Multi-element service co-processing method, device and system, medium and program product

Abstract

The invention relates to a multi-element service cooperative processing method, device and system, a medium and a program product. The multi-element service co-processing method is executed by a core network device, and the multi-element service co-processing method comprises: receiving a multi-element service request sent by a user equipment, the multi-element service request comprising a connection service request and a data service request; and carrying out cooperative processing on the multi-element service request. According to the invention, the cooperative processing capability of the core network equipment on connection and AI data services is enhanced.

Description

Technical Field

[0001] The present disclosure relates to the field of wireless communication technology, and in particular to a multi-factor service collaborative processing method, device and system, medium and program product. Background Art

[0002] In the context of 6G network development, related technical network services only provide basic connection and data transmission functions, which can no longer meet users' needs for AI (Artificial Intelligence) data services. UE (User Equipment) has limited computing power and is unable to independently process complex AI tasks, so AI tasks need to be offloaded to the network side. However, related technical networks lack an effective collaborative processing mechanism and cannot efficiently process connection service and AI data service requests at the same time, resulting in low service efficiency and poor user experience. Summary of the invention

[0003] Through research, the inventors found that how to support the coordinated processing of services such as connections and AI data has become a technical problem that needs to be urgently solved in existing networks.

[0004] In view of at least one of the above technical problems, the present disclosure provides a multi-factor service collaborative processing method, device and system, medium and program product, and the core network equipment enhances the collaborative processing capabilities of connection and AI data services.

[0005] According to one aspect of the present disclosure, a multi-factor service collaborative processing method is provided, which is executed by a core network device and includes:

[0006] Receiving a multi-factor service request sent by a user equipment, wherein the multi-factor service request includes a connection service request and a data service request;

[0007] The multi-factor service request is collaboratively processed.

[0008] In some embodiments of the present disclosure, the collaborative processing of the multi-factor service request includes:

[0009] Extracting a connection service request and a data service request from the multi-factor service request;

[0010] Establishing a connection between the user equipment and the network according to the connection service request;

[0011] According to the data service request, a corresponding data service execution node is selected and a data service task is issued.

[0012] In some embodiments of the present disclosure, the core network device includes at least one of an evolved access and mobility management function network element, a connection service management function network element, and a data service management function network element.

[0013] In some embodiments of the present disclosure, the step of establishing a connection from the user equipment to the network according to the connection service request is performed by the connection service management function network element.

[0014] In some embodiments of the present disclosure, the step of selecting a corresponding data service execution node according to the data service request and issuing a data service task is performed by the data service management function network element.

[0015] In some embodiments of the present disclosure, extracting the connection service request and the data service request from the multi-factor service request includes:

[0016] The evolved access and mobility management function network element decomposes the multi-factor service request into separate connection service requests and data service requests;

[0017] The evolved access and mobility management function network element selects the corresponding connection service management function network element and data service management function network element;

[0018] The evolved access and mobility management function network element sends the connection service request to the connection service management function network element;

[0019] The evolved access and mobility management function network element sends the data service request to the service management function network element.

[0020] In some embodiments of the present disclosure, extracting the connection service request and the data service request from the multi-factor service request includes:

[0021] The evolved access and mobility management function network element selects the corresponding connection service management function network element and data service management function network element;

[0022] The evolved access and mobility management function network element sends the multi-factor service request to the connection service management function network element and the service management function network element respectively;

[0023] The connection service management function network element parses the multi-factor service request and extracts the connection service request;

[0024] The service management function network element parses the multi-factor service request and extracts the data service request.

[0025] In some embodiments of the present disclosure, the evolved access and mobility management function network element selects the corresponding connection service management function network element and data service management function network element, including:

[0026] The evolved access and mobility management function network element selects a corresponding connection service management function network element and a data service management function network element in the network according to the service area.

[0027] In some embodiments of the present disclosure, the data service is an artificial intelligence data service, and the data service management function network element is an artificial intelligence service management function network element.

[0028] In some embodiments of the present disclosure, selecting a corresponding data service execution node according to the data service request and issuing a data service task includes: an artificial intelligence service management function network element selecting a corresponding artificial intelligence service execution node according to at least one of the artificial intelligence service business type and location area requested in the artificial intelligence service request; and the artificial intelligence service management function network element sending the artificial intelligence task to the selected artificial intelligence service execution node.

[0029] In some embodiments of the present disclosure, the core network device also includes an artificial intelligence service execution node.

[0030] In some embodiments of the present disclosure, selecting a corresponding data service execution node according to the data service request and issuing a data service task further includes:

[0031] The artificial intelligence service execution nodes cooperate to execute the artificial intelligence tasks;

[0032] The artificial intelligence service execution node returns the artificial intelligence task execution result to the user device.

[0033] In some embodiments of the present disclosure, the artificial intelligence service execution node includes a data plane functional network element and a data storage functional network element.

[0034] In some embodiments of the present disclosure, the artificial intelligence task includes at least one of a data collection task, a data analysis task, a data processing task, and a data storage task.

[0035] In some embodiments of the present disclosure, the artificial intelligence service execution node returns the artificial intelligence task execution result to the user device, including: the data storage function network element sends a stored message of the artificial intelligence data service result to the data service management function network element, wherein the stored message includes the storage address of the artificial intelligence data service result; the data service management function network element sends the storage address of the artificial intelligence data service result to the evolved access and mobility management function network element; the evolved access and mobility management function network element sends the storage address of the artificial intelligence data service result to the user device.

[0036] In some embodiments of the present disclosure, receiving a multi-factor service request sent by a user equipment includes:

[0037] receiving a multi-factor service request sent by a user equipment based on a protocol configuration option field of a non-access stratum message of a protocol data unit session; or,

[0038] Based on the newly added non-access layer message of the dedicated multi-factor service request, a multi-factor service request sent by the user equipment is received.

[0039] In some embodiments of the present disclosure, the data service is an artificial intelligence data service.

[0040] In some embodiments of the present disclosure, the multi-factor service request is a collaborative request for a connection service and an artificial intelligence data service.

