Communication method and related equipment

Abstract

The invention discloses a communication method and related equipment, and is applied to a communication system, the communication system comprises a service architecture SBA network element and an SBA semantic agent, the SBA semantic agent comprises a semantic graph and a graph query language, the semantic graph synchronizes service logic and service data from the SBA network element, and the method comprises the following steps: the SBA semantic agent obtains a graph query request; the SBA semantic agent calls a graph query language according to the graph query request; the SBA semantic agent accesses the semantic graph through a graph query language. In the application, since the semantic graph in the SBA semantic agent synchronizes the service logic and the service data of the SBA network element, the service of the SBA network element is realized by accessing the semantic graph in the SBA semantic agent, a request for calling a service interface does not need to be initiated to the SBA network element, so that the service interface does not need to be written for the SBA network element, and the efficiency of accessing the service of the SBA network element is improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a communication method and related equipment. Background Art

[0002] Service-based Architecture (SBA) is an important feature of the fifth generation mobile communication technology (5th Generation Mobile Communication Technology, 5G). Combining the network characteristics and technological development trends of the mobile core network, the service-based architecture can divide network services into several reusable network elements (i.e., SBA network elements), and each SBA network element corresponds to a service. Lightweight interfaces are used for communication between SBA network elements. Its goal is to achieve high efficiency, software-based, and open 5G systems. In the design process of SBA, the network architecture and processes are roughly divided first, and then the interface messages and data models of the SBA network elements are written according to the functions of different SBA network elements.

[0003] The 23.501 and 23.502 specifications of the 3rd Generation Partnership Project (3gpp) protocol provide a typical SBA design, define different processes in different scenarios, and divide the overall SBA architecture into different SBA network elements. The 29.XXX series of specifications of the 3gpp protocol define specific interface messages and data models for each SBA network element. Then, by calling the service of the SBA network element, a complete process can be formed.

[0004] See also Figure 1 , Figure 1 A possible SBA diagram is shown in Figure 2. Figure 1 As shown in the figure, the actual service-oriented architecture often includes a large number of SBA network elements to provide different services. A request from a user equipment (UE) may require the use of services from multiple SBA network elements, so the data generated by the request will be processed and transmitted by multiple SBA network elements. Developers and operation and maintenance personnel need to manually write the service interfaces between each SBA network element, for example, they need to specifically define the Path in the open application programming interface (OpenAPI) Schema. In addition, if the service interface of a certain SBA network element is subsequently updated, added, or deleted, it will also affect the service interfaces of more other related SBA network elements, for example, the Path in the OpenAPI Schema of multiple SBA network elements needs to be modified, resulting in low efficiency in providing services by the SBA network elements. Summary of the invention

[0005] The present application provides a communication method and related equipment for improving the efficiency of accessing services of SBA network elements.

[0006] In a first aspect, the present application provides a communication method, which is applied to a communication system, wherein the communication system includes an SBA network element (ie, a distributed SBA network element) and an SBA semantic agent.

[0007] The SBA network element defined in the embodiments of the present application refers to a network element used to provide network services in a service-oriented architecture. Exemplarily, the SBA network element includes but is not limited to a mobility management network element (Access and Mobility Management Function, AMF), a session management network element (Session Management Function, SMF), a user plane forwarding network element (User Plane Function, UPF) or an authentication server function (Authentication Server Function, AUSF), which is not specifically limited here.

[0008] The SBA semantic agent stores a semantic graph and a graph query language, and the semantic graph can be accessed by calling the graph query language. In the embodiment of the present application, the semantic graph in the SBA semantic agent synchronizes the business logic and business data of the SBA network element. Among them, it can be considered that the business data of the SBA is associated with the business logic of the SBA network element, or these business data are needed when executing the business logic. In other words, the service of the SBA network element is synchronized to the SBA semantic agent, and in the SBA semantic agent, the synchronized business logic and business data from the SBA network element are defined with the semantic graph as the data model, so as to define the service of the SBA network element by performing a graph query on the semantic graph. Therefore, by accessing the business logic and business data in the semantic graph, the service of the SBA network element can be realized. Specifically, the SBA semantic agent obtains a graph query request. Among them, the graph query request can be sent by the UE, or it can also be sent by other SBA semantic agents, or it can also be sent by other entities requesting access to the SBA service, and the embodiment of the present application does not limit this.

[0009] Specifically, the SBA semantic agent obtains a graph query request, parses the graph query request, and determines the graph query language called by the graph query request. The SBA semantic agent executes the graph query language called by the graph query request, thereby accessing the semantic graph and implementing the service of the SBA network element.

[0010] In the embodiment of the present application, since the semantic graph in the SBA semantic agent synchronizes the business logic and business data of the SBA network element, the service of the SBA network element can be implemented by accessing the semantic graph in the SBA semantic agent. There is no need to initiate a request to call the service interface to the SBA network element. Therefore, there is no need to write a service interface for the SBA network element (such as the Path in the OpenAPI Schema), which improves the efficiency of accessing the services of the SBA network element.

[0011] Based on the first aspect, in an optional implementation, after the SBA semantic agent executes the graph query request, the data model of the semantic graph in the SBA semantic agent undergoes data updates. Since there is a synchronization relationship and a binding relationship between the data of the semantic graph and the SBA network element, the data updates that occur in the data model of the semantic graph also need to be synchronized to the SBA network element. Therefore, the SBA semantic agent generates a processing result corresponding to the graph query request and sends the processing result to the SBA network element, wherein the processing result includes update information of the business data in the semantic graph. After receiving the processing result, the SBA network element updates the business data in the SBA network element according to the update information in the processing result, thereby completing the synchronization of the business data between the semantic graph and the SBA network element. The update of the business data in the SBA network element, reflected at the semantic graph level, is an update of the nodes, the attributes of the nodes, and the relationships between the nodes in the semantic graph.

[0012] Based on the first aspect, in an optional implementation, if the business logic of the SBA network element can be expressed by executing a graph query of the semantic graph through the SBA semantic agent, then the business logic of the SBA network element can be assigned to the SBA semantic agent for processing and execution, and the SBA network element service only needs to be responsible for the platform layer (P layer) function. Specifically, after the SBA semantic agent parses the graph query request, it determines that a certain business logic of the SBA network element cannot be fully expressed through the SBA semantic agent executing a graph query of the semantic graph, then the processing result sent by the SBA semantic agent to the SBA network element may also include a target instruction. The target instruction is used to notify the SBA network element that the SBA network element will execute the service corresponding to this graph query request. Therefore, after the SBA network element receives the processing result, it executes the service of the SBA network element according to the target instruction in the processing result. Specifically, in actual applications, the target instruction can be an instruction for accessing the service interface of the SBA network element, so as to maintain compatibility with the SBA service-oriented architecture. In the embodiment of the present application, in addition to implementing the services of the SBA network element through the SBA semantic agent, the services corresponding to the graph query request can also be handed over to the SBA network element for execution, thereby improving the flexibility of the SBA network element in providing services.

[0013] Based on the first aspect, in an optional implementation, the communication system includes N SBA network elements and N SBA semantic subagents, where N is an integer greater than or equal to 2. Each SBA network element in the communication system is configured with a corresponding SBA semantic agent, and the service of each SBA network element will be executed by the SBA semantic agent corresponding to the SBA network element, and the SBA semantic agent corresponding to an SBA network element is the SBA semantic subagent in the embodiment of the present application. Specifically, the communication system includes N SBA network elements and N SBA semantic subagents, and the N SBA semantic subagents include a first SBA subagent, and the aforementioned SBA semantic agent is the first SBA semantic subagent, and each SBA semantic subagent is connected to an SBA network element in communication. Then the semantic graph in the SBA semantic subagent is a semantic subgraph, and the semantic subgraph synchronizes the business logic and business data from an SBA network element. In actual applications, each SBA semantic subagent can be deployed on an independent device (such as a server) to implement, or multiple SBA semantic subagents can be integrated and deployed on one device to implement, which is not limited here. In an embodiment of the present application, the business logic and business data of each SBA network element are synchronized with the semantic subgraph in an SBA semantic subagent, and each SBA semantic subagent is only responsible for executing the services of one SBA network element, thereby reducing the load and resource overhead of the SBA semantic subagent.

[0014] Based on the first aspect, in an optional implementation, the SBA semantic subagents are independent of each other, and the semantic subgraphs are also independent of each other. The SBA semantic subagent's graph query for a semantic subgraph can express the service of an SBA network element. Therefore, a complete network processing flow often needs to be decomposed into graph queries of several semantic subgraphs to complete. Specifically, in a complete network processing flow, after a certain SBA semantic subagent performs a graph query on a semantic subgraph based on the acquired graph query request, the SBA semantic subagent determines the next service node in the network processing flow (i.e., the second SBA semantic subagent in the embodiment of the present application) according to the graph query request and the semantic subgraph in the SBA semantic subagent, wherein the second SBA semantic subagent is an SBA semantic subagent among the N SBA semantic subagents except the first SBA semantic subagent. The SBA semantic agent generates a graph query request for the next hop based on the graph query request and the semantic subgraph in the SBA semantic subagent, and sends the graph query request for the next hop to the second SBA semantic subagent. After the second SBA semantic subagent receives the graph query request of the next hop, it accesses the semantic subgraph in the second SBA semantic subagent according to the graph query request of the next hop. The process of the second SBA semantic subagent accessing its semantic subgraph is similar to the process of the aforementioned SBA semantic agent accessing its semantic graph, and will not be repeated here.

