CN114978946B - Node fault diagnosis method and device, electronic equipment and storage medium - Google Patents
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Abstract
The disclosure provides a node fault diagnosis method, a node fault diagnosis device, electronic equipment and a storage medium, and relates to the technical field of knowledge maps. The method comprises the following steps: acquiring target node objects to be diagnosed and relation information; according to the target node object to be diagnosed and the relation information, node objects conforming to the relation information with the target node object are screened out from a pre-constructed product service resource knowledge graph; detecting whether the screened node object meets a preset fault condition; and marking and displaying the node objects meeting the preset fault conditions. The method and the device can quickly check out the fault node from the large-scale node data and display the fault node in the mark, improve the operation and maintenance efficiency and improve the user experience.
Description
Technical Field
The disclosure relates to the technical field of knowledge maps, and in particular relates to a node fault diagnosis method, a node fault diagnosis device, electronic equipment and a storage medium.
Background
The data of the operator resource nodes, the service capability nodes, the product nodes and the like are important components of the new generation cloud network operation system. Currently, the integration level of telecommunication Product Service Resources (PSR) is not high, and the data display dimension is insufficient, so that data dispersion is caused. When faced with large-scale data, troubleshooting potential failed nodes is inefficient. This would hamper intensive research efforts on telecommunication product service resources. In order to promote research of a new generation cloud network operation system, research work of integrating various existing telecommunication product service resources and accelerating automatic troubleshooting of fault node data is urgently needed.
It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the present disclosure and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The disclosure provides a node fault diagnosis method, a node fault diagnosis device, electronic equipment and a storage medium, which at least overcome the technical problem that a fault node is difficult to quickly check and diagnose in the face of large-scale node data in the related technology to a certain extent.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
According to one aspect of the present disclosure, there is provided a node fault diagnosis method, the method comprising: acquiring target node objects to be diagnosed and relation information; according to the target node object to be diagnosed and the relation information, node objects conforming to the relation information with the target node object are screened out from a pre-constructed product service resource knowledge graph; detecting whether the screened node object meets a preset fault condition; and marking and displaying the node objects meeting the preset fault conditions.
In some embodiments, the method further comprises: obtaining a node type of the target node object, wherein the node type comprises: source node and/or target node.
In some embodiments, the relationship information includes: object relationships and object region relationships; according to the target node object to be diagnosed and the relation information, the node object conforming to the relation information with the target node object is screened from a pre-constructed product service resource knowledge graph, and the method comprises the following steps: according to the target node object to be diagnosed and the object relation, product service resource node objects conforming to the object relation with the target node object are screened out from a pre-constructed product service resource knowledge graph; and screening out the regional node objects which accord with the target node object with the object regional relationship from a pre-constructed product service resource knowledge graph according to the target node object to be diagnosed and the object regional relationship.
In some embodiments, the target node object is a node object that provides a product service or resource for an operator, and the object relationship at least includes: containment, carrying, dependency, partitioning, splicing, perforation; the object region relationship includes at least: in design, to be audited, in audit, online, offline, and disabled.
In some embodiments, before the node object conforming to the relationship information with the target node object is screened from the pre-constructed product service resource knowledge graph according to the target node object to be diagnosed and the relationship information, the method further comprises: acquiring a product service resource object file, wherein the product service resource object file contains attribute information of one or more product service resource objects; obtaining a product service resource object relation file, wherein the product service resource object relation file contains the relation among all product service resource objects; acquiring an area file, wherein the area file contains attribute information of one or more areas; obtaining an object region relation file, wherein the object region relation file contains the relation between each object and a region; and constructing a product service resource knowledge graph according to the product service resource object file, the product service resource object relation file, the region file and the object region relation file.
In some embodiments, constructing a product service resource knowledge graph according to the product service resource object file, the product service resource object relationship file, the region file, and the object region relationship file includes: and importing the product service resource object file, the product service resource object relation file, the region file and the object region relation file into a map database to generate a product service resource knowledge graph.
In some embodiments, the graph database is a Neo4J database.