[0041] In some embodiments of the present disclosure, the connection service request is a protocol data unit session establishment request for the connection service.

[0042] In some embodiments of the present disclosure, the data service request is a data service request for an artificial intelligence data service.

[0043] In some embodiments of the present disclosure, the data service request includes at least one of the artificial intelligence data service business type, the requested artificial intelligence data service area, the required computing power resource type, and the service quality requirement of the requested service.

[0044] In some embodiments of the present disclosure, the artificial intelligence data service business type includes at least one of statistical analysis of registrations or sessions, artificial intelligence model training, and artificial intelligence reasoning.

[0045] In some embodiments of the present disclosure, the computing resource type includes at least one of a central processing unit, a graphics processing unit, and storage.

[0046] In some embodiments of the present disclosure, the quality of service requirement includes training accuracy.

[0047] According to another aspect of the present disclosure, a multi-factor service collaborative processing method is provided, which is executed by a user equipment, and includes:

[0048] A multi-factor service request is sent to a core network device, wherein the multi-factor service request includes a connection service request and a data service request, and the core network device is used to collaboratively process the multi-factor service request.

[0049] According to another aspect of the present disclosure, a core network device is provided, including:

[0050] An evolved access and mobility management function network element is configured to receive a multi-factor service request sent by a user equipment, wherein the multi-factor service request includes a connection service request and a data service request;

[0051] The collaborative processing module is configured to collaboratively process the multi-factor service request.

[0052] According to another aspect of the present disclosure, a core network device is provided, including:

[0053] a memory configured to store instructions; and

[0054] The processor is configured to execute the instructions so that the core network device implements the multi-factor service collaborative processing method as described in any of the above embodiments.

[0055] According to another aspect of the present disclosure, a user equipment is provided, including:

[0056] a memory configured to store instructions; and

[0057] The processor is configured to execute the instructions so that the user equipment implements the multi-factor service collaborative processing method as described in any of the above embodiments.

[0058] According to another aspect of the present disclosure, a multi-factor service collaborative processing system is provided, comprising a core network device as described in any of the above embodiments, and a user device as described in any of the above embodiments.

[0059] According to another aspect of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the multi-factor service collaborative processing method as described in any of the above embodiments is implemented.

[0060] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the multi-factor service collaborative processing method as described in any of the above embodiments is implemented.

[0061] The present disclosure enhances the collaborative processing capabilities of core network equipment for connections and AI data services. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present disclosure 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 some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0063] Figure 1 The present invention provides a schematic diagram of some embodiments of the multi-factor service collaborative processing method.

[0064] Figure 2 Schematic diagram of other embodiments of the multi-factor service collaborative processing method disclosed in the present invention.

[0065] Figure 3 Schematic diagram of other embodiments of the multi-factor service collaborative processing method disclosed in the present invention.

[0066] Figure 4 Schematic diagrams of some further embodiments of the multi-factor service collaborative processing method disclosed in the present invention.

[0067] Figure 5 Schematic diagrams of some further embodiments of the multi-factor service collaborative processing method disclosed in the present invention.

[0068] Figure 6 It is a schematic diagram of the structure of some embodiments of the core network device disclosed in the present invention.

[0069] Figure 7 It is a schematic diagram of the structure of other embodiments of the core network device disclosed in the present invention.

[0070] Figure 8 It is a structural diagram of some other embodiments of the core network device disclosed in the present invention.

[0071] Fig. 9 It is a schematic diagram of the structure of other embodiments of the core network device disclosed in the present invention.

[0072] Fig.10 The present invention is a schematic diagram of the structure of some embodiments of the user equipment disclosed herein.

[0073] Fig.11 It is a schematic diagram of the structure of some embodiments of the multi-factor service collaborative processing system disclosed in the present invention. DETAILED DESCRIPTION

[0074] The technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present disclosure and its application or use. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0075] Unless specifically stated otherwise, the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure.

[0076] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0077] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered as part of the specification.

[0078] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0079] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0080] The inventors also found through research that the traditional network services of related technologies mainly focus on connection services, that is, providing users with network access and data transmission functions. However, in new 6G business scenarios such as perception and AI, users often need to obtain diversified AI data services such as data analysis and AI reasoning on the basis of connection services. Therefore, how to support the coordinated processing of services such as connection and AI data has become an urgent problem to be solved in existing networks.

[0081] In response to the growing demand for AI data services, due to the limited computing power of terminals, users can offload subsequent AI tasks to the network side after collecting data. They can request AI data services from the network at the same time as requesting connection services. Therefore, core network equipment needs to enhance the collaborative processing capabilities of connections and AI data services.

[0082] In view of at least one of the above technical problems, the present disclosure provides a multi-factor service collaborative processing method, device and system, medium and program product, which are described below through embodiments.

[0083] Figure 1 The present invention provides a schematic diagram of some embodiments of the multi-factor service collaborative processing method. Figure 1 The embodiment may be executed by the core network device of the present disclosure or the multi-factor service collaborative processing system of the present disclosure. Figure 1 As shown, Figure 1 The method of the embodiment may include at least one of steps 100 to 200 .

[0084] Step 100: The core network device receives a multi-factor service request sent by a user equipment, wherein the multi-factor service request includes a connection service request and a data service request.

[0085] In some embodiments of the present disclosure, step 100 may include at least one of steps 110 to 120 .

[0086] Step 110: receiving a multi-factor service request sent by a user equipment based on a PCO (Protocol Configuration Option) field of a NAS (Non-access stratum) message of a protocol data unit session.

[0087] Step 120: Receive a multi-factor service request sent by a user equipment based on the newly added non-access layer message of the dedicated multi-factor service request.

[0088] In some embodiments of the present disclosure, the core network device may include at least one of an eAMF (evolved Access and Mobility Management Function), a CSMF (Connection Service Management Function), a DSMF (Data Service Management Function), and an artificial intelligence service execution node.

[0089] In some embodiments of the present disclosure, the evolved access and mobility management functional network element may be configured to enhance the collaborative processing capability of multiple element services such as data services and connection services in addition to being responsible for UE access and mobility management related signaling.

