Equipment asset management system and method based on graph model

Abstract

The invention provides an equipment asset management system and method based on a graph model, a data module is used for acquiring sample data, and the sample data comprises network equipment in a network service architecture and a dependency relationship among the network equipment; the graph model module is used for constructing a graph model according to the sample data, each network device in the network service architecture is a vertex of the graph model, and a dependency relationship among the network devices is an edge of the graph model; and the query module is used for receiving a query request of a user, performing query in the graph model by utilizing a graph query language based on the query request, and displaying a query result, and the query result displays the equipment dependence network with potential influence. By constructing the graph model, the dependency relationship between the devices can be effectively judged, and potential influence analysis is carried out, so that the device management efficiency is improved, and the device management effect is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise asset management, and in particular to an equipment asset management system and method based on a graph model. Background Art

[0002] In the daily operations of an enterprise, management systems or control systems are usually required, such as MES systems, APS systems, quality management systems, and equipment maintenance systems, in order to manage the enterprise's operations, equipment, materials and other static assets.

[0003] Due to the differences in production types and business contents of enterprises, the development of equipment asset management systems for different enterprises is mainly achieved by relevant developers writing codes according to enterprise needs. When new enterprise needs arise, the code needs to be rewritten, resulting in a long development cycle of the equipment asset management system and low development efficiency.

[0004] In addition, traditional equipment asset management systems rely on tables or tree structures and are unable to efficiently model and query complex many-to-many dependencies, resulting in inefficient troubleshooting. Summary of the Invention

[0005] The present invention provides an equipment asset management system and method based on a graph model, which is used to solve the defects of the prior art in which code is written for enterprise management systems, resulting in a long management system development cycle and low development efficiency, and realizes intelligent equipment management and improved efficiency.

[0006] The present invention provides an equipment asset management system based on a graph model, comprising: A data module is used to obtain sample data, wherein the sample data includes network devices in the network service architecture and dependencies between the network devices; A graph model module, configured to construct a graph model based on the sample data, wherein each network device in the network service architecture is a vertex of the graph model, and the dependency relationships between the network devices are edges of the graph model; The query module is used to receive a user's query request, perform a query in the graph model based on the query request using a graph query language, and display the query result, wherein the query result displays the device dependency network with potential impact.

[0007] According to the equipment asset management system based on the graph model provided by the present invention, the system further includes an analysis module for: Based on the device-dependent network, analyzing the network devices that the user depends on from top to bottom to obtain a first analysis result; Based on the device dependency network, bottom-up analysis is performed on the impact of the network device failure on the application, service, or user to obtain a second analysis result; Based on the first analysis result and the second analysis result, it is determined whether there is a redundant path in the device-dependent network.

[0008] According to the equipment asset management system based on the graph model provided by the present invention, the graph model module is further used for: According to the type of network device corresponding to each vertex in the graph model, the attribute of each vertex is defined.

[0009] According to the equipment asset management system based on the graph model provided by the present invention, the graph model module is specifically used for: When the type of the network device corresponding to the vertex is a server, the attribute of the vertex is defined as the server number; When the type of the network device corresponding to the vertex is a network server virtual machine, the attribute of the vertex is defined as the VM number; When the type of the network device corresponding to the vertex is a database virtual machine, the attribute of the vertex is defined as a DBVM label; When the type of the network device corresponding to the vertex is a website, the attribute of the vertex is defined as a URL; When the type of network device corresponding to the vertex is a customer relationship management system, the attribute of the vertex is defined as a management system number; When the type of the network device corresponding to the vertex is a storage area network, the attribute of the vertex is defined as a SAN number.

[0010] According to the equipment asset management system based on the graph model provided by the present invention, the query result adopts a tree layout structure.

[0011] According to the graph model-based equipment asset management system provided by the present invention, the query module adopts Cypher or Gremlin graph query language.

[0012] The present invention further provides a device asset management method based on a graph model, which is implemented by any of the above-described device asset management systems based on a graph model, and the method comprises: Receive user query requests; Based on the query request, querying in a pre-built graph model using a graph query language and displaying query results, wherein the query results display a potentially impactful device dependency network in the network service architecture; The graph model is constructed by taking each network device in the network service architecture as a vertex and the dependency relationships between the network devices as edges.