In some embodiments, the method further comprises: displaying the network topology information of the product service resource knowledge graph at the front end by using Vue and D3. Js; the Spring Boot framework is used so that the backend responds to requests from the front end.
According to an aspect of the present disclosure, there is also provided a node failure diagnosis apparatus including: the data acquisition module is used for acquiring the target node object to be diagnosed and the relation information; the data screening module is used for screening out node objects which accord with the relation information from a pre-constructed product service resource knowledge graph according to the target node objects to be diagnosed and the relation information; the fault diagnosis module is used for detecting whether the screened node object meets a preset fault condition; the fault display module is used for displaying the node objects meeting the preset fault conditions in a marked mode.
According to one aspect of the present disclosure, there is also provided an electronic device including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the node fault diagnosis method of any one of the above via execution of the executable instructions.
According to an aspect of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the node failure diagnosis method of any one of the above.
According to the node fault diagnosis method, the node fault diagnosis device, the electronic equipment and the storage medium, through construction of the product service resource knowledge graph, the node objects conforming to the relation information with the target node objects can be screened out from the pre-constructed product service resource knowledge graph according to the target node objects to be diagnosed and the relation information, whether the screened node objects meet preset fault conditions or not is detected, and finally the node objects meeting the preset fault conditions are marked and displayed. According to the embodiment of the disclosure, the fault node can be rapidly arranged from the large-scale node data and marked for display, so that the operation and maintenance efficiency is improved, and the user experience is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort.
FIG. 1 illustrates a flow chart of a node fault diagnosis method in an embodiment of the present disclosure;
FIG. 2 illustrates a node object screening flow diagram in an embodiment of the present disclosure;
FIG. 3 illustrates an object relationship selection page diagram in an embodiment of the present disclosure;
FIG. 4 illustrates an object region relationship selection page diagram in an embodiment of the present disclosure;
FIG. 5 illustrates a knowledge graph construction flow chart in an embodiment of the present disclosure;
FIG. 6 illustrates a flowchart of a particular implementation of a node failure diagnosis method in an embodiment of the present disclosure;
FIG. 7 illustrates a failed node presentation page schematic in an embodiment of the present disclosure;
FIG. 8 illustrates a schematic diagram of a node failure diagnosis apparatus in an embodiment of the present disclosure;
FIG. 9 shows a block diagram of an electronic device in an embodiment of the disclosure;
fig. 10 shows a schematic diagram of a computer-readable storage medium in an embodiment of the disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.
For ease of understanding, before describing embodiments of the present disclosure, several terms referred to in the embodiments of the present disclosure are first explained as follows:
knowledge graph: a data structure consisting of objects, relationships and attributes.
PSR: product Service resource, product service resources.
The following detailed description of embodiments of the present disclosure refers to the accompanying drawings.
Firstly, the embodiment of the disclosure provides a node fault diagnosis method to achieve the purpose of quickly checking out a fault node from large-scale node data and displaying marks, and the method can be executed by any electronic device with calculation processing capability.
In some embodiments, the node fault diagnosis method provided in the embodiments of the present disclosure may be performed by a terminal device; in other embodiments, the node fault diagnosis method provided in the embodiments of the present disclosure may be performed by a server; in other embodiments, the node fault diagnosis method provided in the embodiments of the present disclosure may be implemented by the terminal device and the server in an interactive manner.
The terminal device may be a variety of electronic devices including, but not limited to, smartphones, tablets, laptop portable computers, desktop computers, wearable devices, augmented reality devices, virtual reality devices, and the like.
Alternatively, the clients of the applications installed in different terminal devices are the same or clients of the same type of application based on different operating systems. The specific form of the application client may also be different based on the different terminal platforms, for example, the application client may be a mobile phone client, a PC client, etc.
The server may be a server providing various services, such as a background management server providing support for devices operated by the user with the terminal device. The background management server can analyze and process the received data such as the request and the like, and feed back the processing result to the terminal equipment.
Optionally, the server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs (Content Delivery Network, content delivery networks), basic cloud computing services such as big data and artificial intelligence platforms, and the like.