[0090] In some embodiments of the present disclosure, the CSMF may be configured to be responsible for control functions such as session establishment, modification, and release between a user and a network in a next generation network.

[0091] In some embodiments of the present disclosure, DSMF can be configured to translate and decompose AI data service requirements into AI tasks, select specific UE, RAN, AI data service execution nodes and other NFs with different computing resources, form an executable UE, RAN, AI data service execution node logical topology, and control the work chain to implement specific AI data service functions.

[0092] In some embodiments of the present disclosure, the data service may be an artificial intelligence data service.

[0093] In some embodiments of the present disclosure, the data service management function network element may be an artificial intelligence service management function network element.

[0094] In some embodiments of the present disclosure, the multi-factor service request may be a collaborative request for a connection service and an artificial intelligence data service.

[0095] In some embodiments of the present disclosure, the connection service request may be a PDU (Protocol Data Unit) session establishment request for the connection service.

[0096] In some embodiments of the present disclosure, the data service request may be a data service request for an artificial intelligence data service.

[0097] In some embodiments of the present disclosure, the data service request may include at least one of the artificial intelligence data service business type, the requested artificial intelligence data service area, the required computing resource type, and the QoS (Quality of Service) requirement of the requested service.

[0098] In some embodiments of the present disclosure, the artificial intelligence data service business type may include at least one of statistical analysis of registrations or sessions, artificial intelligence model training, and artificial intelligence reasoning.

[0099] In some embodiments of the present disclosure, the computing resource type may include at least one of a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and a storage.

[0100] In some embodiments of the present disclosure, the quality of service requirement may include training accuracy.

[0101] Step 200: The core network device collaboratively processes the multi-factor service request.

[0102] In some embodiments of the present disclosure, step 200 may include at least one of steps 210 to 220 .

[0103] Step 210: extracting a connection service request and a data service request from the multi-element service request.

[0104] In some embodiments of the present disclosure, step 210 may include at least one of steps 211 to 214 .

[0105] Step 211: The evolved access and mobility management function network element decomposes the multi-factor service request into separate connection service requests and data service requests.

[0106] Step 212: The evolved access and mobility management function network element selects a corresponding connection service management function network element and a data service management function network element.

[0107] In some embodiments of the present disclosure, step 212 may include: the evolved access and mobility management function network element selects a corresponding connection service management function network element and a data service management function network element in the network according to the service area.

[0108] Step 213: The evolved access and mobility management function network element sends the connection service request to the connection service management function network element.

[0109] Step 214: The evolved access and mobility management function network element sends the data service request to the service management function network element.

[0110] In some other embodiments of the present disclosure, step 210 may include at least one of steps 21a to 21d.

[0111] Step 21a: The evolved access and mobility management function network element selects a corresponding connection service management function network element and a data service management function network element.

[0112] Step 21b: The evolved access and mobility management function network element sends the multi-factor service request to the connection service management function network element and the service management function network element respectively.

[0113] Step 21c: the connection service management function network element parses the multi-factor service request and extracts the connection service request.

[0114] Step 21d: The service management function network element parses the multi-factor service request and extracts the data service request.

[0115] Step 220: Establish a connection from the user equipment to the network according to the connection service request.

[0116] In some embodiments of the present disclosure, step 220 may be performed by the connection service management function network element.

[0117] Step 230: According to the data service request, a corresponding data service execution node is selected and a data service task is issued.

[0118] In some embodiments of the present disclosure, step 230 may be performed by the data service management function network element.

[0119] In some embodiments of the present disclosure, step 230 may include at least one of steps 231 to 234 .

[0120] Step 231: The artificial intelligence service management function network element selects a corresponding artificial intelligence service execution node according to at least one of the artificial intelligence service business type and location area requested in the artificial intelligence service request.

[0121] Step 232: The artificial intelligence service management function network element sends the artificial intelligence task to the selected artificial intelligence service execution node.

[0122] Step 233: The artificial intelligence service execution nodes cooperate to execute the artificial intelligence task.

[0123] In some embodiments of the present disclosure, the artificial intelligence service execution node may include at least one of a DPF (Data Plane Function) and a DSF (Data Storage Function).

[0124] In some embodiments of the present disclosure, the DPF may be configured to implement functions such as data collection, transmission, preprocessing, and analysis.

[0125] In some embodiments of the present disclosure, DSF may be configured to store collected data and data service results, etc.

[0126] In some embodiments of the present disclosure, the artificial intelligence task may include at least one of a data collection task, a data analysis task, a data processing task, and a data storage task.

[0127] Step 234: The artificial intelligence service execution node returns the artificial intelligence task execution result to the user device.

[0128] In some embodiments of the present disclosure, step 234 may include: the data storage function network element sends a stored message of the artificial intelligence data service result to the data service management function network element, wherein the stored message includes the storage address of the artificial intelligence data service result; the data service management function network element sends the storage address of the artificial intelligence data service result to the evolved access and mobility management function network element; the evolved access and mobility management function network element sends the storage address of the artificial intelligence data service result to the user device.

[0129] The above-mentioned embodiments of the present disclosure address the problem that users in the next-generation network simultaneously request connection services and AI data services, and propose a core network connection service and AI data service coordination method and process, which supports the core network to simultaneously process multi-factor collaborative service requests for connection + AI data services initiated by UE, thereby realizing the core network's collaborative processing of connection and AI data services.

[0130] Figure 2 Schematic diagram of other embodiments of the multi-factor service collaborative processing method disclosed in the present invention. Figure 2 The embodiment may be executed by the user equipment of the present disclosure or the multi-factor service collaborative processing system of the present disclosure. Figure 2 As shown, Figure 2 The method of an embodiment may include step 20 .

[0131] Step 20: The user equipment sends a multi-factor service request to the core network equipment, wherein the multi-factor service request includes a connection service request and a data service request, and the core network equipment is used to collaboratively process the multi-factor service request.

