CN114745286A - Intelligent network situation perception system facing dynamic network based on knowledge graph technology - Google Patents
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Abstract
The invention discloses an intelligent network situation perception system facing a dynamic network based on a knowledge graph technology, which comprises situation perception nodes, a network situation perception fusion center and a network situation perception application. The invention provides a knowledge graph technology-based intelligent network situation perception system for a 5G dynamic network, which solves the problem of intelligentized agile dynamic network situation perception in the 5G communication era, controls the whole network situation perception of carrying network distribution, various types of subnet interweaving relations, network flow trend, network load, network paths, network element entity information and the like of a transmission network, and meets the requirement of multi-view visual dynamic perception of construction optimization, operation maintenance, network safety and network supervision urgent need.
Description
Technical Field
The invention belongs to the technical field of network situation perception, and particularly relates to a knowledge graph technology-based dynamic network-oriented intelligent network situation perception system.
Background
At present, a network situation awareness technology hotspot collects, monitors, perceives and manages the state of accompanying network equipment, and belongs to the field of network management system equipment. For example, an intelligent network management method based on network situation awareness is disclosed in a chinese patent application with application number "201811409929.4", which is applicable to state awareness and management and maintenance of network devices in a specific computer room.
In the current 5G communication era, any to any ubiquitous connection, SNP network slice access network, transport pipeline clouding, and ubiquitous intelligent full mesh are under technical popularization and application of software defined networking SDN. The communication network is entering the intelligent agile dynamic network era, and the access of IP internet, private network, signaling network and various enterprise group private networks is convenient at any time and any place. The blueprint planning bearing network is switched into a bearing network which changes as required, so that the difficulty of network state cognition is brought to the construction optimization, operation maintenance and network security monitoring management of the network.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a knowledge graph technology-based dynamic network-oriented intelligent network situation awareness system.
The purpose of the invention is realized by the following technical scheme: a situation awareness system for a dynamic network-oriented intelligent network based on a knowledge graph technology comprises situation awareness nodes, a network situation awareness fusion center and a network situation awareness application;
the situation awareness nodes extract and complete knowledge conversion processing based on network sensing node data, and network situation awareness is completed when the network situation sensing nodes are arranged to build a local network situation knowledge map library;
the network situation perception fusion center carries out fusion disambiguation processing and inference analysis completion on a knowledge map library based on a local network situation knowledge map model generated by networking each network sensing node to construct a network situation knowledge map model; researching, analyzing and finishing the formulation of a standardized network situation knowledge map ontology model; meanwhile, the method has the functions of network situation knowledge map data sharing, network situation change early warning analysis and network reasoning analysis service, and carries out situation awareness node networking management;
the network situation awareness application is used for providing a visual configuration ontology knowledge creation, a network map relation and network situation information display, and a network entity network element node information analysis and early warning application service system.
Further: the network situation knowledge map model is constructed based on an ontology model, and the network situation knowledge map model object entity network element knowledge comprises link, network and session protocol parameters belonging to static state, flow, fault frequency, associated network elements and associated region dynamic attributes; the network situation knowledge map model object entity network element interweaving relation knowledge comprises a line, a port, interactive cooperation flow and bearing service attributes.
Further, the method comprises the following steps: the data extraction and knowledge conversion specifically comprises the following steps: by knowledge extraction, network element entities, relationship and attribute knowledge elements can be extracted from original data, and a structured and networked knowledge system is finally obtained by knowledge processing, wherein the knowledge processing comprises the following steps: knowledge representation, knowledge reasoning, knowledge updating and quality assessment.
Further: the knowledge representation can be manually constructed in a manual editing mode, and also can be constructed in a data-driven automatic mode, wherein the automatic mode comprises 3 stages: the method comprises the steps of entity parallel relation similarity calculation, entity superior-subordinate relation extraction and ontology generation.
Further: the knowledge reasoning refers to performing computer reasoning from existing entity network element relation data in a knowledge base to establish new association between entity network elements, thereby expanding and enriching knowledge network elements.