The medium providing the communication link between the terminal device and the server may be a wired network or a wireless network. Alternatively, the wireless network or wired network uses standard communication techniques and/or protocols. The network is typically the Internet, but may be any network including, but not limited to, a local area network (Local Area Network, LAN), metropolitan area network (Metropolitan Area Network, MAN), wide area network (Wide Area Network, WAN), mobile, wired or wireless network, private network, or any combination of virtual private networks. In some embodiments, data exchanged over a network is represented using techniques and/or formats including HyperText Mark-up Language (HTML), extensible markup Language (Extensible MarkupLanguage, XML), and the like. All or some of the links may also be encrypted using conventional encryption techniques such as secure sockets layer (Secure Socket Layer, SSL), transport layer security (Transport Layer Security, TLS), virtual private network (Virtual Private Network, VPN), internet protocol security (Internet ProtocolSecurity, IPsec), etc. In other embodiments, custom and/or dedicated data communication techniques may also be used in place of or in addition to the data communication techniques described above.
Fig. 1 shows a flowchart of a node fault diagnosis method in an embodiment of the present disclosure, and as shown in fig. 1, the node fault diagnosis method provided in the embodiment of the present disclosure includes the following steps:
s102, obtaining the object of the target node to be diagnosed and the relation information.
It should be noted that, the target node object to be diagnosed in S102 may be any node object, in some embodiments, may be a node object serving as a source node, in other embodiments, may be a node object serving as a destination node, and in order to more comprehensively analyze the node object, the target node object may be selected as the source node and the destination node at the same time, so as to analyze all node objects associated when the node object serves as the source node and the destination node. The relationship information in S102 refers to information about the relationship between the target node object and other node objects.
It should be noted that, the node object in the embodiment of the present disclosure may be, but is not limited to, a product service resource node and an area node, where the product service resource node corresponds to a product service resource provided by the product service resource node; the regional nodes correspond to a predetermined region (which may be, but not limited to, a geographically divided region).
Thus, in some embodiments, the method further comprises: obtaining a node type of the target node object, wherein the node type comprises: source node and/or target node.
S104, according to the target node object to be diagnosed and the relation information, the node object which accords with the relation information with the target node object is screened out from a pre-constructed product service resource knowledge graph.
In the embodiment of the disclosure, in order to analyze large-scale node data, a product service resource knowledge graph including a plurality of product service resource nodes and region nodes is constructed according to the large-scale node data, so that other node objects having a certain relationship with a target node can be rapidly analyzed based on the product service resource knowledge graph.
S106, detecting whether the screened node object meets a preset fault condition.
It should be noted that, the preset fault condition in the embodiment of the present disclosure may be a condition that characterizes that there is an abnormality in the node data, and after node objects that conform to the relationship information with the target node objects are screened out from the pre-constructed product service resource knowledge graph according to the target node objects to be diagnosed and the relationship information, whether the data of the node objects meets the preset fault condition is detected one by one.
S108, marking and displaying the node objects meeting the preset fault conditions.
In order to facilitate operation and maintenance personnel to quickly understand a fault node, after node objects meeting preset fault conditions are detected, the node objects can be marked and displayed, and the marking mode of the fault node is not particularly limited in the embodiment of the disclosure, so long as the fault node can be highlighted. In some embodiments, node objects that meet a preset fault condition may be highlighted.
As can be seen from the foregoing, according to the node fault diagnosis method, apparatus, electronic device and storage medium provided by the embodiments of the present disclosure, by constructing a product service resource knowledge graph, a node object that accords with relationship information with a target node object can be screened out from a pre-constructed product service resource knowledge graph according to the target node object and relationship information to be diagnosed, so as to detect whether the screened node object meets a preset fault condition, and finally, the node object that meets the preset fault condition is marked and displayed. According to the embodiment of the disclosure, the fault node can be rapidly arranged from the large-scale node data and marked for display, so that the operation and maintenance efficiency is improved, and the user experience is improved.