[0132] In some embodiments of the present disclosure, the user equipment may be various types of terminal equipment having a wireless communication function and supporting users to access network services.

[0133] The above-mentioned embodiment of the present disclosure proposes a method for the UE to initiate a collaborative service request for connection+AI data service to the core network through a NAS message.

[0134] Figure 3 Schematic diagram of other embodiments of the multi-factor service collaborative processing method disclosed in the present invention. Figure 3 The embodiment can be executed by the multi-factor service collaborative processing system disclosed in the present invention. Figure 3 As shown, Figure 3 The method of the embodiment may include at least one of steps 1 to 7.

[0135] Step 1: The UE initiates a connection and AI data service collaborative service request to the network (core network equipment). The UE can send a connection and AI data service collaborative service request to the eAMF through an enhanced NAS message. The connection service request is a PDU session establishment request for the UE. The AI ​​data service request may include the requested AI task (such as AI model training, AI reasoning, etc.), the required computing resource type (such as CPU, GPU, storage, etc.), and the specific QoS requirements of the computing task (such as training accuracy, etc.).

[0136] Step 2, eAMF, connection service management function network element, and AI data service management function network element participate in the multi-factor collaborative service request processing. Among them, the eAMF can disassemble and translate the multi-factor collaborative service request into separate connection service requests and AI data service requests, and select the appropriate connection service management function network element and AI data service management function network element, and send the corresponding request to the corresponding service management function network element.

[0137] Step 3: After receiving the connection service request message, the connection service management function network element controls the establishment of a PDU session connection from the UE to the network.

[0138] Step 4: After receiving the AI ​​data service request message, the AI ​​data service management function network element selects a suitable AI data service execution node according to the AI ​​data service requirements (such as the requested AI data service business type, location area, etc.).

[0139] Step 5: The AI ​​data service management function network element sends a specific AI task to the selected AI data service execution node.

[0140] Step 6: Each AI data service execution node cooperates to execute the AI ​​task.

[0141] Step 7: The AI ​​data service execution node returns the AI ​​task execution result to the UE.

[0142] The above-mentioned embodiments of the present disclosure utilize eAMF as a control node to optimize the processing flow of AI multi-factor service requests, thereby improving service efficiency and user experience. The above-mentioned embodiments of the present disclosure simplify the interaction process between user equipment and the network, reduce communication overhead, and improve efficiency through an integrated service request processing mechanism. In addition, the above-mentioned embodiments of the present disclosure provide a flexible service request processing method, which increases the flexibility and scalability of the system to adapt to different business needs and network environments. Thirdly, the above-mentioned embodiments of the present disclosure enhance the network's ability to coordinate connection services and AI data services, optimize resource allocation, and improve service response speed and quality. Finally, the above-mentioned embodiments of the present disclosure use eAMF as a control node to achieve efficient processing of AI multi-factor service requests, significantly improving user experience. The above-mentioned embodiments of the present disclosure solve the problems of poor service coordination and resource waste in related technical network systems, and provide solutions for efficient management and value-added of data services in 6G networks.

[0143] Figure 4 Schematic diagrams of some further embodiments of the multi-factor service collaborative processing method disclosed in the present invention. Figure 4 The embodiment can be executed by the multi-factor service collaborative processing system disclosed in the present invention. Figure 4 As shown, Figure 4 The method of the embodiment may include at least one of steps 40 to 49 .

[0144] In step 40, the UE sends a NAS message to the eAMF to request both the connection service and the AI ​​data service. There are two options: implementation based on the PCO field of the PDU session NAS message and implementation based on a newly added dedicated multi-factor service request NAS message. It carries both connection and data service requests, such as a PDU session establishment request for the connection service and a data service request for the AI ​​data service, including the requested AI data service service type (such as registration or session statistical analysis, AI model training, AI reasoning, etc.), the requested AI data service area, the specific QoS requirements of the requested service, etc.

[0145] Step 41, eAMF processes the multi-factor service request, including extracting the connection and AI data service request related fields from the NAS message, and disassembling them into independent connection service requests and AI data service requests. eAMF selects the appropriate CSMF and DSMF in the network based on the service area, etc.

[0146] Step 42: eAMF sends a connection service request to CSMF.

[0147] Step 43: eAMF sends an AI data service request to DSMF.

[0148] Step 44: After receiving the connection service request message, CSMF controls the establishment of a PDU session connection from the UE to the network.

[0149] Step 45: After receiving the AI ​​data service request message, the DSMF selects appropriate DPF and DSF according to the AI ​​data service requirements (such as the requested AI data service business type, area, etc.).

[0150] Step 46, the DSMF sends data collection, analysis, processing or storage tasks to the selected DPF and DSF respectively.

[0151] In step 47, DPF and DSF respectively perform data collection, analysis, processing and storage tasks.

[0152] Step 48: After the data collection, processing and data result storage tasks are completed, DSF sends a message to DSMF indicating that the AI ​​data service result has been stored, which includes the storage address of the AI ​​data service result.

[0153] Step 49: DSMF sends the storage address of the AI ​​data service result to eAMF. eAMF sends the storage address of the AI ​​data service result to the service requesting UE via a downlink NAS message.

[0154] The above embodiment of the present disclosure proposes a method for processing a multi-factor collaborative service request, which can receive a multi-factor service request including a connection service and an AI data service request sent by a user equipment (UE), and decompose it into independent connection service requests and AI data service requests. The above embodiment of the present disclosure realizes the collaborative processing of connection services and AI data services by selecting appropriate network function entities (such as CSMF and DSMF) to process these two requests respectively.

[0155] The above embodiments of the present disclosure achieve unified management and coordination of network resources by introducing network function entities such as DSMF. The DSMF of the above embodiments of the present disclosure can select appropriate DPF and DSF for data collection, analysis, processing and storage tasks according to the AI ​​data service requirements, thereby achieving dynamic allocation and optimization of network resources.

[0156] Figure 5 Schematic diagrams of some further embodiments of the multi-factor service collaborative processing method disclosed in the present invention. Figure 5 The embodiment can be executed by the multi-factor service collaborative processing system disclosed in the present invention. Figure 5 As shown, Figure 5 The method of the embodiment may include at least one of steps 50 to 60 .