[0015] Based on the first aspect, in an optional implementation, the communication system includes N SBA network elements and N SBA semantic subagents, where N is an integer greater than or equal to 2. The SBA semantic agent includes one SBA global semantic agent, which is in communication connection with the N SBA network elements, that is, one SBA global semantic agent manages the N SBA network elements in the communication system. Among them, the semantic graph in the SBA global semantic agent is a global semantic graph, which synchronizes the business logic and business data from the N SBA network elements. In other words, the global semantic graph and the graph query language for the global semantic graph written in the present application are stored in the SBA global semantic agent. The graph query for the global semantic graph describes the global processing flow of the network, such as a series of SBA network element services used by the UE access process or service request process. It can be seen that the services of the N SBA network elements in the communication system are migrated to one SBA global semantic agent for unified execution, which improves the efficiency of the SBA global semantic agent in processing graph query requests.

[0016] Based on the first aspect, in an optional implementation, a SaaS semantic agent is deployed for a software operation service SaaS network element in a communication system, and the SaaS semantic agent and the SBA semantic agent are connected in communication. The SaaS semantic agent stores a semantic graph and a graph query language, and the semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element. After the SaaS semantic agent obtains a graph query request, it calls the graph query language stored in the SaaS semantic agent according to the graph query request to access the semantic graph stored in the SaaS semantic agent through the graph query language. In the present application, the graph query request obtained by the SBA semantic agent can be sent by the SaaS semantic agent to the SBA semantic agent; and the graph query request obtained by the SaaS semantic agent can be sent by the SBA semantic agent to the SaaS semantic agent. Specifically, the process of the SaaS semantic agent executing the service of the SaaS network element is similar to the process of the SBA semantic agent executing the service of the SBA network element. For details, please refer to the aforementioned description of the SBA semantic agent executing the service of the SBA network element, which will not be repeated here. The SaaS semantic agent and the SBA semantic agent can communicate and interact with each other, so that the services of the SBA network elements and the SaaS network elements are expressed by relying on the semantic agent to execute the graph query of the semantic graph. There is no need to write service interfaces (Path in OpenAPI Schema) for the interaction between the SBA semantic agent and the SaaS network element, and the interaction between the SaaS semantic agent and the SBA network element, thereby improving the working efficiency of the SBA semantic agent and the SaaS semantic agent.

[0017] Based on the first aspect, in an optional implementation, the graph query language stored in the SBA semantic agent includes Create Read Update Delete (CRUD) functions for the semantic graph, and CRUD operations can be performed on the semantic graph by calling the CRUD functions. Therefore, the graph query language of the semantic graph can express operations such as CRUD on the semantic graph, triggering the update of the data model defined by the semantic graph.

[0018] Based on the first aspect, in an optional implementation, the business logic and business data from the SBA network element can be directly stored in the semantic graph, that is, the same business logic and business data will be stored in the semantic graph or the SBA network element at the same time, or the semantic graph can realize the binding relationship by storing the business logic of the SBA network element and the index of the business data of the SBA network element.

[0019] In a second aspect, the present application provides a service-oriented architecture SBA semantic agent, which is applied to a communication system. The communication system includes a service-oriented architecture SBA network element and an SBA semantic agent. The SBA semantic agent includes a semantic graph and a graph query language. The semantic graph synchronizes business logic and business data from the SBA network element. The SBA semantic agent includes:

[0020] A transceiver unit, used to obtain a graph query request;

[0021] A processing unit, configured to call a graph query language according to a graph query request;

[0022] The processing unit is also used to access the semantic graph through the graph query language.

[0023] Based on the second aspect, in an optional implementation, the processing unit is further used to generate a processing result corresponding to the graph query request;

[0024] The processing unit is also used to send the processing result to the SBA network element, wherein the processing result includes the update information of the business data in the semantic graph, so that the SBA network element updates the business data in the SBA network element according to the update information in the processing result.

[0025] Based on the second aspect, in an optional implementation, the processing result also includes a target instruction, and the target instruction is used to instruct the SBA to execute the service of the SBA network element according to the target instruction in the processing result.

[0026] Based on the second aspect, in an optional implementation, the SBA semantic agent is an SBA semantic subagent, the communication system includes N SBA network elements and N SBA semantic subagents, N is an integer greater than or equal to 2, each SBA network element corresponds to an SBA semantic subagent, and the semantic graph in the SBA semantic subagent is a semantic subgraph, which synchronizes the business logic and business data from an SBA network element.

[0027] Based on the second aspect, in an optional implementation, the processing unit is further used to determine a second SBA semantic subagent according to the graph query request and the semantic subgraph in the SBA semantic subagent, wherein the second SBA semantic subagent is another SBA semantic subagent in the communication system;

[0028] The SBA semantic agent generates a graph query request for the next hop based on the graph query request and the semantic subgraph in the SBA semantic subagent;

[0029] The SBA semantic agent sends a next-hop graph query request to the second SBA semantic subagent, where the next-hop graph query request is used to access the semantic subgraph in the second SBA semantic subagent.

[0030] Based on the second aspect, in an optional implementation, the communication system includes N SBA network elements and 1 global SBA semantic agent, N is an integer greater than or equal to 2, and the SBA global semantic agent is communicatively connected to the N SBA network elements, wherein the semantic graph in the SBA global semantic agent is a global semantic graph, and the global semantic graph synchronizes business logic and business data from the N SBA network elements.

[0031] Based on the second aspect, in an optional implementation, the global semantic graph includes N semantic subgraphs, each semantic subgraph synchronizes the service logic and service data from an SBA network element.

[0032] Based on the second aspect, in an optional implementation, the communication system also includes a software operation service SaaS network element and a SaaS semantic agent corresponding to the SaaS network element, the SaaS semantic agent includes a semantic graph and a graph query language, the semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element, and the transceiver unit is specifically used to receive a graph query request from the SaaS semantic agent.

[0033] Based on the second aspect, in an optional implementation, the communication system also includes a software operation service SaaS network element and a SaaS semantic agent corresponding to the SaaS network element, the SaaS semantic agent includes a semantic graph and a graph query language, the semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element, and the transceiver unit is specifically used to send a next-hop graph query request to the SaaS semantic agent, and the next-hop graph query request is used to access the semantic graph in the SaaS semantic agent.

[0034] Based on the second aspect, in an optional implementation, the graph query language includes CRUD functions for adding, searching, updating or deleting the semantic graph.

[0035] Based on the second aspect, in an optional implementation, the semantic graph includes business logic and business data from the SBA network element.

[0036] Based on the second aspect, in an optional implementation, the semantic graph includes the business logic of the SBA network element and an index of the business data of the SBA network element.

[0037] In a third aspect, the present application provides a communication device, comprising: a processor, the processor is coupled to a memory, the memory is used to store instructions, when the instructions are executed by the processor, the device implements the method in the above-mentioned first aspect, or any possible implementation of the first aspect.

[0038] In a fourth aspect, the present application provides a computer-readable storage medium having instructions stored thereon, which, when executed, cause a computer to execute the method in the above-mentioned first aspect, or any possible implementation of the first aspect.

[0039] In a fifth aspect, the present application provides a computer program product, which includes a computer program code. When the computer program code runs on a computer, it enables the computer to execute the method in the above-mentioned first aspect or any possible implementation manner of the first aspect.

[0040] In a sixth aspect, the present application provides a chip, comprising: a processor, the processor is coupled to a memory, the memory is used to store instructions, and when the instructions are executed by the processor, the chip implements the method in the above-mentioned first aspect, or any possible implementation of the first aspect.

