Business processing method and device, communication equipment and readable storage medium

Abstract

The invention discloses a service processing method and device, communication equipment and a readable storage medium, and belongs to the technical field of communication, and the service processing method comprises the steps that a first network element receives a first message sent by a second network element, the first message is used for requesting to establish an artificial intelligence (AI) service for the second network element, and the AI service is sent to the second network element; the AI service is a verification service; sending a second message to the second network element, wherein the second message is used for responding to the first message; the first network element is a core network element, and the second network element is a third-party server.

Description

Technical Field

[0001] The present application belongs to the field of communication technology, and specifically relates to a service processing method, apparatus, communication equipment and readable storage medium. Background Art

[0002] With the development of wireless mobile communication technology, artificial intelligence (AI) will become one of the pillar technologies of communication systems, and communication systems will provide end-to-end support for AI-related services and applications. In related technologies, communication systems can use AI to perform some operation optimizations, but AI is not provided as a general service to third-party servers, nor is AI business services implemented according to the needs or purposes of third-party servers. Third-party servers are an important supplement to communication systems. In this case, how to implement the AI ​​business service process based on third-party servers is an urgent problem to be solved. Summary of the invention

[0003] The embodiments of the present application provide a business processing method, apparatus, communication equipment and readable storage medium, which can solve the problem of how to implement an AI business service process based on a third-party server.

[0004] In a first aspect, a service processing method is provided, which is performed by a first network element, and the method includes:

[0005] The first network element receives a first message sent by the second network element, wherein the first message is used to request to establish an artificial intelligence AI service for the second network element, and the AI ​​service is a verification service;

[0006] The first network element sends a second message to the second network element, where the second message is used to respond to the first message; the first network element is a core network element, and the second network element is a third-party server.

[0007] In a second aspect, a service processing method is provided, which is performed by a second network element, and the method includes:

[0008] The second network element sends a first message to the first network element, wherein the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service;

[0009] The second network element receives a second message sent by the first network element, where the second message is used to respond to the first message; the first network element is a core network element, and the second network element is a third-party server.

[0010] According to a third aspect, a service processing method is provided, which is executed by a third network element, and the method includes:

[0011] The third network element sends a fourth message to the sixth network element, wherein the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service;

[0012] The third network element receives a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0013] In a fourth aspect, a service processing method is provided, which is executed by a fourth network element, and the method includes:

[0014] The fourth network element receives first data sent by the second network element, where the first data includes input data of the AI ​​unit;

[0015] The fourth network element performs AI unit processing according to the first data;

[0016] The fourth network element sends second data to the second network element, where the second data includes an output result of the AI ​​unit.

[0017] In a fifth aspect, a service processing method is provided, which is executed by a sixth network element, and the method includes:

[0018] The sixth network element receives a fourth message sent by the third network element, wherein the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service;

[0019] The sixth network element sends a response message of the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0020] In a sixth aspect, a service processing device is provided, which is applied to a first network element, including:

[0021] A first receiving module, configured to receive a first message sent by a second network element, wherein the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service;

[0022] The first sending module is used to send a second message to the second network element, wherein the second message is used to respond to the first message.

[0023] In a seventh aspect, a service processing device is provided, which is applied to a second network element, including:

[0024] A third sending module is used to send a first message to the first network element, wherein the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service;

[0025] The second receiving module is used to receive a second message sent by the first network element, wherein the second message is used to respond to the first message.

[0026] In an eighth aspect, a service processing device is provided, which is applied to a third network element, including:

[0027] a sixth sending module, configured to send a fourth message to a sixth network element, wherein the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service;

[0028] The fourth receiving module is used to receive a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0029] In a ninth aspect, a service processing device is provided, which is applied to a fourth network element, including:

[0030] A sixth receiving module, configured to receive first data sent by a second network element, where the first data includes input data of an AI unit;

[0031] A processing module, configured to perform AI unit processing according to the first data;

[0032] A ninth sending module is used to send second data to the second network element, where the second data includes the output result of the AI ​​unit.

[0033] In a tenth aspect, a service processing device is provided, which is applied to a sixth network element, including:

[0034] an eighth receiving module, configured to receive a fourth message sent by a third network element, wherein the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service;

[0035] A tenth sending module is used to send a response message of the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0036] In the eleventh aspect, a communication device is provided, which network side device includes a processor and a memory, the memory storing a program or instruction that can be run on the processor, and the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect, or implements the steps of the method described in the second aspect, or implements the steps of the method described in the third aspect, or implements the steps of the method described in the fourth aspect, or implements the steps of the method described in the fifth aspect.

[0037] In the twelfth aspect, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented, or the steps of the method described in the second aspect are implemented, or the steps of the method described in the third aspect are implemented, or the steps of the method described in the fourth aspect are implemented, or the steps of the method described in the fifth aspect are implemented.

[0038] In the thirteenth aspect, a wireless communication system is provided, including: a first network element, a second network element, a third network element, a fourth network element and a sixth network element, wherein the first network element can be used to execute the steps of the method described in the first aspect, the second network element can be used to execute the steps of the method described in the second aspect, the third network element can be used to execute the steps of the method described in the third aspect, the fourth network element can be used to execute the steps of the method described in the fourth aspect, and the sixth network element can be used to execute the steps of the method described in the fifth aspect.