[0157] In step 50, the UE sends a NAS message to the eAMF to request both the connection service and the AI ​​data service. There are two options: implementation based on the PCO field of the PDU session NAS message and implementation based on a newly added dedicated multi-factor service request NAS message. It carries both connection and data service requests, such as a PDU session establishment request for the connection service and a data service request for the AI ​​data service, including the requested AI data service business type (such as statistical analysis of registration or session, AI model training, AI reasoning, etc.), the requested AI data service area, and the specific QoS requirements of the requested service.

[0158] The above embodiments of the present disclosure provide two service request processing mechanisms, namely, implementation based on the PCO field of the PDU session NAS message and implementation based on the newly added dedicated multi-factor service request NAS message. Both mechanisms can carry connection and data service requests at the same time, and support detailed descriptions of the requested AI data service business type, region, QoS requirements and other information. This greatly improves the flexibility and accuracy of service requests.

[0159] Step 51: eAMF processes the multi-factor service request, including extracting the connection and AI data service request related fields from the NAS message to form a multi-factor service request, including the connection service request and the AI ​​data service request. eAMF selects the appropriate CSMF and DSMF in the network based on the service area, etc.

[0160] Step 52: eAMF sends a connection service and AI data service collaboration request to CSMF.

[0161] Step 53: eAMF sends a connection service and AI data service collaboration request to DSMF.

[0162] Step 54: After receiving the connection service and AI data service collaboration request message, CSMF extracts the connection service related information and controls the establishment of the PDU session connection from the UE to the network.

[0163] Step 55, after receiving the connection service and AI data service collaboration request message, DSMF extracts the relevant information of AI data service and selects appropriate DPF and DSF according to the specific requirements of the data service contained therein (such as the requested data service business type, area, etc.).

[0164] Step 56, DSMF sends data collection, analysis, processing and storage tasks to the selected DPF and DSF respectively.

[0165] In step 57, the DPF and DSF respectively perform data collection, analysis, processing and storage tasks.

[0166] Step 58: After the data collection, analysis, processing and storage tasks are completed, DSF sends a message to DSMF indicating that the AI ​​data service results have been stored, which includes the storage address of the AI ​​data service results.

[0167] Step 59: DSMF sends the storage address of the AI ​​data service result to eAMF. eAMF sends the storage address of the AI ​​data service result to the service requesting UE via a downlink NAS message.

[0168] In the above embodiments of the present disclosure, the UE sends a connection and AI data service collaborative service request to the eAMF through a NAS message. The eAMF disassembles and translates the collaborative service request into a single service request, or the CSMF and DSMF parse the collaborative service request and extract the corresponding service request information respectively. Network-related network elements such as eAMF, CSMF, and DSMF participate in the processing of multi-factor collaborative service requests, establish a connection from the UE to the network, and select a suitable AI data service execution node to issue AI tasks.

[0169] The above-mentioned embodiments of the present disclosure aim at the problem that users in the next-generation network simultaneously request connection services and AI data services, and propose a technical method and process for collaborative processing of core network connection services and AI data services, which supports the core network to simultaneously process connection and AI multi-factor service requests initiated by UE. After the network provides the connection service, it selects a suitable AI data service execution node to realize the core network's collaborative processing of connection and AI data services for UE, so as to solve the problems of poor service coordination and resource waste in the existing network system, and improve service efficiency and user experience.

[0170] Figure 6 Schematic diagram of the structure of some embodiments of the core network device disclosed in the present invention. Figure 6 As shown, the core network device of the present disclosure may include an evolved access and mobility management function network element 61 and a collaborative processing module 62 .

[0171] The evolved access and mobility management function network element 61 is configured to receive a multi-factor service request sent by a user equipment, wherein the multi-factor service request includes a connection service request and a data service request.

[0172] The collaborative processing module 62 is configured to collaboratively process the multi-factor service request.

[0173] In some embodiments of the present disclosure, the collaborative processing module 62 is configured to extract a connection service request and a data service request from the multi-factor service request; establish a connection from the user device to the network based on the connection service request; select a corresponding data service execution node based on the data service request, and issue a data service task.

[0174] In some embodiments of the present disclosure, the core network device of the present disclosure may be configured to implement the multi-factor service collaborative processing method as described in any of the above embodiments.

[0175] In some embodiments of the present disclosure, the functions of the collaborative processing module 60 may be performed by multiple network elements. Figure 7 and Figure 8 The present disclosure is further described.

[0176] Figure 7 It is a schematic diagram of the structure of other embodiments of the core network device disclosed in the present invention. Figure 8 It is a structural diagram of some other embodiments of the core network device disclosed in the present invention. Figure 7 and Figure 8 They are the service-oriented interface form and the point-to-point interface form of the network system that supports data services. Figures 3 to 5 Any embodiment also provides a structural diagram of some embodiments of the core network device of the present disclosure.

[0177] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, the core network device may include at least one of an evolved access and mobility management function network element (eAMF), a connection service management function network element (CSMF), a data service management function network element (DSMF), a data plane function network element (DPF) and a data storage function network element (DSF).

[0178] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, eAMF can be configured to enhance the coordinated processing of multiple elements of services such as data services and connection services in addition to being responsible for UE access and mobility management related signaling.

[0179] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, a connection service management function network element (CSMF) may be configured to receive connection service tasks, control the establishment, modification and release of a connection between a UE and a data network (DN), etc.

[0180] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, a connection service management function network element (CSMF) may be configured to establish a connection between the user equipment and the network according to the connection service request.

[0181] In some embodiments of the present disclosure, Figures 3 to 5, Figure 7 and Figure 8 As shown, the data service management function network element (DSMF) can be configured to select specific DPF, DSF and other NFs with different data capabilities to form an executable UE, RAN, DPF, DSF logical topology and control the work chain to implement specific data service functions. DSMF also needs to support the data service capability reporting function of DPF.