[0041] In a seventh aspect, the present application provides a communication method, which is applied to a communication system, the communication system comprising an SBA network element and an SBA semantic agent, the SBA semantic agent being configured with a semantic graph and a graph query language, the semantic graph in the SBA semantic agent synchronizing business logic and business data from the SBA network element, the method comprising:

[0042] The SBA network element receives a target instruction from the SBA semantic agent, and the target instruction is obtained by the SBA semantic agent after accessing the semantic graph in the SBA semantic agent through the graph query language in the SBA semantic agent;

[0043] The SBA network element executes the service of the SBA network element according to the target instruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0045] Figure 1 A possible SBA diagram is shown;

[0046] Figure 2 This is a schematic diagram of the network architecture of the IaaS layer, PaaS layer, and SaaS layer;

[0047] Figure 3 This is a schematic diagram of the OpenAPI architecture;

[0048] Figure 4 This is a schematic diagram of data distribution of each network element before the network is registered;

[0049] Figure 5 It is a schematic diagram of data distribution of each network element in an idle state after network registration is completed;

[0050] Figure 6 It is a schematic diagram of data distribution of each network element in a connected state after network registration is completed;

[0051] Figure 7 This is a schematic diagram of data distribution of each network element after the network is deregistered;

[0052] Figure 8 This is a schematic diagram of the architecture for deploying sidecar in a service mesh;

[0053] Fig. 9 A schematic diagram of the architecture of a communication system provided in an embodiment of the present application;

[0054] Fig.10 A flow chart of a communication method provided in an embodiment of the present application;

[0055] Fig.11 A global semantic graph including a functional model of mobility management network elements;

[0056] Fig.12 It is the global semantic graph for AMF and UDM;

[0057] Fig.13 is the semantic subgraph for AMF;

[0058] Fig.14 is the semantic subgraph for UDM;

[0059] Fig.15 A schematic diagram of the scenario in which the SBA semantic agent processes graph query requests based on GraphQL;

[0060] Fig.16 A schematic diagram of a registration process of a UE in a communication system according to an embodiment of the present application;

[0061] Fig.17 This is a schematic diagram of the architecture of a communication system including a SaaS network element and a SaaS semantic agent in an embodiment of the present application;

[0062] Fig.18 A schematic diagram of an online conference scenario;

[0063] Fig.19 A global semantic graph corresponding to the signaling interaction process of the online conference scenario;

[0064] Fig. 20 A schematic diagram of dividing the global semantic graph of an online conference scene into regions;

[0065] Fig.21 The access control device sub-map and campus management software sub-map in the online conference scenario;

[0066] Fig. 22 A schematic diagram of the structure of the SBA semantic agent provided in the embodiment of the present application;

[0067] Fig.23 A schematic diagram of a logical structure of a communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0068] The embodiments of the present application provide a communication method and related devices for improving the efficiency of accessing services of SBA network elements.

[0069] The embodiments of the present application are described below in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation mode of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the embodiments of the present application. It is known to those skilled in the art that with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0070] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: the existence of A alone, the existence of A and B at the same time, and the existence of B alone, where A and B can be singular or plural. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0071] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0072] Based on the ideas of Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) in cloud computing technology, the network architecture can also be divided into the following: Figure 2 The IaaS layer, PaaS layer and SaaS layer shown in the figure, the IaaS layer is mainly a computing and virtualization architecture, while the PaaS layer focuses on the protocol architecture, and the SaaS layer is applications and services. Among them, the PaaS layer has developed microservices, service grids and serverless architectures.

[0073] Specifically, microservices generally use a Uniform Resource Identifier (URI) resource tree to manage services. The URI resource tree includes multiple resource nodes. The add, search, update or delete CRUD operations on each resource node are supported by a RESTful interface based on the Hypertext Transfer Protocol (HTTP).

[0074] Service-based Architecture (SBA) is an important feature of the fifth generation mobile communication technology (5th Generation Mobile Communication Technology, 5G). Combining the network characteristics and technological development trends of the mobile core network, the service-based architecture can divide network services into several reusable network elements (i.e., SBA network elements), and each SBA network element corresponds to a service. Lightweight interfaces are used for communication between SBA network elements. Its goal is to achieve high efficiency, software-based, and open 5G systems. In the design process of SBA, the network architecture and processes are roughly divided first, and then the interface messages and data models of the SBA network elements are written according to the functions of different SBA network elements.

[0075] The 23.501 and 23.502 specifications of the 3rd Generation Partnership Project (3gpp) protocol provide a typical SBA design, define different processes in different scenarios, and divide the overall SBA architecture into different SBA network elements. The 29.XXX series of specifications of the 3gpp protocol define specific interface messages and data models for each SBA network element. Then, by calling the service of the SBA network element, a complete process can be formed.

[0076] Specifically, the 23.501 and 23.502 specifications of the 3gpp protocol use text to describe functions and processes, while the 29.XXX series uses the open application programming interface (OpenAPI) syntax to standardize (formalize) the interface messages and data structures. Therefore, in the design, development and maintenance cycle of the service-oriented architecture (including the iterative process from global service-oriented architecture deployment to the alignment of service interfaces between local SBA network elements), manual work is required, making it difficult to achieve agility and automation.

[0077] OpenAPI further describes the service interface schema of the network element, so that the interface message encoding and decoding module can be automatically generated. Figure 3 , Figure 3 This is a schematic diagram of the OpenAPI architecture. Figure 3 As shown in the figure, when defining the service interface of a network element based on OpenAPI syntax, it mainly includes the following parts:

[0078] Servers defines the URI of the network element;

[0079] Path defines the service interface (HTTP CRUD verb) provided by the network element;

[0080] RequestBody is the input parameter of the service interface, Responses is the return parameter of the service interface, Components defines the schema required by all service interfaces in the service, and the object defined in the schema can be referenced by requestBody and Responses in the path.

[0081] Specifically, the most important part is the service interface request and response defined by the path. The data structure required by the service interface path forms the schema. Each NF defines the schema independently. For example, the process of NF1 accessing NF2 is: the data in NF1 components is encapsulated in the requestBody of the NF2 service interface as the input of the service interface; NF2 takes out the data in the requestBody for processing to form the data in the NF2 components, and then encapsulates it in the responses of the NF2 service interface and returns it to NF1; NF1 will store the data in the NF1 components. Therefore, the operation and maintenance personnel need to manually write the service interface between NF1 and NF2, for example, they need to specifically define the Path in the OpenAPISchema.

[0082] However, if Figure 1 As shown in Figure 1, the actual service-oriented architecture often includes a large number of SBA network elements to provide different services. A request from a user device may require the use of services from multiple SBA network elements, and the data generated by the request will be processed and transmitted by multiple SBA network elements. Therefore, the data interaction between the various SBA network elements is very frequent and close. For example, please refer to Figure 4 , Figure 5 , Figure 6 and Figure 7 . Figure 4 This is a schematic diagram of data distribution of each network element before registration; Figure 4 This is a schematic diagram of data distribution of each network element before the network is registered; Figure 5 It is a schematic diagram of data distribution of each network element in an idle state after network registration is completed; Figure 6 It is a schematic diagram of data distribution of each network element in a connected state after network registration is completed; Figure 7 The figure is a diagram showing the data distribution of each network element after the network is deregistered.

[0083] Currently, developers and operation and maintenance personnel are still required to manually write the service interfaces between various SBA network elements, such as the need to specifically define the Path in the OpenAPI Schema. In addition, if the service interface of a certain SBA network element is subsequently updated, added, or deleted, it will also affect the service interfaces of many other related SBA network elements. For example, the Path in the OpenAPI Schema of multiple SBA network elements needs to be modified, resulting in low efficiency in providing services by the SBA network elements.

[0084] The service-oriented architecture based on microservices can manage service clusters from the perspective of URI Resource Tree, support service interfaces from the HTTP-based RESTful access mode, and describe interface data structures based on OpenAPI, but still regards services as independent design units. The service orchestration performed to complete the network processing flow only manages the front and back connections of services. Figure 8 , Figure 8 The following is a schematic diagram of the architecture for deploying sidecar in a service grid. Figure 8 The service grid shown in the figure begins to decouple some common processing in the service cluster and service connection and puts them in the sidecar of the network element service. For example, services such as load balancing, traffic management, instance migration or scaling can all be supported by the sidecar. However, the sidecar in the service grid is limited to implementing services such as load balancing, traffic management, instance migration or scaling, and does not involve the business logic of the SBA network element.

[0085] In view of this, the present application embodiment provides a communication method and related devices for improving the efficiency of accessing the services of SBA network elements. Fig. 9 , Fig. 9 This is a schematic diagram of the architecture of the communication system provided in the embodiment of the present application. Fig. 9 As shown, the communication system includes an SBA network element 101 (i.e., a distributed SBA network element) and an SBA semantic agent 102 corresponding to the SBA network element 101. The SBA network element 101 defined in the embodiment of the present application refers to a network element used to provide network services in a service-oriented architecture. Exemplarily, the SBA network element 101 includes, but is not limited to, a mobility management network element (Access and Mobility Management Function, AMF), a session management network element (Session Management Function, SMF), a user plane forwarding network element (User Plane Function, UPF) or an authentication and authorization network element (Authentication Server Function, AUSF), which are not specifically limited here.

[0086] In the embodiment of the present application, the SBA semantic agent 102 implements and executes the service of the SBA network element 101. Next, in conjunction with the accompanying drawings, the solution of the SBA semantic agent 102 implementing and executing the service of the SBA network element 101 in the embodiment of the present application is introduced. Fig.10 , Fig.10 A flow chart of the communication method provided in the embodiment of the present application is shown as follows: Fig.10 As shown, the communication method includes:

[0087] 201.SBA semantic agent obtains graph query request.

[0088] In the embodiment of the present application, the SBA semantic agent stores a semantic graph and a graph query language, and the semantic graph can be accessed by calling the graph query language. In the embodiment of the present application, the semantic graph in the SBA semantic agent synchronizes the business logic and business data of the SBA network element. Among them, it can be considered that the business data of the SBA is associated with the business logic of the SBA network element, or these business data are needed when executing the business logic. In other words, the service of the SBA network element is synchronized to the SBA semantic agent, and in the SBA semantic agent, the synchronized business logic and business data from the SBA network element are defined with the semantic graph as the data model, so as to define the service of the SBA network element by performing a graph query on the semantic graph. Therefore, by accessing the business logic and business data in the semantic graph, the service of the SBA network element can be realized. Specifically, the SBA semantic agent obtains a graph query request. Among them, the graph query request can be sent by the UE, or it can also be sent by other SBA semantic agents, or it can also be sent by other entities requesting access to the SBA service, and the embodiment of the present application does not limit this.