Further: the knowledge inference method utilizes 3 broad categories: ontology reasoning, rule-based reasoning, and graph-based reasoning.
Further: the knowledge updating comprises updating of a concept layer and updating of a data layer, wherein the updating of the concept layer means that a new concept is obtained after Schema data is newly added, and the new concept needs to be automatically added into the concept layer of the knowledge base; the updating of the data layer mainly comprises newly adding or updating entities, relations and attribute values; updating the data layer needs to consider the reliability of the data sources and the consistency of the data, and select the fact and the attribute with high occurrence frequency in each data source to be added into the knowledge base.
Further: the quality assessment can quantify the confidence level of knowledge, and the quality of the knowledge base is guaranteed by discarding the knowledge with lower confidence level.
Further: the fusion disambiguation processing of the knowledge map library aims at data in different levels of network fields in an ISO seven-layer network structure, combines a body model, researches a data fusion algorithm of a plurality of situation perception nodes, realizes the fusion and completion of multi-node network situation map data, and is divided into the fusion of a mode layer and the fusion of a data layer;
the mode layer fusion is oriented to schema and comprises concepts, the upper and lower parts of the concepts and the unification of attributes; the fusion of the data layer is to fuse the same entities of different data sources in different expression forms, and comprises the combination of the entities, the combination of the entity attributes and the relationship, and a TransE model related to the entity similarity.
Further: the peer-to-peer system architecture adopted by the networking is composed of one or more network sensing nodes.
The aforementioned main aspects of the invention and their respective further alternatives may be freely combined to form a plurality of aspects, all of which are aspects that may be adopted and claimed by the present invention. The skilled person in the art can understand that there are many combinations, which are all the technical solutions to be protected by the present invention, according to the prior art and the common general knowledge after understanding the scheme of the present invention, and the technical solutions are not exhaustive herein.
The invention has the beneficial effects that: the invention provides a knowledge graph technology-based intelligent network situation perception system for a 5G dynamic network, which solves the problem of intelligentized agile dynamic network situation perception in the 5G communication era, controls the whole network situation perception of carrying network distribution, various types of subnet interweaving relations, network flow trend, network load, network paths, network element entity information and the like of a transmission network, and meets the requirement of multi-view visual dynamic perception of construction optimization, operation maintenance, network safety and network supervision urgent need.
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FIG. 1 is a schematic diagram of the system components of the present invention;
FIG. 2 is a schematic diagram of the system of the present invention;
FIG. 3 is a schematic diagram showing the composition of an ontology model in an embodiment;
FIG. 4 is a diagram of an embodiment of a network situation awareness ontology model;
FIG. 5 is a diagram illustrating data knowledge extraction according to an embodiment;
FIG. 6 is a basic flow chart of the knowledge fusion technique in the embodiment;
fig. 7 is a schematic diagram of a networking model in the embodiment.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that, in order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations and positional relationships that are conventionally used in the products of the present invention, and are used merely for convenience in describing the present invention and for simplicity in description, but do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and therefore, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another, and are not to be construed as indicating or implying relative importance.
Furthermore, the terms "horizontal", "vertical", "overhang" and the like do not imply that the components are required to be absolutely horizontal or overhang, but may be slightly inclined. For example, "horizontal" merely means that the direction is more horizontal than "vertical" and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the present invention, it should also be noted that, unless otherwise explicitly specified or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, it should be noted that, in the present invention, if the specific structures, connection relationships, position relationships, power source relationships, and the like are not written in particular, the structures, connection relationships, position relationships, power source relationships, and the like related to the present invention can be known by those skilled in the art without creative work on the basis of the prior art.
Example 1:
referring to fig. 1, the invention discloses a situation awareness system for a dynamic network-oriented intelligent network based on a knowledge graph technology. The system mainly comprises 3 layers, namely a situation awareness node, a network situation awareness fusion center and a network situation awareness application. And establishing a communication cable and a communication node knowledge graph by means of data networking integration data, and simultaneously performing situation analysis and reasoning on enriched graph data to finally obtain a network graph relation network and a situation information visualization result. Data networking analysis, intelligently constructing knowledge graphs of information data resources transmitted, loaded, stored and exchanged on the IP internet, a private network, a signaling network and various deep network communication networks, realizing dynamic network situation perception analysis, changing, identifying and monitoring capabilities, reasoning and enriching graph data, and finally obtaining a network graph relation network and situation information visualization result.