[0182] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, the data service management function network element (DSMF) may be configured to select a corresponding data service execution node according to the data service request and issue a data service task.

[0183] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 As shown, the evolved access and mobility management function network element (eAMF) can be configured to decompose the multi-factor service request into separate connection service requests and data service requests; select the corresponding connection service management function network element and data service management function network element; send the connection service request to the connection service management function network element; and send the data service request to the service management function network element.

[0184] In other embodiments of the present disclosure, Figures 3 to 5 , Figure 8 As shown, the evolved access and mobility management function network element (eAMF) can be configured to select a corresponding connection service management function network element and a data service management function network element, and send the multi-factor service request to the connection service management function network element and the service management function network element respectively; the connection service management function network element can be configured to parse the multi-factor service request and extract the connection service request; the service management function network element can be configured to parse the multi-factor service request and extract the data service request.

[0185] In some embodiments of the present disclosure, the data service is an artificial intelligence data service.

[0186] In some embodiments of the present disclosure, the multi-factor service request may be a collaborative request for a connection service and an artificial intelligence data service.

[0187] In some embodiments of the present disclosure, the connection service request may be a protocol data unit session establishment request for the connection service.

[0188] In some embodiments of the present disclosure, the data service request may be a data service request for an artificial intelligence data service.

[0189] In some embodiments of the present disclosure, the data service request may include at least one of the artificial intelligence data service business type, the requested artificial intelligence data service area, the required computing power resource type, and the service quality requirement of the requested service.

[0190] In some embodiments of the present disclosure, the artificial intelligence data service business type may include at least one of statistical analysis of registrations or sessions, artificial intelligence model training, and artificial intelligence reasoning.

[0191] In some embodiments of the present disclosure, the computing resource type may include at least one of a central processing unit, a graphics processing unit, and a storage.

[0192] In some embodiments of the present disclosure, the quality of service requirement may include training accuracy.

[0193] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, the evolved access and mobility management function network element (eAMF) can be configured to select corresponding connection service management function network elements and data service management function network elements in the network according to the service area.

[0194] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, the evolved access and mobility management function network element (eAMF) can be configured to receive a multi-factor service request sent by a user equipment based on a protocol configuration option field of a non-access layer message of a protocol data unit session; or, to receive a multi-factor service request sent by a user equipment based on a newly added non-access layer message of a dedicated multi-factor service request.

[0195] In some embodiments of the present disclosure, the data service management function network element may be an artificial intelligence service management function network element.

[0196] In some embodiments of the present disclosure, the artificial intelligence service management function network element can be configured to select a corresponding artificial intelligence service execution node based on at least one of the artificial intelligence service business type and location area requested in the artificial intelligence service request; and send an artificial intelligence task to the selected artificial intelligence service execution node.

[0197] In some embodiments of the present disclosure, the core network device may further include an artificial intelligence service execution node.

[0198] In some embodiments of the present disclosure, the artificial intelligence service execution node may be configured to cooperatively execute the artificial intelligence task; and return the artificial intelligence task execution result to the user device.

[0199] In some embodiments of the present disclosure, the artificial intelligence service execution node may include a data plane function network element and a data storage function network element.

[0200] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, DPF can be configured to realize functions such as data collection, transmission, preprocessing, and analysis.

[0201] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, DSF can be configured to store collected data and data service results, etc.

[0202] In some embodiments of the present disclosure, the artificial intelligence task includes at least one of a data collection task, a data analysis task, a data processing task, and a data storage task.

[0203] In some embodiments of the present disclosure, the data storage functional network element may be configured to send a stored message of the artificial intelligence data service result to the data service management functional network element, wherein the stored message includes the storage address of the artificial intelligence data service result; the data service management functional network element may be configured to send the storage address of the artificial intelligence data service result to the evolved access and mobility management functional network element; the evolved access and mobility management functional network element may be configured to send the storage address of the artificial intelligence data service result to the user device.

[0204] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, the core network device of the present disclosure may also include at least one network element of SEF (Service Exposure Function), UPF (User plane Function), DN (Data Network), AF (Application Function), control plane NF (Network Function) and eNRF (evolved NF Repository Function).

[0205] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, SEF can be configured to open up 6G network services to the outside world.

[0206] In some embodiments of the present disclosure, Figures 3 to 5 , Figure 7 and Figure 8 As shown, SEF can be configured to provide open core network services to the outside world.

[0207] In some embodiments of the present disclosure, Figure 8 As shown, the core network device of the present disclosure may further include a DC (Data Collection, data collection unit), a DS (Data Storage, data storage unit) and a DP (Data Plane, data plane unit).

[0208] In some embodiments of the present disclosure, Figure 8 As shown, DC is set at UE, RAN, UPF, DPF and DSF; DS is set at DSF; DP is set at DPF.

[0209] In some embodiments of the present disclosure, Figure 8 As shown, DC can be configured to obtain data from data sources, including user data, network data, AI data, perception data, etc.

[0210] In some embodiments of the present disclosure, Figure 8 As shown, the DS can be configured to store collected data and data service results, etc.

[0211] In some embodiments of the present disclosure, Figure 8 As shown, DP can be configured to perform data preprocessing, analysis, etc.

[0212] The core network device of the above-mentioned embodiment of the present disclosure has the ability to decompose and select network elements such as CSMF and DSMF according to relevant connection or data service tasks.

[0213] The core network device of the above-mentioned embodiment of the present disclosure has the ability to select a DSMF network element according to an AI data service request.

[0214] The core network device of the above-mentioned embodiment of the present disclosure has the ability to process connection and data service requests separately at the same time, decompose related tasks based on eAMF, and perform collaborative processing by different network units.

[0215] The core network device of the above-mentioned embodiment of the present disclosure has the ability to support detailed description of information such as the requested AI data service business type, area, and QoS requirements.

[0216] The core network device of the above-mentioned embodiment of the present disclosure has the ability to transfer and disassemble service request information and select corresponding network elements for processing.