[0089] 202.The SBA semantic agent calls the graph query language based on the graph query request.

[0090] The SBA semantic agent parses the graph query request to determine the graph query language called by the graph query request.

[0091] 203.SBA semantic agent accesses the semantic graph through graph query language.

[0092] The SBA semantic agent executes the graph query language called by the graph query request, thereby accessing the semantic graph and realizing the service of the SBA network element.

[0093] In the embodiment of the present application, since the semantic graph in the SBA semantic agent synchronizes the business logic and business data of the SBA network element, the service of the SBA network element can be implemented by accessing the semantic graph in the SBA semantic agent. There is no need to initiate a request to call the service interface to the SBA network element. Therefore, there is no need to write a service interface for the SBA network element (such as the Path in the OpenAPI Schema), which improves the efficiency of accessing the services of the SBA network element.

[0094] In the embodiment of the present application, the graph query language stored in the SBA semantic agent includes Create Read Update Delete (CRUD) functions for the semantic graph. By calling the CRUD functions, CRUD operations can be performed on the semantic graph. Therefore, the graph query language of the semantic graph can express operations such as CRUD on the semantic graph, triggering the update of the data model defined by the semantic graph.

[0095] 204. The SBA semantic agent generates a processing result corresponding to the graph query request and sends the processing result to the SBA network element.

[0096] After the SBA semantic agent executes the graph query request, the data model of the semantic graph in the SBA semantic agent is updated. Since there is a synchronization relationship and binding relationship between the data of the semantic graph and the SBA network element, the data update of the data model of the semantic graph also needs to be synchronized to the SBA network element. Therefore, the SBA semantic agent will generate the processing result corresponding to the graph query request and send the processing result to the SBA network element, where the processing result includes the update information of the business data in the semantic graph. After receiving the processing result, the SBA network element updates the business data in the SBA network element according to the update information in the processing result, thereby completing the synchronization of the business data between the semantic graph and the SBA network element. The update of the business data in the SBA network element, reflected at the semantic graph level, is an update of the nodes, node attributes and relationships between nodes in the semantic graph.

[0097] It should be understood that in the embodiment of the present application, the synchronization between the semantic graph and the SBA network element is bidirectional, and data changes on either side may cause synchronous changes on the other. Specifically, on the one hand, after the business logic and business data in the SBA network element are synchronized to the semantic graph, if these business logic or business data are updated (such as addition, deletion or modification), then these updated business logic or business data in the SBA network element also need to be updated to the semantic graph; on the other hand, if the business logic or business data in the semantic graph is updated (such as the business data update caused by the SBA semantic agent after executing the graph query request), then these updated business logic or business data in the semantic graph also need to be updated to the SBA network element. In other words, there is a binding relationship between the business logic and business data in the semantic graph and the business logic and business data of the SBA network element, and data updates on either side will be synchronously updated to the other side.

[0098] In practical applications, the implementation methods of the above binding relationship and synchronization relationship include but are not limited to the following methods:

[0099] a) The semantic graph is bound to the data storage of SBA network elements through data structures;

[0100] b) The binding relationship between the semantic graph and the data of the SBA network element can be achieved through various means such as memory mapping or network remote operation;

[0101] c) The binding relationship between the semantic graph and the data of the SBA network element can be the correspondence of the original data. Specifically, the semantic graph can directly store the business logic and business data from the SBA network element, that is, the same business logic and business data will be stored in the semantic graph or the SBA network element at the same time. Alternatively, the semantic graph can realize the binding relationship by storing the business logic of the SBA network element and the index of the business data of the SBA network element;

[0102] d) The binding relationship between the semantic graph and the data of the SBA network element includes both single data units and the overall data structure, such as Key-Value binding, tree or graph topology binding, etc.

[0103] If the business logic of the SBA network element can be expressed by executing the graph query of the semantic graph through the SBA semantic agent, then the business logic of the SBA network element can be assigned to the SBA semantic agent for processing and execution, and the SBA network element service only needs to be responsible for the platform layer (P layer) function. In a possible implementation, if the SBA semantic agent parses the graph query request and determines that a certain business logic of the SBA network element cannot be fully expressed by executing the graph query of the semantic graph through the SBA semantic agent, then the processing result sent by the SBA semantic agent to the SBA network element may also include a target instruction. The target instruction is used to notify the SBA network element that the SBA network element will execute the service corresponding to this graph query request. Therefore, after receiving the processing result, the SBA network element executes the service of the SBA network element according to the target instruction in the processing result. In the embodiment of the present application, in addition to implementing the service of the SBA network element through the SBA semantic agent, the service corresponding to the graph query request can also be handed over to the SBA network element for execution, thereby improving the flexibility of the SBA network element in providing services.

[0104] As can be seen from the above, the communication system includes N SBA network elements. In order to implement the services of N SBA network elements in the communication system through the SBA semantic agent to perform graph query of the semantic graph, it is necessary to first write the business logic and business data of each SBA network element into the corresponding semantic graph and graph query language, as shown in the following figure. Fig. 9 The global semantic library 103 in the communication system shown. In a possible implementation, the service logic and service data of N SBA network elements in the communication system are uniformly defined as a complete global semantic graph, that is, the global semantic graph synchronizes the service logic and service data from the N SBA network elements. Therefore, by performing a graph query on the global semantic graph, the service of any SBA network element in the communication system can be realized.

[0105] In practical applications, the global semantic graph for N SBA network elements in a communication system generally includes a user-centric context and session model, an SBA network element-centric functional model, and an environment-centric physical model. In an embodiment of the present application, the SBA network element-centric functional model is used to define the business logic of the SBA network element, while the user-centric context and session model and the environment-centric physical model are used to describe the business data required to execute the business logic of the SBA network element. From the above, it can be seen that the update of the business data in the SBA network element is reflected at the semantic graph level, which is an update of the nodes, node attributes, and the relationships between nodes in the semantic graph. Specifically, it can be an update of the user-centric context and session model or the environment-centric physical model in the semantic graph.

[0106] For the sake of convenience, the following only takes the functional model of the global semantic graph including the mobility management network element (Access and Mobility Management Function, AMF) as an example for exemplary introduction. Fig.11 , Fig.11 is an example of a global semantic graph including a functional model of a mobility management network element. Fig.11 As shown, the dashed box on the right is the part related to the mobility management network element in the user-centric context and session model. The dashed box on the left is the functional model centered on the SBA network element. In this semantic graph, the subject, predicate, and object (Subject, Predict, Object) triples are used to describe the attributes and relationships of various SBA network elements, user contexts, and environments. It should be understood that in actual applications, the global semantic graph may also include functional models of SBA network elements such as session management network elements (Session Managem Function, SMF), user plane forwarding network elements (User Plane Function, UPF) or authentication server function (Authentication Server Function, AUSF), or it may also include the capacity, belonging area and topological relationship of the SBA network elements, or it may also include the user's geographic location and target itinerary, which are not limited here.

[0107] The global semantic graph can define both data models and different instances of the same data model, such as users in different locations and coverages, network elements responsible for different areas and coverages, etc.

[0108] The global semantic graph can be divided into different SBA network element domains according to the functions of different SBA network elements, such as AMF domain, SMF domain, UDM domain and AUSF domain, etc. Among them, the division of different SBA network element domains is only for the convenience of design. Any relationship can be formed between nodes in the same functional domain in the semantic graph, and any relationship can also be formed between nodes in different functional domains in the semantic graph.

[0109] In one possible implementation, the SBA semantic agent includes one SBA global semantic agent, which is in communication connection with N SBA network elements, that is, one SBA global semantic agent is used to manage the N SBA network elements in the communication system. Among them, the semantic graph in the SBA global semantic agent is a global semantic graph, which synchronizes the business logic and business data from N SBA network elements. In other words, the global semantic graph compiled in the embodiments of the present application and the graph query language for the global semantic graph are stored in the SBA global semantic agent. It can also be considered that the SBA global semantic agent stores the following Fig. 9The global semantic library 103 shown in the figure synchronizes the business logic and business data from N SBA network elements. The graph query for the global semantic graph describes the global processing flow of the network, such as a series of SBA network element services used by the UE access process or service request process. It can be seen that the services of N SBA network elements in the communication system are migrated to an SBA global semantic agent for unified execution, which improves the efficiency of the SBA global semantic agent in processing graph query requests.

