introducing an autonomous mechanism or improving the network management strategy on the basis of the existing network topology model.

[0183] S5. Integrate the optimized network topology model and the resource object model into a resource object management model, and implement full life cycle management of the resource object based on the resource object management model.

[0184] The embodiment of the present invention can automatically discover network changes, automatically adjust network configuration, and realize automatic and intelligent management of the network by integrating the optimized network topology model and the resource object model into a resource object management model. The resource object management model refers to a model for managing and monitoring various resource objects in a computer network.

[0185] As an embodiment of the present invention, the step of integrating the optimized network topology model and the resource object model into a resource object management model includes:

[0186] Identifying basic nodes and links of the network topology model;

[0187] Mapping the basic node and the link to the resource object corresponding to the resource object model to obtain a model mapping result;

[0188] According to the model mapping result, the optimized network topology model and the resource object model are optimized to obtain optimization parameters;

[0189] According to the optimization parameters, the optimized network topology model and the resource object model are integrated into a resource object management model.

[0190] The basic node refers to the basic unit in the network. The link refers to the connection between the basic nodes. The optimization parameter refers to the parameter used to adjust the model performance during the optimization process of the network topology and resource object model.

[0191] The embodiment of the present invention can continuously optimize the performance of resource objects by implementing the full life cycle management of the resource objects based on the resource object management model, including configuration optimization, performance monitoring and fault prevention. The full life cycle management refers to the management and monitoring of the entire process of resource objects from creation to retirement.

[0192] As an embodiment of the present invention, the full life cycle management of the resource object is implemented based on the resource object management model, including:

[0193] Identify resource object information of the resource object using an automatic discovery algorithm corresponding to the resource object management model;

[0194] Analyzing the current performance and current health status of the resource object according to the resource object information;

[0195] Based on the current performance and the current health status, calculating the life cycle of the resource object;

[0196] According to the life cycle, construct a life cycle management solution for the resource object;

[0197] Based on the lifecycle management solution, the full lifecycle management of the resource object is achieved.

[0198] Among them, the resource object information refers to detailed data about resource objects in the network. The current performance refers to the actual performance indicators of the resource object at a certain point in time, such as bandwidth utilization, latency, packet loss rate, CPU usage, etc. The current health status refers to the overall health status of the resource object at a certain point in time, including device performance, link status, device status, etc. The life cycle refers to the entire process from the creation to the retirement of the resource object, including planning, design, procurement, deployment, operation, maintenance, optimization, troubleshooting, retirement and other stages. The life cycle management plan refers to the management strategy for the life cycle of the resource object, including maintenance plans, update strategies, retirement plans, etc.

[0199] The embodiment of the present invention can ensure the uniformity and consistency of the description language of the resource object by constructing the description language of the resource object based on the resource function and the resource attribute; optionally, the embodiment of the present invention can abstract the common attributes and methods into the parent class by constructing the inheritance relationship of the resource object type, so that the management of the resource object is more modular and standardized, and is easy to maintain and expand; the embodiment of the present invention can make each resource object type and the relationship between them independently managed and maintained by constructing the resource object model based on the inheritance relationship, the association relationship and the description method, thereby improving the reusability and maintainability of the code; the embodiment of the present invention can automatically identify the devices and services in the network by constructing the automatic discovery algorithm of the network, thereby reducing the workload of manual configuration and improving the effect of network configuration; the embodiment of the present invention can realize the automation and intelligence of network management by constructing the autonomous mechanism of the network topology model, and improve the performance and security of the network. Finally, the embodiment of the present invention can continuously optimize the performance of the resource object by realizing the full life cycle management of the resource object based on the resource object management model. Therefore, the present invention can improve the effect of automatic discovery of the whole network topology.

[0200] like Figure 2 , which is a functional module diagram of a system for automatic discovery of the entire network topology provided by an embodiment of the present invention.

[0201] The full network topology automatic discovery system 200 of the present invention can be installed in an electronic device. According to the functions to be implemented, the full network topology automatic discovery system 200 can include a description method determination module 201, a resource object model construction module 202, an automatic discovery algorithm module 203, a network topology model optimization module 204 and a full life cycle management module 205. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0202] In this embodiment, the functions of each module / unit are as follows:

[0203] The description method determination module 201 is used to obtain a resource object of a network, analyze the resource function and resource attributes of the resource object, wherein the resource attributes include: static attributes and dynamic attributes, construct a description language of the resource object based on the resource function and the resource attributes, and determine the description method of the resource object according to the description language;

[0204] The resource object model construction module 202 is used to determine the resource object type of the resource object according to the resource function and the resource attribute, construct the inheritance relationship of the resource object type, and analyze the association relationship of the resource object type, construct the model architecture of the resource object according to the inheritance relationship and the association relationship, analyze the business logic of the resource object, and construct the code generation module of the model architecture using a preset model-driven development tool according to the business logic, construct the initial model of the resource object based on the description method, the model architecture, the business logic and the code generation module, test the initial model to obtain the model test result, analyze the model accuracy and model stability of the initial model according to the test result, and when the model accuracy and the model stability meet the preset accuracy threshold and stability threshold at the same time, use the initial model as the resource object model;