[0013] The device asset management method based on the graph model provided by the present invention further includes: Based on the device-dependent network, analyzing the network devices that the user depends on from top to bottom to obtain a first analysis result; Based on the device dependency network, bottom-up analysis is performed on the impact of the network device failure on the application, service, or user to obtain a second analysis result; Based on the first analysis result and the second analysis result, it is determined whether there is a redundant path in the device-dependent network.

[0014] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the device asset management method based on the graphical model as described above is implemented.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described equipment asset management methods based on a graphical model.

[0016] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements any of the above-mentioned device asset management methods based on the graphical model.

[0017] The present invention provides a graph-based equipment asset management system and method, wherein a data module is used to obtain sample data, wherein the sample data includes network devices in a network service architecture and the dependency relationships between the network devices; a graph model module is used to construct a graph model based on the sample data, wherein the network devices in the network service architecture are vertices of the graph model, and the dependency relationships between the network devices are edges of the graph model; and a query module is used to receive a user's query request, and based on the query request, perform a query in the graph model using a graph query language, and display the query results, wherein the query results display a potentially impactful device dependency network. By constructing a graph model, the present invention can effectively determine the dependency relationships between devices and perform potential impact analysis, thereby improving equipment management efficiency and optimizing equipment management effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 It is a structural diagram of the equipment asset management system based on the graph model provided by the present invention.

[0020] Figure 2 It is a flow chart of the equipment asset management method based on the graph model provided by the present invention.

[0021] Figure 3 It is the execution result of the equipment asset management method based on the graph model provided by the present invention.

[0022] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0023] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0024] The present invention is described in detail below with reference to the accompanying drawings. The specific operating methods in the method embodiments can also be applied to device embodiments or system embodiments. In the description of the present invention, unless otherwise specified, "at least one" includes one or more. "Multiple" refers to two or more. For example, at least one of A, B, and C includes: A exists alone, B exists alone, A and B exist at the same time, A and C exist at the same time, B and C exist at the same time, and A, B, and C exist at the same time. In the present invention, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0025] The present invention will be described in detail below with reference to specific embodiments.

[0026] In some specific embodiments of the present invention, Figure 1 As shown, this solution provides an equipment asset management system based on a graph model, including: The data module 11 is used to obtain sample data, wherein the sample data includes network devices in the network service architecture and the dependencies between the network devices; A graph model module 12 is configured to construct a graph model based on the sample data, wherein each network device in the network service architecture is a vertex of the graph model, and the dependency relationships between the network devices are edges of the graph model; The query module 13 is configured to receive a query request from a user, perform a query in the graph model based on the query request using a graph query language, and display a query result, wherein the query result displays a potentially impacted device dependency network.

[0027] It's important to note that existing equipment asset management solutions rely on tables or tree structures, making them inefficient for modeling and querying complex many-to-many dependencies. This results in inefficient troubleshooting. Furthermore, when equipment needs arise, such as additions, deletions, or modifications, the system requires rewriting code, which is cumbersome and fails to meet user demands for intelligence and real-time performance.

[0028] Therefore, the present invention obtains network devices and their dependencies through the data module, ensures the integrity and structuring of the input data, and provides a basis for the construction of the graph model; abstracts the devices into vertices and the dependencies into edges through the graph model module, realizes the visual modeling of complex networks, and supports topological expression; uses the query module to use the graph query language to realize rapid impact analysis, quickly locate the potential impact device network, significantly improve the troubleshooting efficiency, and solve the problem that traditional tables or hierarchical structures are difficult to express many-to-many dependencies and have low query efficiency.

[0029] In some possible embodiments of the present invention, Figure 1 As shown, the system further includes an analysis module 14, which is used to: Based on the device-dependent network, analyzing the network devices that the user depends on from top to bottom to obtain a first analysis result; Based on the device dependency network, bottom-up analysis is performed on the impact of the network device failure on the application, service, or user to obtain a second analysis result; Based on the first analysis result and the second analysis result, it is determined whether there is a redundant path in the device-dependent network.