[0110] In a possible implementation, a corresponding SBA semantic agent can be configured for each SBA network element in the communication system, and the service of each SBA network element will be executed by the SBA semantic agent corresponding to the SBA network element, and the SBA semantic agent corresponding to an SBA network element is the SBA semantic subagent in the embodiment of the present application. Specifically, the communication system includes N SBA network elements and N SBA semantic subagents, and the N SBA semantic subagents include a first SBA subagent, and the aforementioned SBA semantic agent is the first SBA semantic subagent, and each SBA semantic subagent is connected to a SBA network element in communication. Then the semantic graph in the SBA semantic subagent is a semantic subgraph, and the semantic subgraph synchronizes the business logic and business data from an SBA network element. In actual applications, each SBA semantic subagent can be deployed on an independent device (such as a server) to implement, or multiple SBA semantic subagents can be integrated and deployed on one device to implement, which is not limited here. In an embodiment of the present application, the business logic and business data of each SBA network element are synchronized with the semantic subgraph in an SBA semantic subagent, and each SBA semantic subagent is only responsible for executing the services of one SBA network element, thereby reducing the load and resource overhead of the SBA semantic subagent.

[0111] In an embodiment of the present application, the communication system may include only an SBA global semantic agent, or may include only an SBA semantic subagent, or may include both an SBA global semantic agent and an SBA semantic subagent. For a certain graph query request, both the SBA global semantic agent and the SBA semantic subagent may be used to process the graph query request.

[0112] SBA semantic subagents are independent of each other, and semantic subgraphs are also independent of each other. The SBA semantic subagent can express the service of an SBA network element by querying the graph of a semantic subgraph. Therefore, a complete network processing flow often needs to be decomposed into graph queries of several semantic subgraphs to complete. Specifically, in the complete network processing flow, when an SBA semantic subagent executes a graph query on the semantic subgraph based on the acquired graph query request, on the one hand, the SBA semantic subagent will generate the processing result corresponding to this graph query request so that the SBA network element corresponding to the SBA semantic subagent can synchronize data; on the other hand, the SBA semantic subagent determines the next service node in the network processing flow (i.e., the second SBA semantic subagent in the embodiment of the present application) based on the graph query request and the semantic subgraph in the SBA semantic subagent, wherein the second SBA semantic subagent is an SBA semantic subagent other than the first SBA semantic subagent among the N SBA semantic subagents. The SBA semantic agent generates a graph query request for the next hop based on the graph query request and the semantic subgraph in the SBA semantic subagent, and sends the graph query request for the next hop to the second SBA semantic subagent. After the second SBA semantic subagent receives the graph query request for the next hop, it accesses the semantic subgraph in the second SBA semantic subagent based on the graph query request for the next hop, wherein the process of the second SBA semantic subagent accessing its semantic subgraph is similar to the process of the aforementioned SBA semantic agent accessing its semantic graph, and will not be described in detail here.

[0113] For example, Fig. 9 The two SBA semantic agents 101 in the communication system shown in FIG. 1 are respectively connected to an SBA network element 102. Therefore, Fig. 9 The two SBA semantic agents 101 shown in the figure are SBA semantic sub-agents in the embodiment of the present application.

[0114] In practical applications, the semantic subgraphs of the N SBA semantic sub-agents in the embodiment of the present application can be decomposed from a complete global semantic graph. After the global semantic graph is decomposed into semantic subgraphs, the graph query decomposition of the global semantic graph is decomposed into graph queries of N semantic subgraphs. Figure 1Generally, it includes a user-centric context and conversation model, an SBA network element-centric functional model, and an environment-centric physical model. The process of decomposing the global semantic graph into subgraphs is mainly to first separate the functional models (i.e., business logic) corresponding to each independent SBA network element in the global semantic graph, and obtain N SBA network element-centric functional models (N business logics), where each SBA network element-centric functional model (business logic) corresponds to a semantic subgraph of the SBA network element. Similarly, since the global semantic graph includes business data from N SBA network elements, it is also necessary to allocate the business data in the global semantic graph to the semantic subgraphs corresponding to each SBA network element. Specifically, in the global semantic graph, the user-centric context and conversation model and the environment-centric physical model are decomposed according to the SBA network elements associated with them. In practical applications, this means that the user-centric context and conversation model and the environment-centric physical model are attached, resided, and belonged to the functional model of the SBA network element. Therefore, the semantic subgraph corresponding to each SBA network element includes the functional model corresponding to the SBA network element, the user context and session model associated with the functional model, and the environmental physical model. That is, the semantic subgraph corresponding to each SBA network element includes the business logic of the SBA network element and the business data associated with the business logic.

[0115] For example, Fig.12 The global semantic graph for AMF and UDM shown in the figure can be decomposed into Fig.13 The semantic subgraph for AMF and Fig.14 The semantic subgraph for UDM is shown, wherein there are often several identical user-centric context and session models or environment-centric physical models between the semantic subgraph for AMF and the semantic subgraph for UDM.

[0116] In practical applications, the same business data is often stored and used by multiple SBA network elements. Therefore, when the global semantic graph is decomposed into N semantic subgraphs, the same user context and session model are often decomposed and associated with the functional models corresponding to several SBA network elements. On the other hand, in a semantic subgraph, the functional model corresponding to the same SBA network element will be associated with several user contexts and session models. Specifically, during the decomposition process, if there are edges connecting the vertices of a semantic subgraph with the vertices of other semantic subgraphs, mirror images of other semantic subgraphs are established for the semantic subgraph to maintain their connection.

[0117] Generally speaking, if the graph query for the semantic subgraph triggers an update of the semantic subgraph, the SBA semantic subagent corresponding to the semantic subgraph needs to generate a graph query request, which carries the graph query result of the semantic subgraph, and then send the graph query request to the SBA semantic subagent that stores the same semantic subgraph image as the semantic subgraph, so that other SBA semantic subagents can update the stored semantic subgraph image according to the graph query result; alternatively, the above-mentioned SBA semantic subagents with the same semantic subgraph image can also actively send a graph query request to the SBA semantic subagent where the semantic subgraph update has occurred, so as to access the updated semantic subgraph and then update each semantic subgraph image; alternatively, the above-mentioned SBA semantic subagents with the same semantic subgraph image can update their own semantic subgraph only based on the business logic and business data stored by them, without performing synchronous updates based on the update status of other semantic subgraph images, and the embodiments of the present application are not limited to this.

[0118] In the process of decomposing the global semantic graph into semantic subgraphs, methods such as semantic subgraph mirroring are used to ensure the semantic consistency and automation between the global semantic graph and each semantic subgraph, shorten the iteration cycle from demand to protocol freezing in the existing communication protocol (3gpp protocol, etc.) formulation model, and facilitate the agile evolution of the service-oriented architecture throughout its life cycle from design, deployment to operation and maintenance.

[0119] The global semantic graph is decomposed into N semantic subgraphs, each of which synchronizes the business logic and business data from an SBA network element. Therefore, the semantic subgraphs are independent of each other. A graph query for a semantic subgraph can express the service of an SBA network element. Since these semantic subgraphs are independent of each other, the graph query for the global semantic graph that represents the global processing flow also needs to be decomposed into graph queries of several semantic subgraphs to complete. In other words, the decomposed semantic subgraph and the graph query of the semantic subgraph maintain semantic consistency with the aforementioned global semantic graph and the graph query of the global semantic graph. The global processing flow represented by the graph query of the global semantic graph can be collaboratively implemented by a series of graph queries of semantic subgraphs, and the state changes of the semantic subgraph caused during the graph query process are also consistent with the state changes of the global semantic graph.

[0120] In practical applications, the schema definition language (SDL) can be used to define the data model of the service and describe the processing logic of the service. On the server side, AST (Abstract Syntax Tree, AST) parsing can be used to support flexible queries on the data model. The platform layer (SBA network element) and the semantic layer (SBA semantic agent) are initially decoupled, and a very flexible language is defined to support the data model and processing logic of the semantic layer, and to support it at the platform layer.

[0121] Specifically, the embodiments of the present application may use semantic graph definition languages ​​such as JSON-LD or GRAPHQL SDL to define the business logic and business data in the SBA network element as semantic graphs and semantic subgraphs. Therefore, there is no need to define the service interface of the SBA network element through the Path in the OpenAPI Schema. Instead, any interface is flexibly generated based on the semantic graph data model. The interface is automatically generated without manual intervention, which improves the flexibility of the existing service-oriented interface design and the agility of evolution. In addition, since the semantic subgraph corresponding to each SBA network element is decomposed based on a complete global semantic graph, the data model of the semantic subgraph between SBA network elements is guaranteed to be consistent.

[0122] Furthermore, for the semantic graph and semantic subgraph obtained by using semantic graph definition languages ​​such as JSON-LD or GRAPHQL SDL, the graph query language used can be GraphQL, SPARQL or CYPHER. This facilitates the design of the association between the services executed by the SBA network element and the SBA semantic agent (SBA semantic subagent), and supports the overall service process orchestration and global optimization in the global business model design.

[0123] For ease of understanding, GraphQL is used as the semantic graph definition language in the embodiments of the present application for an exemplary introduction.

[0124] GraphQL is a service interface definition and access technology. It uses SDL to define the data model of SBA network elements, and also includes a query language for the data model (with CRUD operations like RESTful HTTP verb). The query language can be considered as a domain specific language (DSL), so the service interface of the SBA network element can be flexibly defined. Therefore, GraphQL's SDL can be regarded as a semantic graph definition language, and its interface query can also be regarded as a traversal of the semantic graph. It can be seen from this that GraphQL can be considered equivalent to semantic graph definition and query languages ​​such as Resource Description Framework (RDF).