[0039] In the fourteenth aspect, a chip is provided, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instructions to implement the steps of the method described in the first aspect, or the steps of the method described in the second aspect, or the steps of the method described in the third aspect, or the steps of the method described in the fourth aspect, or the steps of the method described in the fifth aspect.

[0040] In the fifteenth aspect, a computer program / program product is provided, which is stored in a storage medium, and the program / program product is executed by at least one processor to implement the steps of the method described in the first aspect, or the steps of the method described in the second aspect, or the steps of the method described in the third aspect, or the steps of the method described in the fourth aspect, or the steps of the method described in the fifth aspect.

[0041] In a sixteenth aspect, a communication system is provided, including: a first network element, a second network element, a third network element, a fourth network element, and a sixth network element, wherein:

[0042] The first network element is used to: receive a first message sent by the second network element, the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service; send a second message to the second network element, and the second message is used to respond to the first message;

[0043] The second network element is used to: send a first message to the first network element, where the first message is used to request to establish an AI service for the second network element; and receive a second message sent by the first network element, where the second message is used to respond to the first message;

[0044] The third network element is used to: send a fourth message to the sixth network element, where the fourth message is used to request an AI unit required for the AI ​​service, and receive a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service;

[0045] The fourth network element is configured to: receive first data sent by the second network element, the first data including input data of the AI ​​unit; perform AI unit processing according to the first data; and send second data to the second network element, the second data including output results of the AI ​​unit;

[0046] The sixth network element is used to: receive a fourth message sent by the third network element, where the fourth message is used to request the AI ​​unit required for the AI ​​service; and send a response message to the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0047] In an embodiment of the present application, a first network element may receive a first message sent by a second network element, the first message being used to request the establishment of an AI service for the second network element, the AI ​​service being a verification service, and return a response message of the first message to the second network element, the second network element being a third-party server. Thus, the establishment of an AI verification service may be initiated according to the needs and purposes of a third-party server (such as an OTT server), thereby realizing the AI ​​service service process. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a block diagram of a wireless communication system to which the embodiments of the present application can be applied;

[0049] Figure 2 It is a flow chart of a business processing method provided by an embodiment of the present application;

[0050] Figure 3 is a flow chart of another business processing method provided by an embodiment of the present application;

[0051] Figure 4 is a flow chart of another business processing method provided by an embodiment of the present application;

[0052] Figure 5 is a flow chart of another business processing method provided by an embodiment of the present application;

[0053] Figure 6 is a flow chart of another business processing method provided by an embodiment of the present application;

[0054] Figure 7 This is one of the flowcharts of the AI ​​business service process in Example 1 of the present application;

[0055] Figure 8 This is one of the flow charts of the AI ​​business service process in Example 2 of the present application;

[0056] Fig. 9 It is a structural diagram of a service processing device provided in an embodiment of the present application;

[0057] Fig.10 is a structural diagram of another service processing device provided in an embodiment of the present application;

[0058] Fig.11 is a structural diagram of another service processing device provided in an embodiment of the present application;

[0059] Fig.12 is a structural diagram of another service processing device provided in an embodiment of the present application;

[0060] Fig.13 is a structural diagram of another service processing device provided in an embodiment of the present application;

[0061] Fig.14 It is a structural diagram of a communication device provided in an embodiment of the present application;

[0062] Fig.15 It is a structural diagram of a network side device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of this application.

[0064] The terms "first", "second", etc. in this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of one type, and the number of objects is not limited, for example, the first object can be one or more. In addition, "or" in this application represents at least one of the connected objects. For example, "A or B" covers three schemes, namely, Scheme 1: including A but not including B; Scheme 2: including B but not including A; Scheme 3: including both A and B. The character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0065] The term "indication" in this application can be a direct indication (or explicit indication) or an indirect indication (or implicit indication). A direct indication can be understood as the sender explicitly informing the receiver of specific information, operations to be performed, or request results in the sent indication; an indirect indication can be understood as the receiver determining the corresponding information according to the indication sent by the sender, or making a judgment and determining the operation to be performed or the request result according to the judgment result.

[0066] It is worth noting that the technology described in the embodiments of the present application is not limited to the Long Term Evolution (LTE) / LTE-Advanced (LTE-A) system, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency-Division Multiple Access (SC-FDMA) or other systems. The terms "system" and "network" in the embodiments of the present application are often used interchangeably, and the described technology can be used for the systems and radio technologies mentioned above as well as for other systems and radio technologies. The following description describes a New Radio (NR) system for illustrative purposes, and NR terminology is used in most of the following descriptions, but these technologies can also be applied to systems other than NR systems, such as the 6th generation (6 th Generation, 6G) communication system.