[0030] Specifically, this embodiment provides an implementation for an analysis module. Existing systems lack bidirectional analysis capabilities, unable to simultaneously predict the impact of device failures on users (bottom-up) and the dependence of user needs on devices (top-down). Redundant path determination also relies on manual effort. This invention uses top-down analysis (user → device) to quickly locate key devices that users rely on, optimizing resource allocation. It also uses bottom-up analysis (device → user) to predict the scope of service impact of device failures, enabling proactive early warning. Redundant path determination identifies redundant configurations in the network, improving system disaster recovery and reducing the risk of single points of failure.

[0031] In some possible implementations of the present invention, the graph model module 12 is further configured to: According to the type of network device corresponding to each vertex in the graph model, the attribute of each vertex is defined.

[0032] Specifically, this embodiment provides an implementation for a graph model module. Traditional device attribute definitions are confusing (e.g., using the same fields for different device types), resulting in inaccurate query results and poor model scalability. This embodiment unifies device identifiers through attribute definitions, avoiding data ambiguity and achieving data standardization. Furthermore, attributed vertices can be filtered or aggregated by type, allowing for quick filtering of all virtual machines or specific devices, enhancing query accuracy.

[0033] In some possible implementations of the present invention, the graph model module is specifically used to: When the type of the network device corresponding to the vertex is a server, the attribute of the vertex is defined as the server number; When the type of the network device corresponding to the vertex is a network server virtual machine, the attribute of the vertex is defined as the VM number; When the type of the network device corresponding to the vertex is a database virtual machine, the attribute of the vertex is defined as a DBVM label; When the type of the network device corresponding to the vertex is a website, the attribute of the vertex is defined as a URL; When the type of network device corresponding to the vertex is a customer relationship management system, the attribute of the vertex is defined as a management system number; When the type of the network device corresponding to the vertex is a storage area network, the attribute of the vertex is defined as a SAN number.

[0034] Specifically, this embodiment provides another implementation method for the graph model module. Traditional device attributes lack specific rules (for example, confusion between the terms "SAN number" and "storage area network"), leading to modeling ambiguity. This embodiment specifies the definition rules for vertex attributes and clarifies the attribute fields corresponding to different device types. For example, URL attributes can be used to directly link websites and backend devices, enabling end-to-end dependency tracking and refined modeling. Standardized attribute definitions support seamless integration when adding new device types (such as IoT devices), eliminating terminology inconsistencies, ensuring a one-to-one correspondence between the model and the actual device, and achieving compatibility and scalability.

[0035] In some possible implementations of the present invention, the query result adopts a tree layout structure.

[0036] Specifically, this embodiment provides a query result implementation. Traditionally, complex dependency relationships are displayed in lists or static charts, making it difficult for users to intuitively understand the impact path. This embodiment uses a tree-like layout structure for query results. This tree structure, with the root node (e.g., a faulty device) as the core, expands the hierarchical relationships. This facilitates quick understanding of the impact path and enables intuitive visual management. Furthermore, the tree structure supports operations such as collapsing / expanding nodes and highlighting critical paths, enabling interactive optimization and improving the user experience.

[0037] In some possible implementations of the present invention, the query module uses Cypher or Gremlin graph query language.

[0038] Specifically, this embodiment provides an implementation method for a query module that supports complex path queries (such as multi-hop traversal and pattern matching) through the Cypher (Neo4j) and Gremlin (JanusGraph) languages ​​to achieve efficient queries; it seamlessly integrates the language in the graph database field with the existing graph database technology stack to reduce development costs.

[0039] In some specific embodiments of the present invention, Figure 2 As shown, this solution provides a device asset management method based on a graph model, which is implemented by the device asset management system based on a graph model as described in any of the above embodiments. The method includes: Step 201: Receive a user's query request; Step 202: Based on the query request, query the pre-built graph model using a graph query language and display the query results, wherein the query results display the device dependency network with potential impact in the network service architecture; The graph model is constructed by taking each network device in the network service architecture as a vertex and the dependency relationships between the network devices as edges.