[0125] Specifically, GraphQL technology can be used to define the schema of SBA network elements (i.e., the business logic and business data of SBA network elements) and flexibly construct its graph query. Since the graph query for the semantic graph is based on DSL, the compilation tool can be used to process the graph query. Fig.15 , Fig.15 The following is a schematic diagram of the scenario in which the SBA semantic proxy processes graph query requests based on GraphQL. Fig.15 As shown, in GraphQL technology, after the SBA semantic agent obtains the graph query request, it performs parse based on the graph query request and builds an abstract syntax tree (AST), then traverses each node on the AST, reads and writes data to other backend data sources (which can be databases or other microservice APIs) at each node, and finally builds the expected response and returns it.

[0126] For ease of understanding, the registration process of the communication system applied to the UE in the embodiment of the present application is taken as an example for exemplary introduction. In this example, the SBA network elements of the communication system include a base station, an SBA semantic agent corresponding to the base station (hereinafter referred to as the base station semantic agent), an AMF, and an SBA semantic agent corresponding to the AMF (hereinafter referred to as the AMF semantic agent). Fig.16 , Fig.16 FIG. 1 is a schematic diagram of a registration process of a UE in a communication system according to an embodiment of the present application. Fig.16 As shown, the UE registration process includes:

[0127] 301. The UE sends a Radio Resource Control (RRC) connection establishment request to the base station semantic agent.

[0128] The UE sends an RRCSetupRequest message to the base station semantic agent. The RRCSetupRequest message carries the RRC establishment cause and UE identifier, requesting to establish an RRC connection.

[0129] 302. The base station semantic agent sends an RRC setup message to the UE.

[0130] The RRC setup message carries detailed information about the signaling radio bearer (SRB) 1 resource configuration.

[0131] 303. The UE sends an RRC connection establishment completion message to the base station semantic agent.

[0132] The UE performs radio resource configuration according to the SRB1 resource information indicated by the RRC setup message, and then sends an RRCSetupComplete message (RRC connection establishment completion message) to the base station semantic agent.

[0133] 304. The base station semantic agent sends an initial UE message to the AMF semantic agent.

[0134] 305. The AMF semantic agent sends a downlink authentication message to the base station semantic agent. The authentication message is used to indicate the Identity query and requires the UE to report the identity information to the AMF semantic agent.

[0135] 306. The base station semantic agent forwards the authentication message from the AMF semantic agent to the UE.

[0136] 307. The UE sends uplink identity information to the base station semantic agent.

[0137] 308. The base station semantic agent forwards the identity information from the UE to the AMF semantic agent.

[0138] 309. The AMF semantic agent sends a downlink authentication request to the base station semantic agent.

[0139] 310. The base station semantic agent forwards the authentication request from the AMF semantic agent to the UE.

[0140] 311. The UE sends an uplink authentication response to the base station semantic agent.

[0141] After the UE receives the authentication parameters given by the network side, the UE will trigger the authentication algorithm. After the UE triggers the algorithm, a set of parameters will be generated. The purpose of this set of parameters is to compare with the authentication parameters carried in the authentication request. If the parameters are consistent, the UE will consider it to be a legitimate network and complete the UE's authentication of the network. After the comparison is completed, the result will be returned to the AMF semantic agent.

[0142] 312. The base station semantic agent sends the authentication response from the UE to the AMF semantic agent.

[0143] 313. The AMF semantic agent sends a downlink security mode command to the base station semantic agent.

[0144] 314. The base station semantic agent forwards the security mode command from the AMF semantic agent to the UE.

[0145] 315. The UE sends an uplink security mode completion response to the base station semantic agent.

[0146] The UE derives the key according to the encryption algorithm indicated by the security mode command, and then replies with a security mode completion response to the base station semantic agent.

[0147] 316. The base station semantic agent sends a security mode completion response from the UE to the AMF semantic agent.

[0148] 317. The AMF semantic agent sends an initial context establishment request to the base station semantic agent.

[0149] 318. The base station semantic agent forwards the initial context establishment request from the AMF semantic agent to the UE.

[0150] 319. The UE sends an uplink initial context establishment response to the base station semantic agent.

[0151] 320. The base station semantic agent sends an initial context establishment response from the UE to the AMF semantic agent.

[0152] The AMF semantic agent receives the initial context establishment response, and the UE registration process is completed.

[0153] exist Fig.16In the example shown (step 301 to step 320), a complete UE registration process requires the use of multiple services of the base station and AMF. If the UE registration process is applied to the embodiment of the present application, the N SBA network elements in the communication system may include a base station and an AMF, as well as an SBA semantic subagent corresponding to the base station and an SBA semantic subagent corresponding to the AMF, wherein the SBA semantic subagent of the base station stores a semantic graph and a graph query language corresponding to the semantic graph, the semantic graph in the SBA semantic subagent of the base station synchronizes the business logic and business data of the base station, the SBA semantic subagent of the AMF stores a semantic graph and a graph query language corresponding to the semantic graph, and the semantic graph in the SBA semantic subagent of the AMF synchronizes the business logic and business data of the AMF. Therefore, the above steps 302, 304, 306, 308, 310, 312, 314, 316, 318 and 320 can be executed by the SBA semantic subagent of the base station by performing a graph query on the semantic graph it stores; the above steps 305, 309, 313 and 317 can be executed by the SBA semantic subagent of the AMF by performing a graph query on the semantic graph it stores.

[0154] The applications and services in the SaaS layer are often completed by software operation services (SaaS network elements), and do not require the participation of SBA network elements and SBA semantic agents. In the embodiment of the present application, a SaaS semantic agent can also be deployed for the software operation service SaaS network element in the communication system, and the SaaS semantic agent and the SBA semantic agent are connected in communication. The SaaS semantic agent stores the semantic graph and the graph query language. The semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element. After the SaaS semantic agent obtains the graph query request, it calls the graph query language stored in the SaaS semantic agent according to the graph query request to access the semantic graph stored in the SaaS semantic agent through the graph query language. Specifically, the process of the SaaS semantic agent executing the service of the SaaS network element is similar to the process of the SBA semantic agent executing the service of the SBA network element. Please refer to the aforementioned description of the SBA semantic agent executing the service of the SBA network element, which will not be repeated here. The SaaS semantic agent and the SBA semantic agent can communicate and interact with each other, so that the services of the SBA network elements and the SaaS network elements are expressed by relying on the semantic agent to execute the graph query of the semantic graph. There is no need to write service interfaces (Path in OpenAPI Schema) for the interaction between the SBA semantic agent and the SaaS network element, and the interaction between the SaaS semantic agent and the SBA network element, thereby improving the working efficiency of the SBA semantic agent and the SaaS semantic agent.

[0155] See also Fig.17, Fig.17 FIG. 1 is a schematic diagram of the architecture of a communication system including a SaaS network element and a SaaS semantic agent in an embodiment of the present application. Fig.17 As shown, the communication system also includes a SaaS network element 104 and a SaaS semantic agent 105. Assume that a network processing flow includes the services of the SBA network element 101 and the services of the SaaS network element 104. Then, after the SaaS semantic agent 105 executes the services of the SaaS network element 104, the SBA semantic agent 102 is used as the next service node, and a graph query request is sent to the SBA semantic agent 102, and the SBA semantic agent 102 executes the services of the SBA network element 101 according to the graph query request; or, after the SBA semantic agent 102 executes the services of the SBA network element 101, the SaaS semantic agent 105 is used as the next service node, and a graph query request is sent to the SaaS semantic agent 105, and the SaaS semantic agent 105 executes the services of the SaaS network element 104 according to the graph query request.

[0156] Next, combine Figures 18 to 21 , which provides an exemplary introduction to the service flow of SaaS network elements and SaaS semantic agents. Fig.18 , Fig.18 Figure 1 is a schematic diagram of an online conference scenario. Fig.18 As shown, the user is using UE to hold an online meeting, and is walking from area J to the conference room in area F. During the walk, the user continues to use UE to participate in the meeting, and switches to the video conferencing system of the conference room after arriving at the conference room.

[0157] In this process, the user holds the user equipment from area J to the conference room in area F. Correspondingly, the service data cached by MEC1 behind base station 1 will be migrated to MCE2 of base station 2, the session connected by UE will also be migrated to the fixed network, and the video conference will be migrated from UE to the conference room equipment. For this, it is usually necessary to arrange the signaling interaction shown in Table 1 below for these migration processes.

[0158]

[0159] Table 1

[0160] Among them, the park management software in Table 1 above is responsible for integrating the park's 5G network, park network and video conferencing applications. The park management software can sense that the UE held by the user has entered the conference room through the access control device of the conference room, and the park management software interacts with the UE through the park service software. Among them, the above-mentioned access control device, park management software and park management service software are SaaS network elements in the embodiment of this application, and SaaS semantic agents can be deployed for the access control device, park management software and park management service software accordingly.