[0205] The automatic discovery algorithm module 203 is used to construct an automatic discovery algorithm for the network, identify devices and device information in the network based on the automatic discovery algorithm, construct a network topology map of the network based on the devices and the device information, analyze device connection relationships in the network topology map, and construct a network topology model of the network based on the network topology map and the device connection relationships;

[0206] The network topology model optimization module 204 is used to identify the full topology structure of the network topology model, analyze the full topology structure using a preset graph database technology to obtain a topology structure analysis result, adjust the network configuration of the network topology model based on the topology structure analysis result, and construct an autonomous mechanism of the network topology model, map the network configuration and the autonomous mechanism to the network topology model, and obtain an optimized network topology model;

[0207] The full life cycle management module 205 is used to integrate the optimized network topology model and the resource object model into a resource object management model, and implement the full life cycle management of the resource object based on the resource object management model.

[0208] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for automatically discovering the topology of the entire network, characterized in that: The method comprises: Acquire a resource object of a network, analyze the resource function and resource attributes of the resource object, wherein the resource attributes include: static attributes and dynamic attributes, construct a description language of the resource object based on the resource function and the resource attributes, and determine a description method of the resource object according to the description language; According to the resource function and the resource attribute, determine the resource object type of the resource object, construct the inheritance relationship of the resource object type, and analyze the association relationship of the resource object type; according to the inheritance relationship and the association relationship, construct the model architecture of the resource object; analyze the business logic of the resource object; according to the business logic, use a preset model-driven development tool to construct a code generation module of the model architecture; based on the description method, the model architecture, the business logic and the code generation module, construct an initial model of the resource object; test the initial model to obtain a model test result; according to the test result, analyze the model accuracy and model stability of the initial model; when the model accuracy and the model stability meet the preset accuracy threshold and stability threshold at the same time, use the initial model as the resource object model; Constructing an automatic discovery algorithm for the network, identifying devices and device information of resource objects corresponding to the network based on the automatic discovery algorithm, constructing a network topology map of the network based on the devices and the device information, analyzing device connection relationships of the network topology map, and constructing a network topology model of the network based on the network topology map and the device connection relationships; Identify the full topology structure of the network topology model, analyze the full topology structure using a preset graph database technology to obtain a topology structure analysis result, adjust the network configuration of the network topology model based on the topology structure analysis result, and construct an autonomous mechanism for the network topology model, map the network configuration and the autonomous mechanism to the network topology model, and obtain an optimized network topology model; The optimized network topology model and the resource object model are integrated into a resource object management model, and based on the resource object management model, the full life cycle management of the resource object is achieved.

2. The method for automatically discovering the entire network topology according to claim 1, characterized in that: The step of constructing the description language of the resource object based on the resource function and the resource attribute includes: Analyzing management requirements of the resource objects; Determine the standardized attribute naming and data type of the resource object according to the resource function, the resource attribute and the management requirement; According to the attribute naming and the data type, construct a description language mechanism of the resource object, wherein the description language mechanism includes: grammar rules, data structure and attribute definition; Testing the description language mechanism to obtain a mechanism test result, and constructing an update mechanism for the description language mechanism according to the mechanism test result; Based on the description language mechanism and the update mechanism, a description language of the resource object is constructed.

3. The method for automatically discovering the entire network topology according to claim 1, characterized in that: The step of constructing the inheritance relationship of the resource object type includes: Identifying type commonalities and type characteristics between the resource object types; According to the type commonality, construct a type base class of the resource object type; According to the type characteristics, construct a type subclass of the resource object type; Determine inheritance functions of the type subclass and the type base class; Analyzing the number of subclass commonalities and the number of subclass characteristics of the subclasses of the type; determining the maximum number of characteristics of the subclass characteristics, and calculating the difference in the number of characteristics between subclasses of the type; According to the number of commonalities of the subclasses, the maximum number of characteristics and the difference in the number of characteristics between the subclasses, the inter-subclass relationship coefficient of the type subclass is calculated using the following formula; Among them, μ represents the relationship coefficient between subclasses, G represents the number of commonalities among subclasses, and T max represents the maximum number of features, and ΔT represents the difference in the number of features between subclasses; According to the inter-subclass relationship coefficient, construct an inheritance hierarchy structure of the resource object type; Based on the type base class, the type subclass, the inheritance function and the inheritance hierarchy, an inheritance relationship of the resource object type is constructed.

4. The method for automatically discovering the entire network topology according to claim 1, characterized in that: The automatic discovery algorithm for constructing the network includes: Analyze the network size, network complexity, and network management requirements of the network; Identifying the community of the network using a preset community discovery algorithm according to the network size, the network complexity, and the network management requirements; Analyzing the network nodes of the network according to the community to determine the total number of nodes, the number of connected edges and the network adjacency matrix of the network nodes; Based on the number of connection edges, determining a total number of connection edges of the network; The modularity of the community is calculated using the following formula according to the total number of nodes, the total number of connected edges, the network nodes, the number of connected edges, and the network adjacency matrix: Among them, D represents modularity, N represents the total number of connected edges in the network, n represents the total number of nodes, and Z ij represents the network adjacency matrix between nodes i and j, B i represents the number of edges connecting node i, B j represents the number of edges connecting node j, S i represents the community of node i, S j represents the community of node j, f(S i , S j ) represents the indicator function, when S i =S j 1 when it is, otherwise 0; Determining a network protocol of the network according to the modularity; Based on the network protocol, construct the algorithm logic of the network, wherein the algorithm logic refers to the steps and processes of algorithm execution; According to the network protocol and algorithm logic, the automatic discovery algorithm of the network is constructed using a preset multi-threaded programming technology.