[0040] In some possible embodiments of the present invention, see Figure 2 ,The equipment asset management method based on the graph model also includes: Step 203: Based on the device-dependent network, analyze the network devices that the user depends on from top to bottom to obtain a first analysis result; Step 204: Based on the device-dependent network, analyze the impact of the network device failure on the application, service, or user from the bottom up to obtain a second analysis result; Step 205: Based on the first analysis result and the second analysis result, determine whether there is a redundant path in the device-dependent network.

[0041] Possibly, constructing a graph model based on the sample data further includes: According to the type of network device corresponding to each vertex in the graph model, the attribute of each vertex is defined.

[0042] Possibly, constructing a graph model based on the sample data specifically includes: When the type of the network device corresponding to the vertex is a server, the attribute of the vertex is defined as the server number; When the type of the network device corresponding to the vertex is a network server virtual machine, the attribute of the vertex is defined as the VM number; When the type of the network device corresponding to the vertex is a database virtual machine, the attribute of the vertex is defined as a DBVM label; When the type of the network device corresponding to the vertex is a website, the attribute of the vertex is defined as a URL; When the type of network device corresponding to the vertex is a customer relationship management system, the attribute of the vertex is defined as a management system number; When the type of the network device corresponding to the vertex is a storage area network, the attribute of the vertex is defined as a SAN number.

[0043] Possibly, Cypher or Gremlin graph query languages ​​are used to query the graph model.

[0044] Possibly, the query results adopt a tree layout structure.

[0045] An embodiment of the present invention discloses an equipment asset management system and method based on a graph model, which includes a data module for obtaining sample data; wherein the sample data includes a network service architecture; a graph model module for constructing a graph model based on the sample data; wherein each component device in the network service architecture is used as a vertex, and the dependency relationship between the devices is used as an edge; a query module for obtaining a user's query request, transmitting the query request to the graph model for query, and displaying the feedback query result, wherein the query result shows a potentially influential device dependency network; its beneficial effect is: through the constructed graph model, the entire life cycle of the equipment can be traced, the equipment association relationship can be visualized, and management personnel can be helped to effectively judge the dependency relationship between the equipment, and on this basis, potential impact analysis can be performed, thereby improving equipment management efficiency and optimizing equipment management effects.

[0046] In a specific embodiment, the equipment asset management system based on the graph model includes: a data module, a scale of sample data, a graph model module, and a query module; The data module is used to obtain sample data; the sample data includes a network service architecture.

[0047] In a possible embodiment, the sample data can be manually constructed based on public white papers and public models of web conferences. The web service architecture includes: Dependencies between servers, web server VMs, database VMs, websites, customer relationship management systems, storage area networks, and devices; these are examples of network service architecture devices and are not intended to be limiting; In a possible embodiment, the sample data scale includes: 7 servers, 5 network server virtual machines, 5 database virtual machines, 10 websites, 3 customer relationship management systems, 2 storage area networks, and 85 device dependencies. It should be noted that this embodiment uses network-related devices as an example and is not intended to be limiting.

[0048] A graph model module is used to construct a graph model based on the sample data; wherein each component device in the network service architecture is used as a vertex and the dependency relationship between the devices is used as an edge.

[0049] In a possible embodiment, referring to Table 1, Table 1 shows the correspondence between the vertex type and the vertex tree of the graph model. For example, when the vertex type is a website, the corresponding attribute is a URL; When the point type is a network server virtual machine, the corresponding attribute is the VM number; When the point type is server, the corresponding attribute is the server number; When the point type is storage area network, the corresponding attribute is SAN number; When the point type is a database virtual machine, the corresponding attribute is the DBVM label; When the point type is customer relationship management system, the corresponding attribute is the management system number.

[0050] Table 1

[0051] Correspondingly, the edge types in the graph model of this embodiment are shown in Table 2.

[0052] Table 2

[0053] The query module is used to obtain the user's query request, transmit the query request to the graph model for query, and display the feedback query results. The query results show the potentially affected device dependency network.

[0054] In a possible embodiment, a graph query language such as Cypher or Gremlin is used when applying. When querying, all devices that depend on the queried device are first queried, then the potentially affected devices and services are obtained, and finally the potentially affected network is displayed, and when displaying, it is displayed in a tree layout.