The functions of the components are as follows:
1. and (4) extracting and completing knowledge conversion processing based on the network sensing node data, and completing local network situation perception of the network situation sensing node to construct a local network situation knowledge map library.
2. The network situation perception fusion center carries out fusion disambiguation processing of a knowledge map library and inference analysis completion on the knowledge map library based on a local network situation knowledge map library generated by each networking sensing node to construct a full network situation knowledge map library; researching, analyzing and finishing the formulation of a standardized network situation knowledge map ontology model; meanwhile, the system has the services of network situation knowledge map data sharing, network situation change early warning analysis, network reasoning analysis and the like.
3. And the network situation perception application is an application service system for providing visual configuration ontology knowledge creation, network map relation and network situation information display, network entity network element node information analysis, early warning and the like.
The working principle is shown in fig. 2. The network situation awareness system needs a corresponding data platform as a support to ensure systematization and process of data acquisition, processing and application. Unifying data formats and data standards, further mining and complementing the data to be put in storage by using machine learning algorithms such as clustering, association, regression and the like, and providing a data base for the atlas analysis service.
And the fusion service is used for constructing an ontology and a mapping file of the data by combining the source data according to a pre-constructed ontology model and storing the data into a graph database. Meanwhile, knowledge reasoning analysis service is provided, and implicit information can be obtained based on technologies such as logic reasoning and rule reasoning.
And applying information visualization service to realize human-computer interface interaction and related data display functions, displaying each query data in a reading and reporting mode, and presenting analysis results (such as topology, association, path graph and the like) in a visualization view mode. The layer comprises interfaces such as situation change early warning, node information, ontology management, network map relation, network situation information and the like.
The network situation knowledge map model is shown in fig. 3 and 4. The network situation knowledge map model management is constructed based on an ontology model, and ontology construction by adopting creation software can be considered. The Prot g is cross-platform knowledge graph and ontology editing software based on JRE.
The network situation knowledge graph model object entity network element knowledge comprises attributes such as protocol parameters of links, networks, sessions and the like, such as static properties, flow, fault frequency, associated network elements, associated region dynamic properties and the like.
The network situation knowledge graph model object entity network element interweaving relation knowledge comprises attributes of lines, ports, interactive cooperation flow, bearing services and the like.
Data extraction and knowledge translation are shown in fig. 5. Through knowledge extraction, knowledge elements such as network element entities, relations and attributes can be extracted from original data, and a knowledge processing process is needed to finally obtain a structured and networked knowledge system. The knowledge processing mainly comprises 4 aspects: knowledge representation (ontology construction), knowledge reasoning, knowledge updating and quality evaluation.
Knowledge representation can be manually constructed (by means of ontology editing software such as a project) in a manual editing mode, and can also be constructed in a data-driven automatic mode, wherein the ontology comprises 3 stages: the method comprises the steps of entity parallel relation similarity calculation, entity superior-subordinate relation extraction and ontology generation.
The knowledge reasoning means that computer reasoning is carried out from the existing entity network element relation data in a knowledge base, and new association between entity network elements is established, so that the knowledge network elements are expanded and enriched. The inference method of knowledge utilizes 3 broad categories: ontology reasoning, rule-based reasoning, and graph-based reasoning.
And in knowledge updating and logic view, the updating of the knowledge base comprises the updating of a concept layer and the updating of a data layer, the updating of the concept layer means that a new concept is obtained after Schema data is newly added, and the new concept needs to be automatically added into the concept layer of the knowledge base. The updating of the data layer mainly comprises adding or updating entities, relations and attribute values. Updating the data layer needs to consider reliable data sources such as reliability of the data sources and data consistency (whether contradiction or redundancy exists and other problems), and select facts and attributes with high occurrence frequency in each data source to be added into the knowledge base. The updating mode includes full quantity updating and increment updating.