[0161] The signaling interaction process is to transmit information. If the communication system architecture in the embodiment of the present application is used, the above signaling interaction process can be implemented by a series of graph queries for semantic graphs. Fig.18 The signaling interaction process of the online conference scenario shown is defined as a global semantic graph. Fig.19 , Fig.19 is the global semantic graph corresponding to the signaling interaction process of the online conference scenario. Fig.19 The global semantic graph shown mainly reflects the relationship between nodes in the signaling interaction process (the attributes of the nodes are not reflected).

[0162] Furthermore, Fig. 20 In, for Fig.19 The global semantic graph of the online conference scenario shown in the figure divides the regions around the functional model corresponding to the SBA network element, the user context and session model associated with the functional model, and the environmental physical model. For details, please refer to Fig. 20 , Fig. 20 This is a schematic diagram of dividing the global semantic graph of the online conference scene into regions. Fig. 20 As shown in the figure, the global semantic graph has been divided by domain in the dotted box, but the nodes between different domains are still related. The global processing flow of the network is to perform graph queries on the nodes (and their attributes and relationships) on the global semantic graph, which can be expressed by graph queries on the global semantic graph.

[0163] Furthermore, you can follow Fig. 20 The area division shown will Fig.19 The global semantic graph shown is divided into multiple semantic subgraphs. For the sake of ease of description, the following only takes the semantic subgraph corresponding to the access control device (access control subgraph) and the semantic subgraph corresponding to the campus management software (campus management software subgraph) as an example to introduce the semantic subgraph. Fig.21 , Fig.21 It is the access control device sub-map and campus management software sub-map in the online conference scenario. Fig.21 The access control device subgraph and campus management software subgraph shown in Table 1 can be expressed by the graph query shown below.

[0164] 1. Perform a graph query on the access control device subgraph to obtain the user's access rights. Specifically, the user uses the access control device, and the access control device needs to verify the user's access rights to provide the door opening service. The graph query for this logical chain will obtain the user's access rights.

[0165] 2. After the user uses the access control device, the relationship between the user and the location is updated, that is, the user has moved from Area J to the conference room in Area F. This will trigger the subsequent logic of the campus management software.

[0166] 3. Perform a graph query on the subgraph of the campus management software to obtain the user's intention. It is detected that the user comes to the conference room in area F to continue the meeting. The conference service on the UE needs to be switched to the video equipment in the conference room to ensure user experience.

[0167] 4. The campus management software, based on the above user intention, queries the device used by the user (ie, UE), the campus-related services it provides (video conferencing in this example), and the attributes of these services (access address or ID of the current meeting, etc.).

[0168] 5. The campus management software updates the attributes and relationships of each node between the access control device subgraph and the campus management software subgraph.

[0169] 6. The campus service software finds that the UE's online conference service has been connected to the video device in Area F, so the conference on the UE is terminated.

[0170] The implementation process of each of the above steps can be subdivided into corresponding graph queries, so the above process is equivalent to the interaction between SaaS semantic agents corresponding to SaaS network elements (including access control devices, campus management software and campus service software).

[0171] The access control device subgraph contains three nodes, representing the node (vertex) of the access control device network element itself, the conference room node where the access control device is located, and the node of the user who is using the access control device, as well as the edges (edges) between them. In the access control device subgraph, the data of users and conference rooms are mirrored from the campus management software subgraph, in other words, the access control device subgraph and the campus management software subgraph. We will maintain a mechanism at the P layer to synchronize the data between the subgraph mirror and the source. This part of the work is not visible at the semantic layer.

[0172] Figures 18 to 21 The example shown shows how to implement the global network processing flow through the semantic graph and its graph query, especially the graph query of the subgraph synonym mode; specifically, the migration of user context at the business and network levels is achieved by maintaining the synonym relationship between the same user context subgraph and the semantic agents of different network elements. The entire process is reflected in the modification of the semantic graph, without the need for explicit semantic query or operation, and is achieved by the consistency guarantee of the distributed storage of synonymous subgraphs at the platform layer.

[0173] Accordingly, the present application also provides a related device for implementing the above solution. Fig. 22 , Fig. 22A schematic diagram of the structure of the SBA semantic agent provided in the embodiment of the present application. Fig. 22 As shown, the SBA semantic agent includes a transceiver unit 401 and a processing unit 402 .

[0174] The transceiver unit 401 is used to obtain a graph query request;

[0175] Processing unit 402, configured to call a graph query language according to a graph query request;

[0176] The processing unit 402 is further configured to access the semantic graph through a graph query language.

[0177] In one possible design, the processing unit 402 is further used to generate a processing result corresponding to the graph query request;

[0178] The processing unit 402 is also used to send the processing result to the SBA network element, wherein the processing result includes the update information of the business data in the semantic graph, so that the SBA network element updates the business data in the SBA network element according to the update information in the processing result.

[0179] In one possible design, the processing result also includes a target instruction, and the target instruction is used to instruct the SBA to execute the service of the SBA network element according to the target instruction in the processing result.

[0180] In one possible design, the SBA semantic agent is an SBA semantic subagent, and the communication system includes N SBA network elements and N SBA semantic subagents, where N is an integer greater than or equal to 2, and each SBA network element corresponds to an SBA semantic subagent. The semantic graph in the SBA semantic subagent is a semantic subgraph, and the semantic subgraph synchronizes the business logic and business data from an SBA network element.

[0181] In one possible design, the processing unit 402 is further configured to determine a second SBA semantic subagent according to the graph query request and the semantic subgraph in the SBA semantic subagent, wherein the second SBA semantic subagent is another SBA semantic subagent in the communication system;

[0182] The SBA semantic agent generates a graph query request for the next hop based on the graph query request and the semantic subgraph in the SBA semantic subagent;

[0183] The SBA semantic agent sends a next-hop graph query request to the second SBA semantic subagent, where the next-hop graph query request is used to access the semantic subgraph in the second SBA semantic subagent.

[0184] In one possible design, the communication system includes N SBA network elements and 1 global SBA semantic agent, where N is an integer greater than or equal to 2, and the SBA global semantic agent is communicatively connected to the N SBA network elements, wherein the semantic graph in the SBA global semantic agent is a global semantic graph, and the global semantic graph synchronizes business logic and business data from the N SBA network elements.

[0185] In a possible design, the global semantic graph includes N semantic subgraphs, each of which synchronizes the service logic and service data from an SBA network element.

[0186] In one possible design, the communication system also includes a software operation service SaaS network element and a SaaS semantic agent corresponding to the SaaS network element. The SaaS semantic agent includes a semantic graph and a graph query language. The semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element. The transceiver unit 401 is specifically used to receive a graph query request from the SaaS semantic agent.

[0187] In one possible design, the communication system also includes a software operation service SaaS network element and a SaaS semantic agent corresponding to the SaaS network element. The SaaS semantic agent includes a semantic graph and a graph query language. The semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element. The transceiver unit 401 is specifically used to send a next-hop graph query request to the SaaS semantic agent. The next-hop graph query request is used to access the semantic graph in the SaaS semantic agent.

[0188] In one possible design, the graph query language includes CRUD functions for adding, finding, updating, or deleting the semantic graph.

[0189] In one possible design, the semantic graph includes business logic and business data from SBA network elements.

[0190] In one possible design, the semantic graph includes the business logic of the SBA network element and an index for the business data of the SBA network element.

[0191] It should be noted that the information interaction, execution process, etc. between the modules / units in the communication device are the same as those in this application. Fig.10 The corresponding method embodiments are based on the same concept. For specific contents, please refer to the description in the method embodiments shown above in this application, which will not be repeated here.

[0192] See also Fig.23 , Fig.23 A schematic diagram of a logical structure of a communication device 50 provided in an embodiment of the present application. The communication device 50 may be deployed with Fig. 22 The SBA semantic agent described in the corresponding embodiment is used to implement Fig.10 The functions implemented by the SBA semantic agent in the corresponding embodiment. The computer device 50 includes: a memory 501, a processor 502, a communication interface 503 and a bus 504. The memory 501, the processor 502 and the communication interface 503 are connected to each other through the bus 504.

[0193] The memory 501 may be a read only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM). The memory 501 may store a program. When the program stored in the memory 501 is executed by the processor 502, the processor 502 and the communication interface 503 are used to execute steps 101-103 of the above data processing method embodiment.

[0194] The processor 502 may be a central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), a graphics processing unit (GPU), a digital signal processor (DSP), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components or any combination thereof, for executing related programs to implement one or more steps of steps 101-103 of the data processing method embodiment in the present application. The steps of the data processing method disclosed in the embodiment of the present application may be executed by a compiler and an executor, wherein the compiler and the executor may be executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 501, and the processor 502 reads the information in the memory 501, and executes one or more steps of steps 201-204 of the data processing method embodiment in the present application in combination with its hardware.

[0195] The communication interface 503 uses a transceiver device such as but not limited to a transceiver to implement communication between the computer device 50 and other devices or a communication network.