[0055] Furthermore, an impact analysis is conducted on this basis. The analysis process is as follows: a) From top to bottom, find the network devices that a specific user (group) relies on - applications, services, virtual machines, physical devices, data centers, routers, switches, optical fibers, etc. b) Bottom-up analysis of whether applications, services, and users (groups) will be affected by a specific network device failure; c) For a specific user, is there any redundant part in the entire network? Overall, graph model technology can improve the intelligence of equipment asset management based on the relationship between things. When inferring complex events based on the underlying network event flow, it can evaluate the impact of events based on the graph model and determine whether to take necessary remedial measures.

[0056] Specifically, the entire network is the logical network scope relative to the set of devices associated with a specific user request. Its boundary is dynamically determined based on the context of the query request, covering the dependent devices and their interconnected relationships that may be involved in the user access path.

[0057] When analyzing the path topology, the system identifies possible redundant configurations based on the connection structure and service connection capabilities of nodes at the same level in the graph model, and then provides auxiliary decision-making information for reference by operation and maintenance personnel.

[0058] To better understand this solution, the following example uses specific business requirements to illustrate.

[0059] Example 1: Figure 3 As shown, Business Request 1: In asset equipment management, what are the possible impacts caused by a failure of server "Server07"? Specifically, the dependency relationship between devices is very complex. The queried device not only depends on server07 but also has functional dependencies on other devices, as can be seen in Table 2.

[0060] Query instructions for business requirement 1: To analyze the impact of the server "Server07" failure, query its associated devices; Explore the websites or management systems that may be served by the affected devices to determine the potential impact of the failed server and display the potential impact network of the failed server.

[0061] Query statement: / / Query the content that depends on the server "Server07" in the asset equipment relationship network, such as server, network / Database virtual machines, etc. MATCH p=(n3:storage area network)<-[r3]-(n2:server {server number: "Server07"})<[r2]-(n:server)<-[r]-(m)<-[r1]-(n1:website) WITH p ,m / / Query the customer relationship management system that depends on the affected database virtual machine OPTIONAL MATCH q=(m)<-[r4]-(n4:Customer Relationship Management System) / / The relationship network affected by the failure of server "Server07" (recommended layout: tree layout) RETURN p,q.

[0062] According to the returned results, we can see all virtual machines, databases, customer relationship management systems (CRMs), and web pages that depend on "Server 07," such as "Server 03," "Server 02," and "Web Page 08." This means that if Server 07 fails, these services may also be affected.

[0063] When applying, there are some devices and services that are only dependent on a single server. When the dependent server fails, these devices will definitely be affected. When querying the devices that depend on the faulty device, by querying and judging whether the dependent devices only depend on the faulty device, the devices that will definitely be affected are returned. Then, with the previous detection result as the faulty device, the above operation is repeated to obtain the devices that only depend on this faulty device, and finally the network affected by the faulty device is obtained.

[0064] A more common scenario in real life is when an administrator discovers that a website is not displaying. The administrator needs to investigate the server and database devices that the website relies on to find the problem. In Case Request 2, we will examine the cause of the problem that "Page 04" cannot be displayed. Business Request 2: What is the problem that causes “Web Page 04” to not display? Query description: To know why the website cannot be displayed, query the relevant devices in the network associated with page 04; Displays the network of devices associated with the problematic website.

[0065] Query statement: / / Query all devices that the website "URL04" depends on MATCH(n:website{website number:"URL04"})-[r*1 ..4]->(m) / / Return the relationship network of all possible reasons why the website "URL04" is down RETURN p.

[0066] from Figure 3As we can see, according to the returned results, we can find all the devices that the web page URL04 relies on for operation, including the network server "WEBVM02", server "SERVER02" and storage area network "SAN01", etc. We can check the working status of each device one by one to troubleshoot the problem.

[0067] Through the processing process of the above embodiment, it can be seen that by adopting the above scheme, the originally discrete asset equipment is integrated through the constructed graph model, the deployment status of these equipment assets is presented, the entire life cycle of the equipment is traced, the equipment association relationship is visualized, the intelligence level of equipment asset management is improved, and managers are helped to effectively judge the dependency relationship between equipment, and on this basis, potential impact analysis is carried out, thereby improving equipment management efficiency and optimizing equipment management effects.