[0067] Figure 1A block diagram of a wireless communication system applicable to an embodiment of the present application is shown. The wireless communication system includes a terminal 11 and a network side device 12. Among them, the terminal 11 can be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), a notebook computer, a personal digital assistant (Personal Digital Assistant, PDA), a handheld computer, a netbook, an ultra-mobile personal computer (Ultra-mobile Personal Computer, UMPC), a mobile Internet device (Mobile Internet Device, MID), an augmented reality (Augmented Reality, AR), a virtual reality (Virtual Reality, VR) device, a robot, a wearable device (Wearable Device), an aircraft (flight vehicle), a vehicle-mounted device (Vehicle User Equipment, VUE), a ship-mounted device, a pedestrian terminal (Pedestrian User Equipment, PUE), a smart home (home appliances with wireless communication functions, such as refrigerators, televisions, washing machines or furniture, etc.), a game console, a personal computer (Personal Computer, PC), a teller machine or a self-service machine and other terminal side devices. Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. Among them, the vehicle-mounted device can also be called a vehicle-mounted terminal, a vehicle-mounted controller, a vehicle-mounted module, a vehicle-mounted component, a vehicle-mounted chip or a vehicle-mounted unit, etc. It should be noted that the specific type of the terminal 11 is not limited in the embodiment of the present application. The network side device 12 may include an access network device or a core network device, wherein the access network device may also be referred to as a radio access network (Radio Access Network, RAN) device, a radio access network function or a radio access network unit. The access network device may include a base station, a wireless local area network (Wireless Local Area Network, WLAN) access point (Access Point, AP) or a wireless fidelity (Wireless Fidelity, WiFi) node, etc.Among them, the base station may be referred to as a Node B (NB), an evolved Node B (eNB), a next generation Node B (gNB), a New Radio Node B (NR Node B), an access point, a Relay Base Station (RBS), a Serving Base Station (SBS), a Base Transceiver Station (BTS), a radio base station, a radio transceiver, a Basic Service Set (BSS), an Extended Service Set (ESS), a Home Node B (HNB), a Home Evolved Node B (home evolved Node B), a Transmission Reception Point (TRP) or other appropriate terms in the relevant field. As long as the same technical effect is achieved, the base station is not limited to specific technical vocabulary. It should be noted that in the embodiment of the present application, only the base station in the NR system is used as an example for introduction, and the specific type of the base station is not limited.

[0068] The core network equipment may include but is not limited to at least one of the following: core network node, core network function, network data analysis function (Network Data Analytics Function, NWDAF), mobility management entity (Mobility Management Entity, MME), access mobility management function (Access and Mobility Management Function, AMF), session management function (Session Management Function, SMF), user plane function (UserPlane Function, UPF), policy control function (Policy Control Function, PCF), policy and charging rules function unit (Policy and Charging Rules Function, PCRF), edge application service discovery function (Edge Application Server Discovery Function, EASDF), unified data management (Unified Data Management, UDM), unified data storage (Unified Data Repository, UDR), home subscriber server (Home Subscriber Server, HSS), centralized network configuration (CNC), network storage function (Network Repository Function, NRF), network exposure function (Network Exposure Function, NEF), local NEF (Local NEF, or L-NEF), Binding Support Function (BSF), Application Function (AF), AI business management function, collaborative control function, business analysis function, business management function, collaborative control function, AI resource node, computing power execution node, computing power execution function, computing power execution plane, AI model management function, AI model control function, AI algorithm control function, algorithm control function, AI resource management function, computing power control function, computing power control plane, etc.

[0069] In the embodiments of the present application, the AI ​​unit may also be referred to as one of the following: model, AI model, ML (machine learning) model, ML unit, AI structure, AI function, AI characteristics, machine learning model, neural network, neural network function, neural network function, etc.

[0070] Optionally, the AI ​​unit / AI model may refer to a processing unit that can implement specific AI-related algorithms, formulas, processing flows, capabilities, etc., or it may be a processing method, algorithm, function, module or unit for a specific data set, or it may be a processing method, algorithm, function, module or unit running on AI / ML related hardware such as a graphics processor (GPU), a neural processing unit (NPU), a tensor processing unit (TPU), an application specific integrated circuit (ASIC), etc. This application does not make any specific limitations on this.

[0071] Optionally, the particular data set may include inputs and / or outputs of the AI ​​unit / AI model.

[0072] Optionally, the identifier of the AI ​​unit may include at least one of the following: an AI model identifier, an AI structure identifier, an AI algorithm identifier, an identifier of a specific data set associated with the AI ​​unit, an identifier of a specific scenario, environment, channel feature or device related to AI / ML, an identifier of a function, feature, capability or module related to AI / ML, etc. This application does not make any specific limitations on this.

[0073] In the embodiment of the present application, the third network element is used to coordinate various elements, and the first network element converts external demand into internal demand. The seventh network element is used for the selection and allocation of AI resource nodes, etc. The sixth network element is used for AI model management, model ID allocation, model acquisition, etc. The data plane management function is used for the selection and allocation of data resource nodes.

[0074] In the embodiment of the present application, for the definitions / examples of different network elements, please refer to the following Table 1:

[0075] Table 1

[0076]

[0077] Optionally, each network element supports a service-oriented interface based on a service-based architecture (SBA) or an SBA-enhanced architecture, that is, messages exchanged between network elements can be implemented through a service-oriented interface protocol.