[0217] The core network device of the above-mentioned embodiment of the present disclosure can implement two mechanisms of simultaneously carrying connection and data service requests based on the PCO field of the PDU session NAS message and based on the newly added dedicated multi-factor service request NAS message, and perform two types of AI multi-factor service request processing based on eAMF as the control node.

[0218] Fig. 9 FIG. 1 is a schematic diagram of the structure of some other embodiments of the core network device disclosed in the present invention. Fig. 9 As shown, the core network device of the present disclosure may include a memory 91 and a processor 92 .

[0219] The memory 91 is used to store instructions. The processor 92 is coupled to the memory 91. The processor 92 is configured to execute and implement any of the above embodiments based on the instructions stored in the memory (for example: Figure 1 Example Figure 3 Steps 2-7 in the embodiment, Figure 4 Steps 41-49 of the embodiment Figure 5 Steps 51-59 of the embodiment involve a multi-factor service collaborative processing method.

[0220] like Fig. 9 As shown, the core network device also includes a communication interface 93 for information exchange with other devices. At the same time, the core network device also includes a bus 94, through which the processor 92, the communication interface 93, and the memory 91 communicate with each other.

[0221] The memory 91 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory. The memory 91 may also be a memory array. The memory 91 may also be divided into blocks, and the blocks may be combined into virtual volumes according to certain rules.

[0222] In addition, the processor 92 may be a central processing unit (CPU), or may be an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present disclosure.

[0223] Fig.10 The present invention is a schematic diagram of the structure of some embodiments of the user equipment disclosed herein. Fig.10 User equipment of an embodiment and Fig. 9 The structure and function of the core network device of the embodiment are the same or similar. Fig.10 User equipment of an embodiment and Fig. 9 The core network devices of the embodiments are different only in that: Fig.10 The processor 92 in the embodiment is configured to execute any of the above embodiments based on the instructions stored in the memory (for example: Figure 2 Example Figure 3 Step 1 in the embodiment, Figure 4 Step 40 of the embodiment, Figure 5 Step 50 of the embodiment involves a multi-factor service collaborative processing method.

[0224] Fig.11 Schematic diagram of the structure of some embodiments of the multi-factor service collaborative processing system disclosed in the present invention. Fig.11 As shown, the multi-factor service collaborative processing system disclosed in the present invention may include a core network device 300 and a user device 400 .

[0225] In some embodiments of the present disclosure, the core network device 300 may be implemented as a core network device as described in any of the above embodiments.

[0226] In some embodiments of the present disclosure, a user equipment (UE) 400 may be implemented as a user equipment as described in any of the above embodiments.

[0227] Figures 3 to 5 , Figures 7 and 8 Any embodiment also provides a schematic diagram of the structure of some embodiments of the multi-factor service collaborative processing system disclosed in the present invention. Figures 3 to 5 , Figures 7 and 8 , Fig.11 As shown, the multi-factor service collaborative processing system of the present disclosure may further include a RAN (Radio Access Network) 500 .

[0228] In some embodiments of the present disclosure, RAN may be used to provide services such as wireless access control and data transmission for user equipment in a specific area, and support wireless perception of a specific area or target and acquisition of perception measurement data.

[0229] The above embodiments of the present disclosure propose a multi-factor collaborative service processing method and system, which can process connection service and AI data service requests at the same time. The above embodiments of the present disclosure introduce eAMF (enhanced access and mobility management function) as the core control node to achieve collaborative processing of connection services and AI data services. The eAMF of the above embodiments of the present disclosure can decompose collaborative service requests into independent connection service requests and AI data service requests, and send them to corresponding network function entities for processing respectively.

[0230] The above-mentioned embodiments of the present disclosure introduce CSMF and DSMF to manage connection services and AI data services respectively, and can parse collaborative service requests, extract connection service request information or AI data service request information therefrom, and execute corresponding service tasks respectively.

[0231] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the multi-factor service collaborative processing method as described in any of the above embodiments is implemented.

[0232] According to another aspect of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the multi-factor service collaborative processing method as described in any of the above embodiments is implemented.

[0233] The computer-readable storage medium of the present disclosure may be implemented as a non-transitory computer-readable storage medium.

[0234] The above embodiments of the present disclosure belong to the technical field of wireless communications, terminals, and core networks.

[0235] The above embodiments of the present disclosure may be used in the B5G network, which is an evolved version of the 5G network.

[0236] The above embodiments of the present disclosure may be used in future 6G networks, and the systems and methods of the above embodiments of the present disclosure may provide data services for perception and AI scenarios.

[0237] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, devices, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable non-transient storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0238] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0239] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0240] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0241] The core network equipment, user equipment, evolved access and mobility management function network element, collaborative processing module, connection service management function network element, data service management function network element, data plane function network element, data storage function network element, service exposure function network element, user plane function network element, data network, application function network element, control plane network function network element, evolved network storage function network element, data acquisition unit, data storage unit and data plane unit described above can be implemented as a general-purpose processor, programmable logic controller, digital signal processor (DSP), application-specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component or any appropriate combination thereof for performing the functions described in the present disclosure.

[0242] Those skilled in the art will appreciate that all or part of the steps of the above-described embodiment method of the present disclosure may be accomplished by hardware, and the hardware may be implemented as a general-purpose processor, a programmable logic controller, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, or any appropriate combination thereof for executing the method described in the present disclosure.

[0243] So far, the present disclosure has been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Based on the above description, those skilled in the art can fully understand how to implement the technical solution disclosed here.

[0244] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or may be accomplished by instructing the relevant hardware through a program, and the program may be stored in a non-transitory computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0245] The description of the present disclosure is given for the purpose of illustration and description, and is not intended to be exhaustive or to limit the present disclosure to the disclosed form. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present disclosure, and to enable those of ordinary skill in the art to understand the present disclosure and thereby design various embodiments with various modifications suitable for specific uses.

Claims

1. A multi-factor service collaborative processing method, executed by a core network device, comprising: Receiving a multi-factor service request sent by a user equipment, wherein the multi-factor service request includes a connection service request and a data service request; The multi-factor service request is collaboratively processed.