It should be noted that the above relationship information may include, but is not limited to: object relationships and object region relationships; the object relationship is used for representing the relationship between the node objects, and the object region relationship is used for representing the relationship between the node objects and the region node objects.
In some embodiments, in the case where the relationship information includes the object relationship and the object region relationship, as shown in fig. 2, the node fault diagnosis method provided in the embodiments of the present disclosure may screen the node object that conforms to the relationship information with the target node object, including:
s202, according to a target node object to be diagnosed and an object relation, a product service resource node object which accords with the object relation with the target node object is screened out from a pre-constructed product service resource knowledge graph;
s204, according to the target node object to be diagnosed and the object region relation, the region node object which accords with the target node object with the object region relation is screened out from a pre-constructed product service resource knowledge graph.
In some embodiments, the target node object is a node object that provides a product service or resource for an operator, and the object relationship in the embodiments of the present disclosure at least includes: containment, carrying, dependency, partitioning, splicing, perforation; the object region relation in the embodiment of the disclosure at least comprises: in design, to be audited, in audit, online, offline, and disabled. FIG. 3 illustrates an object relationship selection page; FIG. 4 illustrates an object region relationship selection page. As shown in fig. 3, the object relationships support full, single, or multiple choices; the target node object may be selected as a source node, the target node may be selected as a destination node, or the target node may be selected as a source node and a target node. As shown in FIG. 4, in the object region relationship selection page, the object region relationship supports full selection, single selection, or multiple selection.
In some embodiments, as shown in fig. 5, the node fault diagnosis method provided in the embodiments of the present disclosure may construct a product service resource knowledge graph by:
s502, acquiring a product service resource object file, wherein the product service resource object file contains attribute information of one or more product service resource objects;
s504, obtaining a product service resource object relation file, wherein the product service resource object relation file contains the relation among the product service resource objects;
s506, acquiring an area file, wherein the area file contains attribute information of one or more areas;
s508, obtaining an object region relation file, wherein the object region relation file contains the relation between each object and the region;
s510, constructing a product service resource knowledge graph according to the product service resource object file, the product service resource object relation file, the area file and the object area relation file.
It should be noted that, the information stored in the product service resource object file in the embodiment of the present disclosure includes, but is not limited to: name, code, attribute information (JSON array structure) of the product service resource object, etc.; the specific field information is shown in table 1.
TABLE 1
The information stored in the product service resource object relationship file in the embodiments of the present disclosure includes, but is not limited to: a primary key ID of a source node, a name of the source node, a code of the source node, a primary key ID of a destination node, a name of the destination node, a code of the destination node, an object relationship name and the like; the specific field information is shown in table 2.
TABLE 2
Information stored in the region file in the embodiments of the present disclosure includes, but is not limited to: name of the region, coding, etc.; the specific field information is shown in table 3.
TABLE 3 Table 3
| Fields | Interpretation of the drawings | Sample example |
| id | Main key id | 111 |
| regionName | Zone name | Guangdong province |
| regionCode | Region coding | 1880000 |
Information stored in the region file in the embodiments of the present disclosure includes, but is not limited to: the main key ID of the product service resource object, the name of the product service resource object, the code of the product service resource object, the main key ID of the region, the name of the region, the code of the region, the object region relation and the like; the specific field information is shown in table 4.
TABLE 4 Table 4
| Fields | Interpretation of the drawings | Sample example |
| id | Main key id | 1 |
| PSRId | PSR primary key id | 2 |
| PSRCode | PSR coding | cfsFixAccessNetLine |
| PSRName | PSR name | Fixed network access special line CFS |
| regionName | Zone name | Guangdong province |
| regionCode | Region coding | 1880000 |
| relationName | The state of the PSR object in the current region | Wire feeding |
In some embodiments, constructing a product service resource knowledge graph from a product service resource object file, a product service resource object relationship file, a region file, and an object region relationship file includes: and importing the product service resource object file, the product service resource object relation file, the region file and the object region relation file into a map database to generate a product service resource knowledge map.
In some embodiments, the graph database is a Neo4J database.