[0078] The following, in conjunction with the accompanying drawings, describes in detail the business processing method, apparatus, communication device, and readable storage medium provided in the embodiments of the present application through some embodiments and their application scenarios.

[0079] See also Figure 2 , Figure 2 is a flow chart of a service processing method provided in an embodiment of the present application, the method is executed by a first network element, such as Figure 2 As shown, the method comprises the following steps:

[0080] Step 21: The first network element receives a first message sent by the second network element, where the first message is used to request to establish an AI service for the second network element, where the AI ​​service is a verification service.

[0081] Step 22: The first network element sends a second message to the second network element, where the second message is used to respond to the first message.

[0082] In this embodiment, the first network element is a core network element, and the second network element is a third-party server. The first network element can be understood as a central control node, which can be selected as but not limited to a policy and charging function PCF, an AI service management function, an external service management function, a service management function, a collaborative control function or a computing power service management function. The policy and charging function PCF is mainly used for application and service data flow detection, policy (such as UE policy, session policy, etc.) generation and provision, etc. The AI ​​service management function is mainly used for service management and service identity resolution, specifically, to coordinate different element control functions, such as AI resource management function, AI model management function and data management function; when the AI ​​service management function is used as a central control node, it will work with the policy and charging function to convert external AI service requests into AI policy functions that can be understood internally.

[0083] The second network element may be a third-party server such as an OTT server, whose content or service is built on the basic telecommunication service. The AI ​​service may be a verification service, a reasoning service, a training service, etc.

[0084] Therefore, the establishment of AI verification service can be initiated according to the needs and purposes of the third-party server (such as OTT server), thereby realizing the AI ​​service process.

[0085] Optionally, the first message may include at least one of the following:

[0086] The identifier of the AI ​​unit used for the verification service; for example, when the AI ​​service is AI unit verification / AI model verification, the identifier of the AI ​​unit is the identifier of the AI ​​unit to be verified;

[0087] The type of service used for the verification business; for example, environmental reconstruction, facial recognition, etc.;

[0088] A first indication indicating the format of input or output data of the AI ​​unit used for the verification service;

[0089] A second indication indicating a performance verification method of the AI ​​unit used for the verification service; for example, if this indication is in a default state, it indicates that the performance verification method of the AI ​​unit is specified by the network;

[0090] A third indication indicating a reporting format of the verification result of the verification service; for example, if this indication is in a default state, it indicates that the reporting format of the verification result is specified by the network;

[0091] Classification of verification objects used for the verification service; for example, the verification object may include a private AI unit provided by the second network element, a private AI unit of the second network element in the network, a private AI unit of multiple second network elements under contract, or a shareable AI unit, etc. Verification of different types of AI units affects the verification charging strategy; if it is private model verification, the charge is lower;

[0092] A fourth indication, indicating a privacy mode of the AI ​​unit provided by the second network element; for example, the privacy mode may include a container mode, a hardware privacy security mode, etc.;

[0093] Description information of the AI ​​unit used for the verification service provided by the second network element;

[0094] Demand information for AI services; for example, this demand information can be understood as target information, which may include but is not limited to AI service processing latency, AI service processing accuracy, AI service computing volume, data processing scale, data storage requirements, expected application scope, etc.;

[0095] Quality of Experience (QoE) requirements for AI services.

[0096] Optionally, the first message may further include at least one of the following:

[0097] AI business logo;

[0098] AI unit related parameters, such as whether the network internal AI unit indication is required, AI unit identification, etc.

[0099] An indication of whether network internal data and the source of the data are required.

[0100] In this embodiment, the first message may be an AI service establishment request message, etc.

[0101] In this embodiment, in addition to the above information, the first message may also include a data network name (Data Network Name, DNN), single network slice selection assistance information (Single Network SliceSelection Assistance information, S-NSSAI), etc.

[0102] Optionally, the second message may be used to notify the result of the AI ​​service establishment request, including at least one of the following:

[0103] Relevant information of the AI ​​resource node used to perform the verification service; for example, the relevant information is a node identifier used to identify the AI ​​resource node;

[0104] A fifth indication, wherein the fifth indication is used to indicate a verification indicator of the AI ​​service, or to indicate that the verification indicator of the AI ​​service is determined by the second network element; for example, the fifth indication may explicitly indicate the verification indicator of the AI ​​service, or to indicate that the verification indicator of the AI ​​service is determined by the OTT server;

[0105] Verification indicator thresholds for AI services;

[0106] Parameter items that need to be reported in the verification results of the verification service; for example, the reported parameter items may include but are not limited to at least one of the following items of the AI ​​unit: accuracy, recall, normalized mean square error, normalized root mean square error, error level, accuracy level, recall level, etc.

[0107] Here, the AI ​​resource node may also be referred to as a resource node, a computing power resource node, a business resource node, a computing power execution node, a computing power execution plane, etc., and is used for business processing and implementation of business policy rules, etc.; specifically, the AI ​​business may be computed and processed according to the command of the seventh network element, such as execution on the user plane, or AI resource status may be updated to the seventh network element, etc.