2. The multi-factor service collaborative processing method according to claim 1, wherein: The collaborative processing of the multi-factor service request includes: Extracting a connection service request and a data service request from the multi-element service request; Establishing a connection between the user equipment and the network according to the connection service request; According to the data service request, a corresponding data service execution node is selected and a data service task is issued.

3. The multi-factor service collaborative processing method according to claim 2, wherein: The core network device includes at least one of an evolved access and mobility management function network element, a connection service management function network element, and a data service management function network element; Wherein, the step of establishing a connection between the user equipment and the network according to the connection service request is performed by the connection service management function network element; The step of selecting a corresponding data service execution node according to the data service request and issuing a data service task is performed by the data service management function network element.

4. The multi-factor service collaborative processing method according to claim 3, wherein: The extracting the connection service request and the data service request from the multi-factor service request comprises: The evolved access and mobility management function network element decomposes the multi-factor service request into separate connection service requests and data service requests; The evolved access and mobility management function network element selects the corresponding connection service management function network element and data service management function network element; The evolved access and mobility management function network element sends the connection service request to the connection service management function network element; The evolved access and mobility management function network element sends the data service request to the service management function network element.

5. The multi-factor service collaborative processing method according to claim 3, wherein: The extracting the connection service request and the data service request from the multi-factor service request comprises: The evolved access and mobility management function network element selects the corresponding connection service management function network element and data service management function network element; The evolved access and mobility management function network element sends the multi-factor service request to the connection service management function network element and the service management function network element respectively; The connection service management function network element parses the multi-factor service request and extracts the connection service request; The service management function network element parses the multi-factor service request and extracts the data service request.

6. The multi-factor service collaborative processing method according to claim 4 or 5, wherein: The evolved access and mobility management function network element selects the corresponding connection service management function network element and data service management function network element, including: The evolved access and mobility management function network element selects a corresponding connection service management function network element and a data service management function network element in the network according to the service area.

7. The multi-factor service collaborative processing method according to any one of claims 3 to 5, wherein: The data service is an artificial intelligence data service, and the data service management function network element is an artificial intelligence service management function network element; The selecting, according to the data service request, a corresponding data service execution node and issuing a data service task comprises: the artificial intelligence service management function network element selecting, according to at least one of the artificial intelligence service business type and location area requested in the artificial intelligence service request, a corresponding artificial intelligence service execution node; The artificial intelligence service management function network element sends the artificial intelligence task to the selected artificial intelligence service execution node.

8. The multi-factor service collaborative processing method according to claim 7, wherein: The core network device also includes an artificial intelligence service execution node; The selecting a corresponding data service execution node according to the data service request and issuing the data service task further comprises: The artificial intelligence service execution nodes cooperate to execute the artificial intelligence tasks; The artificial intelligence service execution node returns the artificial intelligence task execution result to the user device.

9. The multi-factor service collaborative processing method according to claim 8, wherein: The artificial intelligence service execution node includes a data plane functional network element and a data storage functional network element; The artificial intelligence task includes at least one of a data collection task, a data analysis task, a data processing task, and a data storage task; The artificial intelligence service execution node returns the artificial intelligence task execution result to the user equipment, including: the data storage function network element sends a stored message of the artificial intelligence data service result to the data service management function network element, wherein the stored message includes the storage address of the artificial intelligence data service result; the data service management function network element sends the storage address of the artificial intelligence data service result to the evolved access and mobility management function network element; the evolved access and mobility management function network element sends the storage address of the artificial intelligence data service result to the user equipment.

10. The multi-factor service collaborative processing method according to any one of claims 1 to 5, wherein: The receiving a multi-factor service request sent by a user equipment includes: receiving a multi-factor service request sent by a user equipment based on a protocol configuration option field of a non-access stratum message of a protocol data unit session; or, Based on the newly added non-access layer message of the dedicated multi-factor service request, a multi-factor service request sent by the user equipment is received.

11. The multi-factor service collaborative processing method according to any one of claims 1 to 5, wherein: The data service is an artificial intelligence data service; The multi-factor service request is a connection service and an artificial intelligence data service collaborative request; The connection service request is a protocol data unit session establishment request for the connection service; The data service request is a data service request for artificial intelligence data services.

12. The multi-factor service collaborative processing method according to claim 11, wherein: The data service request includes at least one of an artificial intelligence data service business type, a requested artificial intelligence data service area, a required computing resource type, and a service quality requirement of the requested service.

13. The multi-factor service collaborative processing method according to claim 12, wherein: The artificial intelligence data service business type includes at least one of statistical analysis of registrations or sessions, artificial intelligence model training, and artificial intelligence reasoning; The computing resource type includes at least one of a central processing unit, a graphics processing unit, and a storage; The quality of service requirements include training accuracy.

14. A multi-factor service collaborative processing method, executed by a user device, comprising: A multi-factor service request is sent to a core network device, wherein the multi-factor service request includes a connection service request and a data service request, and the core network device is used to collaboratively process the multi-factor service request.

15. A core network device, comprising: An evolved access and mobility management function network element is configured to receive a multi-factor service request sent by a user equipment, wherein the multi-factor service request includes a connection service request and a data service request; The collaborative processing module is configured to collaboratively process the multi-factor service request.

16. A core network device, comprising: a memory configured to store instructions; and The processor is configured to execute the instructions so that the core network device implements the multi-factor service collaborative processing method as described in any one of claims 1-13.

17. A user equipment, comprising: a memory configured to store instructions; and The processor is configured to execute the instructions so that the user equipment implements the multi-factor service collaborative processing method as described in claim 14.

18. A multi-factor service collaborative processing system, comprising the core network device as claimed in claim 15 or 16, and the user equipment as claimed in claim 17.

19. A computer-readable storage medium, wherein: The computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the multi-factor service collaborative processing method as described in any one of claims 1 to 14 is implemented.

20. A computer program product comprising a computer program, wherein: When the computer program is executed by a processor, the multi-factor service collaborative processing method as described in any one of claims 1 to 14 is implemented.

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