In some embodiments, the node fault diagnosis method provided in the embodiments of the present disclosure further includes the following steps: displaying the network topology information of the product service resource knowledge graph at the front end by using Vue and D3. Js; the Spring Boot framework is used so that the backend responds to requests from the front end.
After the data in the product service resource object file, the product service resource object relation file, the area file and the object area relation file are imported into the Neo4J database, the front end displays network topology data by combining technologies such as Vue and D3.Js, and the rear end responds to the front end request by using a Spring Boot frame.
When a user selects a certain node object, the page displays all PSR object nodes which take the node as a source node and/or a destination node and meet the selected relation type and area nodes which are in accordance with the selected object-area relation, then the program automatically checks whether the data meets the specification or not according to a corresponding predefined object node data logic specification table, the specific field information is shown in a table 5, if the data does not meet, the corresponding PSR object nodes are set to be highlighted in red for further checking and verification by the user.
TABLE 5
| Fields | Interpretation of the drawings | Sample example |
| id | Main key id | 1111 |
| PSRId | PSR primary key id | 2 |
| PSRCode | PSR coding | cfsFixAccessNetLine |
| PSRName | PSR name | Fixed network access special line CFS |
| isTgt | Whether or not the target node is identified | TRUE |
| conformanceSpecification | Object-region relationship agreement specification | [ "on line", "in audit"] |
Fig. 6 shows a specific implementation flow of a node fault diagnosis method in an embodiment of the disclosure, as shown in fig. 6, including:
s602, constructing a product service resource data set;
s604, constructing a product service resource object file according to the product service resource information;
s606, constructing a product service resource object relation file;
s608, constructing a region file according to the region information;
s610, constructing an object region relation file;
s612, constructing a node data logic specification for detecting whether the node object meets a preset fault condition;
s614, importing a Neo4J database;
s616, selecting a target node object to be diagnosed;
s618, detecting whether other node data associated with the target node object accords with a preset data logic specification (if not, a preset fault condition is met) (namely, the node data accords with a node data logic specification table); if yes, executing S620; if not, then S622 is performed.
S620, normally displaying the node object.
S622 highlights the failed node object.
From the above, it can be seen that the node fault diagnosis method provided in the embodiment of the present disclosure fuses product service resources and regional network topology data of an operator, builds a product service resource knowledge graph by means of the NEO4J database, can realize automatic troubleshooting of the fault node in large-scale data, is beneficial to analysis and mining of important data information by a user, improves user experience, and can provide assistance for construction and further optimization of a new generation cloud network operation system.
Assume that when the user selects an A node object, and the selected node type is "source node", the object relationship selects "dependency", and the object region relationship selects "online"; at this time, the back-end program performs object region relationship check on all the associated node objects according to the object region relationship coincidence specification of table 5, and highlights the associated node objects that do not coincide with "online". As shown in fig. 7, the node a object depends on the node B, C, D, E object, and the node a object belongs to the "on line" state in the four areas, so the node B, C, D, E object also belongs to the "on line" state for the four areas, and accords with logic, so the node B in the figure is in the "off line" state for the area "Tianjin", does not accord with the data logic, and is highlighted for the user to further manually judge the inspection data.
Based on the same inventive concept, a node fault diagnosis device is also provided in the embodiments of the present disclosure, as described in the following embodiments. Since the principle of solving the problem of the embodiment of the device is similar to that of the embodiment of the method, the implementation of the embodiment of the device can be referred to the implementation of the embodiment of the method, and the repetition is omitted.
Fig. 8 is a schematic view of a node fault diagnosis apparatus according to an embodiment of the disclosure, as shown in fig. 8, the apparatus includes: a data acquisition module 81, a data screening module 82, a fault diagnosis module 83, and a fault display module 84.
The data acquisition module 81 is configured to acquire a target node object to be diagnosed and relationship information; the data screening module 82 is configured to screen node objects that conform to relationship information with the target node objects from a pre-constructed product service resource knowledge graph according to the target node objects to be diagnosed and the relationship information; the fault diagnosis module 83 is configured to detect whether the screened node object meets a preset fault condition; the fault display module 84 is configured to display a node object that meets a preset fault condition in a marked manner.