[0108] In this embodiment, the second message may be an AI service establishment request response message, that is, a response message to the above-mentioned AI service establishment request message.

[0109] Optionally, the service processing method further includes:

[0110] The first network element sends a third message to the third network element, where the third message is used to request allocation of AI resources or required AI units for the AI ​​service.

[0111] Here, the third network element may be selected as an AI service management function, an external service management function, a collaborative control function, a service management function, a computing power service management function or other network functions that can realize similar functions, and is used for service management and service identification resolution, etc.; specifically, it coordinates different element control functions, such as AI resource management function, AI model management function and data management function; when the AI ​​service management function acts as a central control node, it will work together with the policy billing function to convert external AI service requests into AI policy functions that can be understood internally.

[0112] Optionally, the third message may include at least one of the following: an identifier of the second network element (such as an OTT server identifier), an AI service identifier, AI unit-related parameters, an AI strategy, an application server AS address, etc.

[0113] In this embodiment, the third message may be an AI service establishment request message, such as a message sent by a policy charging function PCF to an AI service management function.

[0114] In this embodiment, the first network element and the third network element may be the same network element or jointly set up. When the first network element and the third network element are the same network element or jointly set up, the third message is implemented inside the network element. For example, in this embodiment, the first network element is a policy charging function, and the third network element is an AI service management function. The policy charging function and the AI ​​service management function may be the same network element or jointly set up.

[0115] See also Figure 3 , Figure 3 is a flow chart of a service processing method provided in an embodiment of the present application, the method is executed by the second network element, such as Figure 3 As shown, the method comprises the following steps:

[0116] Step 31: The second network element sends a first message to the first network element, where the first message is used to request to establish an AI service for the second network element, where the AI ​​service is a verification service.

[0117] Step 32: The second network element receives a second message sent by the first network element, where the second message is used to respond to the first message.

[0118] In this embodiment, the first network element is a core network element, and the second network element is a third-party server. The first network element can be understood as a central control node, which can be selected as but not limited to a policy charging function, an AI service management function, an external service management function, a service management function, a collaborative control function, or a computing power service management function. The second network element can be selected as a third-party server such as an OTT server, whose content or service is built on basic telecommunications services. Thus, the second network element (such as an OTT server) can initiate the establishment of an AI service, thereby realizing the AI ​​service service process.

[0119] Optionally, the first message includes at least one of the following:

[0120] The identification of the AI ​​unit used for the verification service;

[0121] The type of service used for the verification business; for example, environmental reconstruction, facial recognition, etc.;

[0122] A first indication indicating the format of input or output data of the AI ​​unit used for the verification service;

[0123] A second indication indicating a performance verification method of the AI ​​unit used for the verification service; for example, if this indication is in a default state, it indicates that the performance verification method of the AI ​​unit is specified by the network;

[0124] A third indication indicating a reporting format of the verification result of the verification service; for example, if this indication is in a default state, it indicates that the reporting format of the verification result is specified by the network;

[0125] Classification of verification objects of the verification service; for example, the verification object may include a private AI unit provided by the second network element, a private AI unit of the second network element in the network, a private AI unit of multiple second network elements contracted, or a shareable AI unit, etc. Verification of different types of AI units affects the verification charging strategy; if it is private model verification, the charge is lower;

[0126] A fourth indication, indicating a privacy mode of the AI ​​unit for the authentication service provided by the second network element; for example, the privacy mode may include a container mode, a hardware privacy security mode, etc.;

[0127] Description information of the AI ​​unit used for the verification service provided by the second network element;

[0128] Demand information for AI services; for example, this demand information can be understood as target information, which may include but is not limited to AI service processing latency, AI service processing accuracy, AI service computing volume, data processing scale, data storage requirements, expected application scope, etc.;

[0129] Quality of Experience (QoE) requirements for AI services.

[0130] Optionally, the first message may further include at least one of the following:

[0131] AI business logo;

[0132] AI unit related parameters, such as whether the network internal AI unit indication is required, AI unit identification, etc.

[0133] An indication of whether network internal data and the source of the data are required.

[0134] In this embodiment, the first message may be an AI service establishment request message, etc.

[0135] Optionally, the second message is used to notify the result of the AI ​​service establishment request, including at least one of the following:

[0136] Relevant information about the AI ​​resource node used to perform the verification business; for example, the relevant information may be a node identifier, etc.;

[0137] A fifth indication, wherein the fifth indication is used to indicate a verification indicator of the AI ​​service, or to indicate that the verification indicator of the AI ​​service is determined by the second network element; for example, the fifth indication may explicitly indicate the verification indicator of the AI ​​service, or to indicate that the verification indicator of the AI ​​service is determined by the OTT server;

[0138] Verification indicator thresholds for AI services;

[0139] Parameter items that need to be reported in the verification results of the verification service; for example, the reported parameter items may include but are not limited to at least one of the following items of the AI ​​unit: accuracy, recall, normalized mean square error, normalized root mean square error, error level, accuracy level, recall level, etc.