[0196] The bus 504 can realize a path for transmitting information between various components of the computer device 50 (for example, the memory 501, the processor 502, and the communication interface 503). The bus 504 can be a peripheral component interconnect standard (PCI) bus or an extended industry standard architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, Fig.23 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0197] It should be further noted that the communication system embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the communication system embodiment provided in the embodiment of the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0198] Through the description of the above implementation mode, the technicians in the field can clearly understand that the embodiments of the present application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by special hardware including application-specific integrated circuits, special CPUs, special memories, special components, etc. In general, all functions completed by computer programs can be easily implemented with corresponding hardware, and the specific hardware structure used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the embodiments of the present application, software program implementation is a better implementation method in more cases. Based on such an understanding, the technical solution of the embodiments of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, a U disk, a mobile hard disk, a ROM, a RAM, a disk or an optical disk, etc., including a number of instructions to enable a computer device (which can be a personal computer, a training device, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0199] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0200] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, a computer, a training device, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, training device, or data center. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

Claims

1. A communication method, applied to a communication system, characterized in that: The communication system includes a service-based architecture (SBA) network element and an SBA semantic agent, the SBA semantic agent is configured with a semantic graph and a graph query language, the semantic graph in the SBA semantic agent synchronizes the business logic and business data from the SBA network element, and the method includes: The SBA semantic agent obtains a graph query request; The SBA semantic agent calls the graph query language in the SBA semantic agent according to the graph query request; The SBA semantic agent accesses the semantic graph in the SBA semantic agent through a graph query language in the SBA semantic agent.

2. The method according to claim 1, characterized in that After the SBA semantic agent accesses the semantic graph in the SBA semantic agent through the graph query language in the SBA semantic agent, the method further includes: The SBA semantic agent generates update information for a semantic graph in the SBA semantic agent; The SBA semantic agent sends a processing result to the SBA network element, wherein the processing result includes the update information, so that the SBA network element updates the service data in the SBA network element according to the update information in the processing result.

3. The method according to claim 1, characterized in that After the SBA semantic agent accesses the semantic graph in the SBA semantic agent through the graph query language in the SBA semantic agent, the method further includes: The SBA semantic agent generates a target instruction; The SBA semantic agent sends a processing result to the SBA network element, wherein the processing result includes the target instruction, and the target instruction is used to instruct the SBA network element to execute the service of the SBA network element according to the target instruction in the processing result.

4. The method according to any one of claims 1 to 3, characterized in that The communication system includes N SBA network elements and N SBA semantic subagents, the N SBA semantic subagents include a first SBA subagent, the SBA semantic agent is the first SBA semantic subagent, N is an integer greater than or equal to 2, each of the SBA network elements corresponds to one SBA semantic subagent, the semantic graph in the SBA semantic subagent is a semantic subgraph, and the semantic subgraph synchronizes the business logic and business data from one of the SBA network elements.

5. The method according to claim 4, characterized in that The SBA semantic agent accesses the semantic graph through the graph query language, including: The first SBA semantic subagent determines a second SBA semantic subagent according to the graph query request and the semantic subgraph in the SBA semantic subagent, wherein the second SBA subagent is an SBA semantic subagent among the N SBA semantic subagents; The first SBA semantic subagent generates a next-hop graph query request according to the graph query request and the semantic subgraph in the SBA semantic subagent; The first SBA semantic subagent sends the next-hop graph query request to the second SBA semantic subagent, where the next-hop graph query request is used to access the semantic subgraph in the second SBA semantic subagent.

6. The method according to any one of claims 1 to 3, characterized in that The communication system includes N SBA network elements and 1 global SBA semantic agent, where N is an integer greater than or equal to 2, and the SBA global semantic agent is communicatively connected to the N SBA network elements, wherein the semantic graph in the SBA global semantic agent is a global semantic graph, and the global semantic graph synchronizes the business logic and business data from the N SBA network elements.

7. The method according to claim 6, characterized in that The global semantic graph includes N semantic subgraphs, each of which synchronizes the service logic and service data from one of the SBA network elements.

8. The method according to any one of claims 1 to 7, characterized in that The communication system further includes a software operation service SaaS network element and a SaaS semantic agent corresponding to the SaaS network element, wherein the SaaS semantic agent is configured with a semantic graph and a graph query language, and the semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element, and the SBA semantic agent obtains a graph query request, including: The SBA semantic agent receives a graph query request from the SaaS semantic agent.

9. The method according to any one of claims 1 to 7, characterized in that The communication system further includes a software operation service SaaS network element and a SaaS semantic agent corresponding to the SaaS network element, the SaaS semantic agent is configured with a semantic graph and a graph query language, the semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element, and the method further includes: The SBA semantic agent sends a next-hop graph query request to the SaaS semantic agent, where the next-hop graph query request is used to access the semantic graph in the SaaS semantic agent.

10. The method according to any one of claims 1 to 9, characterized in that The graph query language in the SBA semantic agent includes CRUD functions for adding, searching, updating or deleting the semantic graph.

11. The method according to any one of claims 1 to 10, characterized in that The semantic graph in the SBA semantic agent includes business logic and business data from the SBA network element.

12. The method according to any one of claims 1 to 10, characterized in that The semantic graph includes the business logic of the SBA network element and an index of the business data of the SBA network element.

13. A service-based architecture (SBA) semantic agent, applied to a communication system, characterized in that: The communication system includes a service-based architecture (SBA) network element and an SBA semantic agent, wherein the SBA semantic agent is configured with a semantic graph and a graph query language, wherein the semantic graph in the SBA semantic agent synchronizes the service logic and service data from the SBA network element, and wherein the SBA semantic agent includes: A transceiver unit, used to obtain a graph query request; A processing unit, configured to call a graph query language in the SBA semantic agent according to the graph query request; The processing unit is further used to access the semantic graph in the SBA semantic agent through the graph query language in the SBA semantic agent.

14. The SBA semantic agent according to claim 13, characterized in that: The processing unit is further used to generate update information for the semantic graph in the SBA semantic agent; The SBA semantic agent sends a processing result to the SBA network element, wherein the processing result includes the update information, so that the SBA network element updates the service data in the SBA network element according to the update information in the processing result.

15. The SBA semantic agent according to claim 13, characterized in that: The processing unit is also used to generate a target instruction and send a processing result to the SBA network element, wherein the processing result includes the target instruction, and the target instruction is used to instruct the SBA network element to execute the service of the SBA network element according to the target instruction in the processing result.

16. The SBA semantic agent according to any one of claims 13 to 15, characterized in that: The communication system includes N SBA network elements and N SBA semantic subagents, the N SBA semantic subagents include a first SBA subagent, the SBA semantic agent is the first SBA semantic subagent, N is an integer greater than or equal to 2, each of the SBA network elements corresponds to one SBA semantic subagent, the semantic graph in the SBA semantic subagent is a semantic subgraph, and the semantic subgraph synchronizes the business logic and business data from one of the SBA network elements.

17. The SBA semantic agent according to claim 16, characterized in that: The processing unit is specifically used to determine a second SBA semantic subagent based on the graph query request and the semantic subgraph in the SBA semantic subagent, where the second SBA subagent is an SBA semantic subagent among the N SBA semantic subagents; generate a next-hop graph query request based on the graph query request and the semantic subgraph in the SBA semantic subagent; and send the next-hop graph query request to the second SBA semantic subagent, where the next-hop graph query request is used to access the semantic subgraph in the second SBA semantic subagent.

18. The SBA semantic agent according to any one of claims 13 to 15, characterized in that: The communication system includes N SBA network elements and 1 global SBA semantic agent, where N is an integer greater than or equal to 2, and the SBA global semantic agent is communicatively connected to the N SBA network elements, wherein the semantic graph in the SBA global semantic agent is a global semantic graph, and the global semantic graph synchronizes the business logic and business data from the N SBA network elements.

19. The SBA semantic agent according to claim 18, characterized in that: The global semantic graph includes N semantic subgraphs, each of which synchronizes the service logic and service data from one of the SBA network elements.

20. The SBA semantic agent according to any one of claims 13 to 19, characterized in that: The communication system also includes a software operation service SaaS network element and a SaaS semantic agent corresponding to the SaaS network element. The SaaS semantic agent is configured with a semantic graph and a graph query language. The semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element. The transceiver unit is specifically used to receive a graph query request from the SaaS semantic agent.

21. The SBA semantic agent according to any one of claims 13 to 19, characterized in that: The communication system also includes a software operation service SaaS network element and a SaaS semantic agent corresponding to the SaaS network element. The SaaS semantic agent includes a semantic graph and a graph query language. The semantic graph in the SaaS semantic agent synchronizes the business logic and business data from the SaaS network element. The transceiver unit is also used to send a next-hop graph query request to the SaaS semantic agent. The next-hop graph query request is used to access the semantic graph in the SaaS semantic agent.

22. The SBA semantic agent according to any one of claims 13 to 21, characterized in that: The graph query language in the SBA semantic agent includes CRUD functions for adding, searching, updating or deleting the semantic graph.

23. The SBA semantic agent according to any one of claims 13 to 22, characterized in that: The semantic graph in the SBA semantic agent includes business logic and business data from the SBA network element.

24. The SBA semantic agent according to any one of claims 13 to 22, characterized in that: The semantic graph includes the business logic of the SBA network element and an index of the business data of the SBA network element.

25. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 12 is implemented.

26. A computer program product, characterized in that The computer program product stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the method according to any one of claims 1 to 12 is implemented.

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