It should be noted that, the data obtaining module 81, the data filtering module 82, the fault diagnosing module 83 and the fault displaying module 84 correspond to S102 to S108 in the method embodiment, and the foregoing modules are the same as examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in the method embodiment. It should be noted that the modules described above may be implemented as part of an apparatus in a computer system, such as a set of computer-executable instructions.
As can be seen from the foregoing, the node fault diagnosis device provided by the embodiment of the present disclosure, by constructing a product service resource knowledge graph, can screen out a node object conforming to the relationship information with a target node object from a pre-constructed product service resource knowledge graph according to the target node object and the relationship information to be diagnosed by the data screening module 82 after acquiring the target node object and the relationship information to be diagnosed by the data acquisition module 81, further detect whether the screened node object meets a preset fault condition by the fault diagnosis module 83, and finally mark and display the node object meeting the preset fault condition by the fault display module 84. According to the embodiment of the disclosure, the fault node can be rapidly arranged from the large-scale node data and marked for display, so that the operation and maintenance efficiency is improved, and the user experience is improved.
In some embodiments, the data acquisition module 81 is further configured to: obtaining a node type of a target node object, wherein the node type comprises: source node and/or target node.
In some embodiments, the relationship information includes: object relationships and object region relationships; the data screening module 82 is also configured to: according to the target node object to be diagnosed and the object relation, product service resource node objects conforming to the object relation with the target node object are screened out from a pre-constructed product service resource knowledge graph; and screening out the regional node objects which accord with the target node objects in the object regional relationship from the pre-constructed product service resource knowledge graph according to the target node objects to be diagnosed and the object regional relationship.
In some embodiments, the target node object is a node object that provides a product service or resource for an operator, and the object relationship includes at least: containment, carrying, dependency, partitioning, splicing, perforation; the object region relationship includes at least: in design, to be audited, in audit, online, offline, and disabled.
In some embodiments, the node fault diagnosis apparatus provided in the embodiments of the present disclosure further includes: the knowledge graph construction module 85 is configured to: acquiring a product service resource object file, wherein the product service resource object file contains attribute information of one or more product service resource objects; obtaining a product service resource object relation file, wherein the product service resource object relation file contains the relation among the product service resource objects; acquiring an area file, wherein the area file contains attribute information of one or more areas; obtaining an object region relation file, wherein the object region relation file contains the relation between each object and a region; and constructing a product service resource knowledge graph according to the product service resource object file, the product service resource object relation file, the region file and the object region relation file.
In some embodiments, the knowledge graph construction module is further configured to: and importing the product service resource object file, the product service resource object relation file, the region file and the object region relation file into a map database to generate a product service resource knowledge map.
In some embodiments, the graph database is a Neo4J database.
In some embodiments, the node fault diagnosis apparatus provided in the embodiments of the present disclosure further includes: the front end display module 86 is configured to display, at the front end, network topology information of the product service resource knowledge graph using Vue and d3. Js; the back-end response module 87 is configured to use the Spring Boot framework to enable the back-end to respond to the request from the front-end.
Those skilled in the art will appreciate that the various aspects of the present disclosure may be implemented as a system, method, or program product. Accordingly, various aspects of the disclosure may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.
An electronic device 900 according to such an embodiment of the present disclosure is described below with reference to fig. 9. The electronic device 900 shown in fig. 9 is merely an example and should not be construed to limit the functionality and scope of use of embodiments of the present disclosure in any way.
As shown in fig. 9, the electronic device 900 is embodied in the form of a general purpose computing device. Components of electronic device 900 may include, but are not limited to: the at least one processing unit 910, the at least one storage unit 920, and a bus 930 connecting the different system components (including the storage unit 920 and the processing unit 910).