[0140] In this embodiment, the second message may be an AI service establishment request response message, that is, a response message to the above-mentioned AI service establishment request message.

[0141] Optionally, the service processing method may further include:

[0142] The second network element sends first data to the fourth network element, where the first data includes input data of the AI ​​unit, so that the fourth network element performs processing operations of the AI ​​unit, such as AI unit reasoning, based on the received first data.

[0143] Here, the fourth network element is an AI resource node, a resource node, a computing power resource node, a computing power execution node, a computing power execution plane, a business resource node, etc., which is used for business processing and implementation of business policy rules, etc.; specifically, the AI ​​business can be calculated and processed according to the command of the seventh network element, such as execution on the user plane, or AI resource status update to the seventh network element, etc.

[0144] In some embodiments, the fourth network element may perform processing operations of the AI ​​unit, such as AI unit reasoning, based on the first data and data obtained from the data source.

[0145] Optionally, the second network element may send the first data to the fourth network element through the fifth network element. The fifth network element is, for example, a network open function, which is located between the core network (such as the 6G core network) and an external third-party server (possibly also part of the internal AF), and is responsible for opening network capabilities and network internal information; all external applications that want to access the internal data of the core network must go through the network open function. The network open function provides corresponding security guarantees to ensure the security of external applications to the core network, and provides functions such as external application target / demand customization capability opening, mobility status event subscription, and AF request distribution.

[0146] Optionally, the service processing method may further include:

[0147] The second network element receives second data sent by the fourth network element, where the second data includes an output result of the AI ​​unit. For example, the second network element may receive the second data sent by the fourth network element after sending the first data to the fourth network element, such as receiving an AI unit inference result obtained based on the first data.

[0148] Optionally, the service processing method may further include:

[0149] The second network element sends a verification result to the third network element, where the verification result includes at least one of the following:

[0150] Verifying party identification;

[0151] The type of service used to verify the business;

[0152] Whether the AI ​​unit achieves expected performance;

[0153] Generalization indicators of AI units;

[0154] The scope of application of the AI ​​unit, i.e., the scope within which the AI ​​unit can be applied;

[0155] The accuracy level of the AI ​​unit;

[0156] The accuracy of the AI ​​unit;

[0157] AI unit identifier.

[0158] Here, the verification result may be a verification result calculated by the second network element (such as an OTT server) based on the received second data. The verification result may be fed back through the control plane. Thus, the third network element may obtain the verification result related to the AI ​​unit.

[0159] The third network element may be an AI service management function, an external service management function, a collaborative control function, a service management function, a computing service management function, or other network functions capable of implementing similar functions, for service management and service identification resolution, etc. For example, the OTT server may send the verification result to the AI ​​service management function.

[0160] Optionally, when the AI ​​service is a verification service, the generalization index of the AI ​​unit includes at least one of the following:

[0161] 1) First information, including: an identifier of a first data set, an identifier of a second data set, and a difference in an index of an AI unit under the second data set and the first data set, wherein the first data set is a data set for training the AI ​​unit, and the second data set is a data set for verifying the AI ​​unit; for example, the data distribution characteristics of the first data set are different from the data distribution characteristics of the second data set, so as to verify the performance of the AI ​​unit trained according to the first data set under the second data set;

[0162] 2) second information, wherein the second information includes: a sixth indication, an indicator threshold of the AI ​​unit under a supportable data set, wherein the sixth indication is used to indicate a data set that the AI ​​unit can support; in this case, the indicator threshold can be used to verify the performance of the AI ​​unit under the supportable data set; and the sixth indication can be used to characterize the scope of application of the model under the condition that the indicator threshold is met;

[0163] 3) third information, the third information including: an identifier of the first scenario, an identifier of the second scenario, and an index difference between the AI ​​unit in the second scenario and the first scenario, the first scenario being a scenario when the AI ​​unit is trained, and the second scenario being a scenario when the AI ​​unit is verified; in this case, the scenario when the AI ​​unit is trained is different from the scenario when the AI ​​unit is verified, for example, the scenario when the AI ​​unit is trained is a sparse large rural scenario, while the scenario when the AI ​​unit is verified is a dense urban scenario, so as to verify the performance of the AI ​​unit trained in the first scenario in the second scenario;

[0164] 4) fourth information, the fourth information including: a seventh indication, an indicator threshold of the AI ​​unit in a supportable scenario, the seventh indication being used to indicate a scenario that the AI ​​unit can support; in this case, the indicator threshold can be used to verify the performance of the AI ​​unit in a supportable scenario; and the sixth indication can be used to characterize the scope of application of the model when the indicator threshold is met;

[0165] 5) fifth information, the fifth information including: an identifier of the first field, an identifier of the second field, and an index difference between the second field and the first field of the AI ​​unit, the first field being the field of the AI ​​unit training, and the second field being the field of the AI ​​unit verification; in this case, the field of the AI ​​unit training is different from the field of the AI ​​unit verification, for example, the field of the AI ​​unit training is speech recognition in the legal field, while the field of the AI ​​unit verification is speech recognition in the fine arts field, so as to verify the performance of the AI ​​unit trained in the first field in the second field;

[0166] 6) Sixth information, the sixth information includes: an eighth indication and an indicator threshold of the AI ​​unit in a supportable field, the eighth indication is used to indicate the supportable field of the AI ​​unit; in this case, with the help of the indicator threshold, the performance of the AI ​​unit in the supportable field can be verified; with the help of the sixth indication, the scope of application of the model can be represented when the indicator gate is met.