The quality evaluation can quantify the credibility of the knowledge, and the quality of the knowledge base is guaranteed by abandoning the knowledge with lower confidence.
The knowledge-graph fusion process is shown in FIG. 6. Network element target and event disambiguation and fusion functions, which support the automatic disambiguation and fusion functions according to rules or extension programs; the knowledge online streaming application function is used for carrying out streaming identification on targets and events according to knowledge by using rules or expansion operators and carrying out report early warning;
aiming at data in different layers of network fields in an ISO seven-layer network structure, a data fusion algorithm of a plurality of situation perception nodes is researched by combining an ontology model, and multi-node network situation map data fusion and completion are achieved. It is mainly divided into mode layer fusion and data layer fusion. The mode layer fusion is oriented to schema and mainly comprises concepts, the upper and lower parts of the concepts and the unification of attributes; the fusion of the data layer is mainly to fuse the same entities of different data sources in different expression forms, including the combination of the entities, the combination of the attributes and the relationships of the entities, a TransE model related to the similarity of the entities and the like. The main technical difficulty lies in the challenge of data quality, such as problems of difficult alignment or matching error of entities and ontologies caused by data input error, loss, inconsistent format, abbreviation and naming ambiguity; along with the expansion of data scale, the problems of parallel computing, data variety diversity and the like need to be increased.
Networking management technology
The service networking is that each network node network sensing node performs quasi-real-time dynamic network element data extraction and converts the quasi-real-time dynamic network element data into network situation knowledge data, and then an intelligent network situation center completes the basis of fusion of the network situation knowledge data of each node, how to add a plurality of network sensing nodes with dispersed regions into the network situation sensing networking, and the stable reliability of service operation and message receiving and sending is ensured under the condition of smooth network; while feedback or protection mechanisms in case of network congestion need to be considered.
The wide area interconnection characteristics are provided among the network sensing nodes, the wide area network is unstable relative to the local area network due to the complexity of the wide area network, the problems that the center-to-center network is unstable and the online states of the service of the array nodes are variable are faced, and the dynamic change of a system network map becomes a normal state due to the requirement of dynamic expansion of the system.
Aiming at the requirements and the practical environment of network networking of network sensing nodes, a peer-to-peer networking model is designed, the model can timely discover a system fault service node and dynamically expanded service nodes, intelligently reconstructs a network map structure, and has good adaptability to the situations of network faults, service offline, node expansion and the like. The automatic joining and exiting capacity of the network sensing node service, the automatic election capacity of the network sensing main node, the network state maintenance among all nodes, the damage resistance of the fault self-recombination and the high-efficiency cross-domain retrieval are the key points of the whole system design.
The network sensing node networking system is characterized in that a peer-to-peer system architecture is adopted by a network sensing node networking system design model, and the network sensing node networking is composed of one network sensing node or a plurality of network sensing nodes. Peering means that the network sensing nodes are completely equal in position, have no control center or no resource center, and are connected with each other through the network to form a whole.
The system networking model is shown in fig. 7, and in addition, the networking further includes registration management, fault recovery, state management and cross-node data service, which will not be described.
The invention discloses a realization method of a situation awareness system of a 5G dynamic network oriented intelligent network based on knowledge graph technology, which is oriented to easily-perceived, sharable and knowledge-level services, and comprises network entity network element knowledge, network element interweaving relation, network element interweaving parameters, network element flow fault change state, network structure change identification and the like, and mainly comprises the following technical key points:
1. the networking network sensing node supports dynamic expansion;
2. the network perception knowledge form can be customized, and the network perception including an IP internet, a private network, a signaling network and various deep network communication networks is supported;
3. atlas knowledge conforming to the same network situation knowledge atlas ontology model standard can be shared.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A situation awareness system for a dynamic network-oriented intelligent network based on a knowledge graph technology is characterized by comprising situation awareness nodes, a network situation awareness fusion center and a network situation awareness application;
the situation awareness nodes extract and complete knowledge conversion processing based on network sensing node data, and network situation awareness is distributed on the network situation sensing nodes to construct a local network situation knowledge map library;
the network situation perception fusion center carries out fusion disambiguation processing and inference analysis completion on a knowledge map library based on a local network situation knowledge map model generated by networking each network sensing node to construct a network situation knowledge map model; researching, analyzing and finishing the formulation of a standardized network situation knowledge map ontology model; meanwhile, the method has the functions of network situation knowledge map data sharing, network situation change early warning analysis and network reasoning analysis service, and carries out situation awareness node networking management;
the network situation awareness application is used for providing a visual configuration ontology knowledge creation, a network map relation and network situation information display, and a network entity network element node information analysis and early warning application service system.