Wherein the storage unit stores program code that is executable by the processing unit 910 such that the processing unit 910 performs steps according to various exemplary embodiments of the present disclosure described in the above-described "exemplary methods" section of the present specification. For example, the processing unit 910 may perform the following steps of the method embodiment described above: acquiring target node objects to be diagnosed and relation information; according to the target node object to be diagnosed and the relation information, node objects conforming to the relation information with the target node object are screened out from a pre-constructed product service resource knowledge graph; detecting whether the screened node object meets a preset fault condition; and marking and displaying the node objects meeting the preset fault conditions.
In some embodiments, the processing unit 910 may also perform the following steps of the method embodiments described above: obtaining a node type of a target node object, wherein the node type comprises: source node and/or target node.
In some embodiments, the relationship information includes: object relationships and object region relationships; in some embodiments, the processing unit 910 may also perform the following steps of the method embodiments described above: according to the target node object to be diagnosed and the object relation, product service resource node objects conforming to the object relation with the target node object are screened out from a pre-constructed product service resource knowledge graph; and screening out the regional node objects which accord with the target node objects in the object regional relationship from the pre-constructed product service resource knowledge graph according to the target node objects to be diagnosed and the object regional relationship.
In some embodiments, the target node object is a node object that provides a product service or resource for an operator, and the object relationship includes at least: containment, carrying, dependency, partitioning, splicing, perforation; the object region relationship includes at least: in design, to be audited, in audit, online, offline, and disabled.
In some embodiments, the processing unit 910 may also perform the following steps of the method embodiments described above: acquiring a product service resource object file, wherein the product service resource object file contains attribute information of one or more product service resource objects; obtaining a product service resource object relation file, wherein the product service resource object relation file contains the relation among the product service resource objects; acquiring an area file, wherein the area file contains attribute information of one or more areas; obtaining an object region relation file, wherein the object region relation file contains the relation between each object and a region; and constructing a product service resource knowledge graph according to the product service resource object file, the product service resource object relation file, the region file and the object region relation file.
In some embodiments, the processing unit 910 may also perform the following steps of the method embodiments described above: and importing the product service resource object file, the product service resource object relation file, the region file and the object region relation file into a map database to generate a product service resource knowledge map.
In some embodiments, the graph database is a Neo4J database.
In some embodiments, the processing unit 910 may also perform the following steps of the method embodiments described above: displaying the network topology information of the product service resource knowledge graph at the front end by using Vue and D3. Js; the Spring Boot framework is used so that the backend responds to requests from the front end.
The storage unit 920 may include readable media in the form of volatile storage units, such as Random Access Memory (RAM) 9201 and/or cache memory 9202, and may further include Read Only Memory (ROM) 9203.
The storage unit 920 may also include a program/utility 9204 having a set (at least one) of program modules 9205, such program modules 9205 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
The bus 930 may be one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 900 may also communicate with one or more external devices 940 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 900, and/or any devices (e.g., routers, modems, etc.) that enable the electronic device 900 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 950. Also, electronic device 900 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 960. As shown, the network adapter 960 communicates with other modules of the electronic device 900 over the bus 930. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 900, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, a computer-readable storage medium, which may be a readable signal medium or a readable storage medium, is also provided. Fig. 10 illustrates a schematic diagram of a computer-readable storage medium in an embodiment of the present disclosure, and as illustrated in fig. 10, a program product capable of implementing the method of the present disclosure is stored on the computer-readable storage medium 100. In some possible implementations, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the disclosure as described in the "exemplary methods" section of this specification, when the program product is run on the terminal device.
More specific examples of the computer readable storage medium in the present disclosure may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In this disclosure, a computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Alternatively, the program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
In particular implementations, the program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order or that all illustrated steps be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.
From the description of the above embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (11)
1. A node fault diagnosis method, comprising:
acquiring target node objects to be diagnosed and relation information;
according to the target node object to be diagnosed and the relation information, node objects conforming to the relation information with the target node object are screened out from a pre-constructed product service resource knowledge graph;
detecting whether the screened node object meets a preset fault condition;
marking and displaying the node objects meeting the preset fault conditions;
wherein the relationship information includes: the object relationship is used for representing the relationship between the product service resource node object and the product service resource node object, and the object region relationship is used for representing the relationship between the product service resource node object and the region node object; the product service resource knowledge graph comprises the following components: a plurality of product service resource node objects and region node objects;
detecting whether the screened node object meets a preset fault condition comprises the following steps: and detecting whether the data of the screened node objects meets the preset fault condition one by one.