[0167] Here, the above 1) and 2) can be understood as a data set description method for generalization indicators, the above 3) and 4) can be understood as a scene description method for generalization indicators, and the above 5) and 6) can be understood as a domain description method for generalization indicators.

[0168] The above-mentioned indicator may be selected from but not limited to at least one of the following items of the AI ​​unit: accuracy, recall, normalized mean square error, normalized root mean square error, etc. For example, the above-mentioned indicator difference is the accuracy difference, and the above-mentioned indicator threshold is the accuracy threshold; or, the above-mentioned indicator difference is the recall difference, and the above-mentioned indicator threshold is the recall threshold; and so on.

[0169] See also Figure 4 , Figure 4 is a flow chart of a service processing method provided in an embodiment of the present application, the method is executed by a third network element, such as Figure 4 As shown, the method comprises the following steps:

[0170] Step 41: The third network element sends a fourth message to the sixth network element, where the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service.

[0171] Step 42: The third network element receives a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0172] In this embodiment, the fourth message may include but is not limited to at least one of the following:

[0173] Business logo;

[0174] Type of service;

[0175] The expected accuracy of the AI ​​unit used for the verification service;

[0176] Data storage requirements of the AI ​​unit used for the verification service;

[0177] The data input format of the AI ​​unit used for the verification service;

[0178] The generalizability indicator of the AI ​​unit used for the verification business.

[0179] In this embodiment, the fourth message may be selected as an AI unit request message, a model request message, etc.

[0180] In this embodiment, the third network element and the sixth network element may be specifically as described above. Thus, with the help of the fourth message, the AI ​​unit required for the AI ​​service can be determined, thereby realizing the AI ​​service process.

[0181] Optionally, when the AI ​​service is a verification service, the generalization index of the AI ​​unit includes at least one of the following:

[0182] 1) First information, including: an identifier of a first data set, an identifier of a second data set, and a difference in an index of an AI unit under the second data set and the first data set, wherein the first data set is a data set for training the AI ​​unit, and the second data set is a data set for verifying the AI ​​unit; for example, the data distribution characteristics of the first data set are different from the data distribution characteristics of the second data set, so as to verify the performance of the AI ​​unit trained according to the first data set under the second data set;

[0183] 2) second information, wherein the second information includes: a sixth indication, an indicator threshold of the AI ​​unit under a supportable data set, wherein the sixth indication is used to indicate a data set that the AI ​​unit can support; in this case, the indicator threshold can be used to verify the performance of the AI ​​unit under the supportable data set; and the sixth indication can be used to characterize the scope of application of the model under the condition that the indicator threshold is met;

[0184] 3) third information, the third information including: an identifier of the first scenario, an identifier of the second scenario, and an index difference between the AI ​​unit in the second scenario and the first scenario, the first scenario being a scenario when the AI ​​unit is trained, and the second scenario being a scenario when the AI ​​unit is verified; in this case, the scenario when the AI ​​unit is trained is different from the scenario when the AI ​​unit is verified, for example, the scenario when the AI ​​unit is trained is a sparse large rural scenario, while the scenario when the AI ​​unit is verified is a dense urban scenario, so as to verify the performance of the AI ​​unit trained in the first scenario in the second scenario;

[0185] 4) fourth information, the fourth information including: a seventh indication, an indicator threshold of the AI ​​unit in a supportable scenario, the seventh indication being used to indicate a scenario that the AI ​​unit can support; in this case, the indicator threshold can be used to verify the performance of the AI ​​unit in a supportable scenario; the seventh indication can be used to characterize the scope of application of the model when the indicator threshold is met;

[0186] 5) fifth information, the fifth information including: an identifier of the first field, an identifier of the second field, and an index difference between the second field and the first field of the AI ​​unit, the first field being the field of the AI ​​unit training, and the second field being the field of the AI ​​unit verification; in this case, the field of the AI ​​unit training is different from the field of the AI ​​unit verification, for example, the field of the AI ​​unit training is speech recognition in the legal field, while the field of the AI ​​unit verification is speech recognition in the fine arts field, so as to verify the performance of the AI ​​unit trained in the first field in the second field;

[0187] 6) Sixth information, the sixth information includes: an eighth indication, an indicator threshold of the AI ​​unit in a supportable field, and the eighth indication is used to indicate the supportable field of the AI ​​unit; in this case, with the help of the indicator threshold, the performance of the AI ​​unit in the supportable field can be verified; with the help of the eighth indication, the scope of application of the model can be represented when the indicator gate is met.