[0068] In a specific embodiment, a graph-based equipment asset management method is provided, which is applied to any of the above-mentioned graph-based equipment asset management systems. The method includes: S100: Obtain sample data; wherein the sample data includes a network service architecture.

[0069] Specifically, the network service architecture includes: dependencies between servers, network server virtual machines, database virtual machines, websites, customer relationship management systems, storage area networks, and devices; Sample data size: The sample data includes 7 servers, 5 network server virtual machines, 5 database virtual machines, 10 websites, 3 customer relationship management systems, 2 storage area networks, and 85 dependencies between devices.

[0070] S200 , constructing a graph model based on sample data; wherein, each component device in the network service architecture is used as a vertex, and the dependency relationship between the devices is used as an edge.

[0071] Specifically, when the point type is website, the corresponding attribute is URL; When the point type is a network server virtual machine, the corresponding attribute is the VM number; When the point type is server, the corresponding attribute is the server number; When the point type is storage area network, the corresponding attribute is SAN number; When the point type is a database virtual machine, the corresponding attribute is the DBVM label; When the point type is customer relationship management system, the corresponding attribute is the management system number.

[0072] S300: Obtain a query request from the user, transmit the query request to the graph model for query, and display the feedback query result, which shows that the device with potential impact depends on the network.

[0073] Specifically, when applied, the graph database adopts graph query languages ​​such as Cypher and Gremlin; when querying, first query all devices that depend on the queried device, then obtain the potentially affected devices and services, and finally display the potential impact network, and when displaying, display it in a tree layout.

[0074] By adopting the above method and utilizing the constructed graph model, the originally discrete assets and equipment are integrated, the deployment status of these equipment assets is presented, the entire life cycle of the equipment is traced, the equipment association relationship is visualized, the intelligence level of equipment asset management is improved, and managers can effectively judge the dependencies between equipment and conduct potential impact analysis on this basis, thereby improving equipment management efficiency and optimizing equipment management effects.

[0075] The present invention provides a graph-based device asset management system and method. By constructing a graph model, this system and method helps managers effectively determine the dependencies between devices and conduct potential impact analysis, thereby improving device management efficiency and optimizing device management effectiveness. The core of this system and method lies in constructing a graph model, in which the components of a network service architecture are considered as vertices of the graph, and the dependencies between devices constitute the edges of the graph. In this way, the entire life cycle of a device can be traced and its relationships can be visualized. The benefit of this method is that it enables managers to more clearly understand the interactions and dependencies between devices, thereby making more effective decisions during the device management process. The present invention integrates previously discrete asset devices through the constructed graph model, presents the deployment status of these device assets, traces the entire life cycle of the device, and visualizes the device relationships, thereby improving the intelligence of device asset management, helping managers effectively determine the dependencies between devices and conduct potential impact analysis based on this, thereby improving device management efficiency and optimizing device management effectiveness. In addition, the system also includes a data module and a query module. The data module is responsible for obtaining sample data, including network service architecture, while the query module processes user query requests, transmits the requests to the graph model for query, and displays the query results, which include the network dependency of potentially impactful devices. The application of this method not only improves the efficiency of equipment management, but also optimizes the effectiveness of equipment management. Through the constructed graph model, managers can better understand the operating status, dependencies, and potential impacts of the equipment, which is of great significance for preventing equipment failures, optimizing resource allocation, and improving production efficiency. In addition, this method also provides a new means for training engineers and operators. Through 3D simulation teaching, users can more intuitively understand the structure, working principle, and operating process of the equipment, thereby improving operational skills and safety.

[0076] Figure 4 An example of a physical structure diagram of an electronic device is shown below. Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430, and a communications bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other via the communications bus 440. The processor 410 may call logic instructions in the memory 430 to execute a device asset management method based on a graph model, the method comprising: receiving a query request from a user; based on the query request, querying a pre-built graph model using a graph query language, and displaying the query results, wherein the query results display a potentially impactful device dependency network in the network service architecture; wherein the graph model is constructed by taking each network device in the network service architecture as a vertex and the dependency relationships between the network devices as edges.