2. The system of claim 1, wherein the network situation knowledge graph model is constructed based on an ontology model, and the knowledge of network situation knowledge graph model object entity network elements includes link, network, session protocol parameters pertaining to static behavior, traffic, failure frequency, associated network elements, and associated regional dynamic attributes; the network situation knowledge map model object entity network element interweaving relation knowledge comprises a line, a port, interactive cooperation flow and bearing service attributes.
3. The system for perceiving situation of intelligent network facing dynamic network based on knowledge-graph technology as claimed in claim 1, wherein said data extraction and knowledge transformation is specifically: by knowledge extraction, network element entities, relationship and attribute knowledge elements can be extracted from original data, and a structured and networked knowledge system is finally obtained by knowledge processing, wherein the knowledge processing comprises the following steps: knowledge representation, knowledge reasoning, knowledge updating and quality assessment.
4. The system of claim 3, wherein the knowledge representation can be manually constructed by manual editing or an ontology can be constructed in a data-driven automated manner, and the automated manner comprises 3 stages: the method comprises the steps of entity parallel relation similarity calculation, entity superior-subordinate relation extraction and ontology generation.
5. The system of claim 3, wherein the knowledge-based inference refers to performing computer inference from existing entity-network element relationship data in the knowledge base to establish new associations between entity network elements, thereby expanding and enriching knowledge network elements.
6. The system of claim 3, wherein the knowledge-graph-based technology is based on the knowledge-graph technology and oriented to the dynamic network intelligent network situation awareness system, and the knowledge inference method utilizes 3 categories: ontology reasoning, rule-based reasoning, and graph-based reasoning.
7. The system for perceiving situation of a dynamic network-oriented intelligent network based on knowledge-graph technology according to claim 3, wherein the knowledge updating comprises updating of a concept layer and updating of a data layer, and the updating of the concept layer means that a new concept is obtained after Schema data is newly added and needs to be automatically added into the concept layer of the knowledge base; the updating of the data layer mainly comprises newly adding or updating entities, relations and attribute values; updating the data layer needs to consider the reliability of the data sources and the consistency of the data, and select the fact and the attribute with high occurrence frequency in each data source to be added into the knowledge base.
8. The knowledge-graph-based technology dynamic network-oriented intelligent situation awareness system according to claim 3, wherein the quality assessment quantifies the confidence level of knowledge, and the quality of the knowledge base is guaranteed by discarding knowledge with lower confidence level.
9. The system for perceiving situation of intelligent network facing dynamic network based on knowledge-graph technology according to claim 1, wherein the knowledge-graph library fusion disambiguation process is used for researching a data fusion algorithm of a plurality of situation perception nodes by combining ontology models aiming at data of different levels of network fields in an ISO seven-layer network structure, so that multi-node network situation graph data fusion and completion are realized, and the fusion is divided into mode layer fusion and data layer fusion;
the mode layer fusion is oriented to schema and comprises concepts, the upper and lower parts of the concepts and the unification of attributes; the fusion of the data layer is to fuse the same entities of different data sources in different expression forms, and comprises the combination of the entities, the combination of the entity attributes and the relationship, and a TransE model related to the entity similarity.
10. The knowledge-graph-based technology dynamic network-oriented intelligent situation awareness system according to claim 1, wherein the peer-to-peer system architecture adopted by the networking is composed of one or more network sensing nodes.
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