5. The method for automatically discovering the entire network topology according to claim 1, characterized in that: The constructing a network topology diagram of the network based on the device and the device information includes: Extracting a network planning document of the network; Determining a topology of the network according to the device, the device information and the network planning document; Determining a topology drawing tool for constructing the network topology map; Analyze the placement, connection line direction and connection line style of the device; Determining a topological layout of the device according to the placement position, the direction of the connection line, and the style of the connection line; According to the topological structure and the topological map layout, the network topological map of the network is constructed using the topological map drawing tool.

6. The method for automatically discovering the entire network topology according to claim 1, characterized in that: The method of analyzing the full topology structure by using a preset graph database technology to obtain a topology structure analysis result includes: Determine the node type and edge type of the full topology structure; Analyzing node attributes of the node type and analyzing edge attributes of the edge type; According to the node attributes and the edge attributes, the full topology structure is queried using the graph database technology to obtain a topology structure query result; Analyze the network performance indicators and network health status of the full topology structure according to the topology structure query result; Based on the network performance indicators and network health status, using the graph database technology to analyze future failure modes of the full topology structure; Analyzing a network optimization report of the full topology structure according to the future failure mode; The network performance indicator, the network health status, the future failure mode and the network optimization report are integrated into a topology structure analysis result of the full topology structure.

7. The method for automatically discovering the entire network topology according to claim 1, characterized in that: The autonomous mechanism for constructing the network topology model includes: identifying autonomy requirements and autonomy goals of the network topology model; According to the autonomy requirements and autonomy goals, construct an autonomy algorithm for the network topology model, wherein the autonomy algorithm includes: automatic discovery, performance monitoring, fault prediction and repair; an autonomous technique for determining said network topology model; Constructing an initial autonomous mechanism of the network topology model according to the autonomous technology and autonomous algorithm; Testing the initial autonomous mechanism to obtain an autonomous test result, and analyzing the autonomous performance of the initial autonomous mechanism according to the autonomous test result; According to the autonomous performance, the initial autonomous mechanism is optimized to obtain an autonomous mechanism.

8. The method for automatically discovering the entire network topology according to claim 1, characterized in that: The full life cycle management of the resource object is realized based on the resource object management model, including: Identify resource object information of the resource object using an automatic discovery algorithm corresponding to the resource object management model; Analyzing the current performance and current health status of the resource object according to the resource object information; Based on the current performance and the current health status, calculating the life cycle of the resource object; According to the life cycle, construct a life cycle management solution for the resource object; Based on the lifecycle management solution, the full lifecycle management of the resource object is achieved.

9. A system for automatically discovering the topology of the entire network, characterized in that: The system is used to execute the method for automatically discovering the entire network topology according to any one of claims 1 to 8, and comprises: A description method determination module, used to obtain a resource object of a network, analyze the resource function and resource attributes of the resource object, wherein the resource attributes include: static attributes and dynamic attributes, construct a description language of the resource object based on the resource function and the resource attributes, and determine the description method of the resource object according to the description language; A resource object model construction module, used to determine the resource object type of the resource object according to the resource function and the resource attribute, construct the inheritance relationship of the resource object type, and analyze the association relationship of the resource object type, construct the model architecture of the resource object according to the inheritance relationship and the association relationship, analyze the business logic of the resource object, and construct the code generation module of the model architecture using a preset model-driven development tool according to the business logic, construct an initial model of the resource object based on the description method, the model architecture, the business logic and the code generation module, test the initial model to obtain a model test result, analyze the model accuracy and model stability of the initial model according to the test result, and when the model accuracy and the model stability meet the preset accuracy threshold and stability threshold at the same time, use the initial model as the resource object model; An automatic discovery algorithm module, used to construct an automatic discovery algorithm for the network, identify devices and device information of resource objects corresponding to the network based on the automatic discovery algorithm, construct a network topology map of the network based on the devices and the device information, analyze device connection relationships of the network topology map, and construct a network topology model of the network based on the network topology map and the device connection relationships; A network topology model optimization module, used to identify the full topology structure of the network topology model, analyze the full topology structure using a preset graph database technology to obtain a topology structure analysis result, adjust the network configuration of the network topology model based on the topology structure analysis result, and construct an autonomous mechanism for the network topology model, map the network configuration and the autonomous mechanism to the network topology model, and obtain an optimized network topology model; The full life cycle management module is used to integrate the optimized network topology model and the resource object model into a resource object management model, and based on the resource object management model, implement the full life cycle management of the resource object.

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