[0077] Furthermore, the logic instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0078] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the device asset management method based on the graph model provided by the above methods, the method including: receiving a user's query request; based on the query request, using a graph query language to query in a pre-constructed graph model, and displaying the query results, the query results displaying a device dependency network with potential impact in the network service architecture; wherein, the graph model is obtained by taking each network device in the network service architecture as a vertex and the dependency relationship between each of the network devices as an edge.

[0079] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the graph model-based device asset management method provided by the above-mentioned methods, the method comprising: receiving a user's query request; based on the query request, using a graph query language to query in a pre-constructed graph model, and displaying the query results, wherein the query results display a potentially influential device dependency network in the network service architecture; wherein the graph model is obtained by taking each network device in the network service architecture as a vertex and the dependency relationship between each of the network devices as an edge.

[0080] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0081] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, 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 various embodiments of the present invention.

Claims

1. A device asset management system based on a graph model, characterized in that: include: A data module is used to obtain sample data, wherein the sample data includes network devices in the network service architecture and dependencies between the network devices; A graph model module, configured to construct a graph model based on the sample data, wherein each network device in the network service architecture is a vertex of the graph model, and the dependency relationships between the network devices are edges of the graph model; The query module is used to receive a user's query request, perform a query in the graph model based on the query request using a graph query language, and display the query result, wherein the query result displays the device dependency network with potential impact.

2. The equipment asset management system based on the graph model according to claim 1, characterized in that: The system further comprises an analysis module for: Based on the device-dependent network, analyzing the network devices that the user depends on from top to bottom to obtain a first analysis result; Based on the device dependency network, bottom-up analysis is performed on the impact of the network device failure on the application, service, or user to obtain a second analysis result; Based on the first analysis result and the second analysis result, it is determined whether there is a redundant path in the device-dependent network.

3. The equipment asset management system based on the graph model according to claim 1, characterized in that: The graph model module is also used to: According to the type of network device corresponding to each vertex in the graph model, the attribute of each vertex is defined.

4. The method according to claim 3, characterized in that The graph model module is specifically used for: When the type of the network device corresponding to the vertex is a server, the attribute of the vertex is defined as the server number; When the type of the network device corresponding to the vertex is a network server virtual machine, the attribute of the vertex is defined as the VM number; When the type of the network device corresponding to the vertex is a database virtual machine, the attribute of the vertex is defined as a DBVM label; When the type of the network device corresponding to the vertex is a website, the attribute of the vertex is defined as a URL; When the type of network device corresponding to the vertex is a customer relationship management system, the attribute of the vertex is defined as a management system number; When the type of the network device corresponding to the vertex is a storage area network, the attribute of the vertex is defined as a SAN number.

5. The equipment asset management system based on the graph model according to claim 1, characterized in that: The query result adopts a tree layout structure.

6. The equipment asset management system based on a graph model according to any one of claims 1 to 5, characterized in that: The query module uses Cypher or Gremlin graph query language.

7. A device asset management method based on a graph model, characterized in that: The method is implemented by the equipment asset management system based on the graph model according to any one of claims 1 to 6, and includes: Receive user query requests; Based on the query request, querying in a pre-built graph model using a graph query language and displaying query results, wherein the query results display a potentially impactful device dependency network in the network service architecture; The graph model is constructed by taking each network device in the network service architecture as a vertex and the dependency relationships between the network devices as edges.

8. The device asset management method based on the graph model according to claim 7, characterized in that: The method further comprises: Based on the device-dependent network, analyzing the network devices that the user depends on from top to bottom to obtain a first analysis result; Based on the device dependency network, bottom-up analysis is performed on the impact of the network device failure on the application, service, or user to obtain a second analysis result; Based on the first analysis result and the second analysis result, it is determined whether there is a redundant path in the device-dependent network.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the device asset management method based on the graphical model as described in any one of claims 7-8 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the device asset management method based on the graph model as described in any one of claims 7 to 8 is implemented.

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