2. The node fault diagnosis method according to claim 1, wherein before screening out a node object conforming to relationship information with a target node object from a pre-constructed product service resource knowledge graph according to the target node object and relationship information, the method further comprises:
Obtaining a node type of the target node object, wherein the node type comprises: source node and/or target node.
3. The node fault diagnosis method according to claim 1, wherein, according to a target node object to be diagnosed and relationship information, a node object conforming to the relationship information with the target node object is screened from a pre-constructed product service resource knowledge graph, comprising:
according to the target node object to be diagnosed and the object relation, product service resource node objects conforming to the object relation with the target node object are screened out from a pre-constructed product service resource knowledge graph;
and screening out the regional node objects which accord with the target node object with the object regional relationship from a pre-constructed product service resource knowledge graph according to the target node object to be diagnosed and the object regional relationship.
4. A node failure diagnosis method according to claim 3, wherein the target node object is a node object providing a product service or resource for an operator, and the object relationship at least includes: containment, carrying, dependency, partitioning, splicing, perforation; the object region relationship includes at least: in design, to be audited, in audit, online, offline, and disabled.
5. The node fault diagnosis method according to claim 1, wherein before screening out a node object conforming to relationship information with a target node object from a pre-constructed product service resource knowledge graph according to the target node object and relationship information, the method further comprises:
acquiring a product service resource object file, wherein the product service resource object file contains attribute information of one or more product service resource objects;
obtaining a product service resource object relation file, wherein the product service resource object relation file contains the relation among all product service resource objects;
acquiring an area file, wherein the area file contains attribute information of one or more areas;
obtaining an object region relation file, wherein the object region relation file contains the relation between each object and a region;
and constructing a product service resource knowledge graph according to the product service resource object file, the product service resource object relation file, the region file and the object region relation file.
6. The node fault diagnosis method according to claim 5, wherein constructing a product service resource knowledge graph from the product service resource object file, the product service resource object relationship file, the region file, and the object region relationship file comprises:
And importing the product service resource object file, the product service resource object relation file, the region file and the object region relation file into a map database to generate a product service resource knowledge graph.
7. The node fault diagnosis method according to claim 6, wherein the graph database is Neo4J database.
8. The node fault diagnosis method according to claim 7, characterized in that the method further comprises:
displaying the network topology information of the product service resource knowledge graph at the front end by using Vue and D3. Js;
the Spring Boot framework is used so that the backend responds to requests from the front end.
9. A node failure diagnosis apparatus, comprising:
the data acquisition module is used for acquiring the target node object to be diagnosed and the relation information;
the data screening module is used for screening out node objects which accord with the relation information from a pre-constructed product service resource knowledge graph according to the target node objects to be diagnosed and the relation information;
the fault diagnosis module is used for detecting whether the screened node object meets a preset fault condition;
the fault display module is used for displaying the node objects meeting the preset fault conditions in a marked mode;
Wherein the relationship information includes: the object relationship is used for representing the relationship between the product service resource node object and the product service resource node object, and the object region relationship is used for representing the relationship between the product service resource node object and the region node object; the product service resource knowledge graph comprises the following components: a plurality of product service resource node objects and region node objects;
detecting whether the screened node object meets a preset fault condition comprises the following steps: and detecting whether the data of the screened node objects meets the preset fault condition one by one.
10. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the node fault diagnosis method of any one of claims 1 to 8 via execution of the executable instructions.
11. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, implements the node fault diagnosis method of any of claims 1 to 8.
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Application publication date: 20220830 Assignee: Tianyiyun Technology Co.,Ltd. Assignor: CHINA TELECOM Corp.,Ltd. Contract record no.: X2024110000020 Denomination of invention: Node fault diagnosis methods, devices, electronic devices, and storage media Granted publication date: 20231003 License type: Common License Record date: 20240315 |