[0188] In this embodiment, a request may be made to obtain AI resources. The service processing method further includes:

[0189] The third network element sends a fifth message to the seventh network element, where the fifth message is used to request AI resources for the AI ​​service, and the fifth message includes but is not limited to at least one of the following:

[0190] Data storage requirements;

[0191] Handling latency requirements, such as the latency of executing model inference / validation for AI resource nodes;

[0192] the format of input or output data;

[0193] AI unit information, such as model ID or model download address;

[0194] Data source information, such as data source address;

[0195] Computational capacity, such as computing power size and type.

[0196] Here, the seventh network element may be an AI resource management function, a resource management function, a computing power control function, an AI resource control function, a computing power resource management function, or other network functions capable of implementing similar functions, for business resource management, etc. Specifically, the allocation, update, and release of AI / computing power resources may be performed on demand; the status of AI / computing power resource nodes may be updated and maintained, etc. The fifth message may be an AI resource request message, for requesting the required AI resources.

[0197] In this embodiment, at least two (i.e., two or three) of the third network element, the sixth network element, and the seventh network element may be the same network element or may be jointly provided. For example, in this embodiment, when the third network element is an AI service management function, the sixth network element is an AI model management function, and the seventh network element is an AI resource management function, at least two of the AI ​​service management function, the AI ​​model management function, and the AI ​​resource management function may be the same network element or may be jointly provided.

[0198] In this embodiment, the service processing method may further include:

[0199] The third network element receives the verification result sent by the second network element, where the verification result includes at least one of the following:

[0200] Verifying party identification;

[0201] Type of service;

[0202] Whether the AI ​​unit achieves expected performance;

[0203] Generalization indicators of AI units;

[0204] The scope of application of the AI ​​unit, i.e., the scope within which the AI ​​unit can be applied;

[0205] The accuracy level of the AI ​​unit;

[0206] The accuracy of the AI ​​unit;

[0207] AI unit identifier.

[0208] Here, the verification result may be a verification result calculated by the second network element (such as an OTT server) based on the received AI unit output data, thereby enabling the third network element to obtain the verification result related to the AI ​​unit.

[0209] In this embodiment, the service processing method may further include:

[0210] The third network element sends a verification result to the first network element or the sixth network element, where the verification result includes at least one of the following:

[0211] Verifying party identification;

[0212] Type of service;

[0213] Whether the AI ​​unit achieves expected performance;

[0214] Generalization indicators of AI units;

[0215] The scope of application of the AI ​​unit, i.e., the scope within which the AI ​​unit can be applied;

[0216] The accuracy level of the AI ​​unit;

[0217] The accuracy of the AI ​​unit;

[0218] AI unit identifier.

[0219] Here, the third network element, the first network element and the sixth network element may specifically be as described above.

[0220] In some embodiments, after receiving the verification result from the second network element, the third network element may forward the received verification result to the first network element or the sixth network element.

[0221] See also Figure 5 , Figure 5 is a flow chart of a service processing method provided in an embodiment of the present application, the method is executed by a fourth network element, such as Figure 5 As shown, the method comprises the following steps:

[0222] Step 51: The fourth network element receives first data sent by the second network element, where the first data includes input data of the AI ​​unit;

[0223] Step 52: The fourth network element performs AI unit processing according to the first data;

[0224] Step 53: The fourth network element sends second data to the second network element, where the second data includes the output result of the AI ​​unit.

[0225] Here, the fourth network element and the second network element may specifically be as described above.

[0226] The execution of AI unit processing includes but is not limited to model reasoning, etc.

[0227] Therefore, the fourth network element can execute the processing operation of the AI ​​unit according to the first data, such as the model reasoning operation, to obtain the AI ​​unit reasoning result, thereby realizing the AI ​​business service process.

[0228] Optionally, the fourth network element may receive the first data sent by the second network element through the fifth network element.

[0229] Optionally, the fourth network element may send the second data to the second network element through the fifth network element.

[0230] For example, the fifth network element is a network opening function, which is located between the core network (such as the 6G core network) and the external third-party server, and is responsible for managing network data open to the outside world.

[0231] Optionally, the fourth network element may release AI resources after completing AI unit processing to avoid AI resources being occupied by completed services, thereby improving AI resource utilization.

[0232] Optionally, the service processing method may further include:

[0233] The fourth network element receives configuration information sent by the seventh network element, where the configuration information is used to configure AI resources, and the configuration information includes at least one of the following:

[0234] A ninth instruction, wherein the ninth instruction is used to indicate an AI framework;

[0235] A tenth indication, the tenth indication is used to indicate an AI library version;

[0236] Data source information; for example, the data source corresponding to the data source information can be used to generate, store and forward data;

[0237] AI business detection information;

[0238] AI service processing rules; for example, the AI ​​service processing rules may be configured by the network or agreed upon in advance.

[0239] Here, the seventh network element may specifically be as described above. It should be noted that the AI ​​framework is a set of standard interfaces, feature libraries, and toolkits for the design, training, and verification of AI algorithm models. It integrates the encapsulation of algorithms, the calling of data, and the use of computing resources. It also provides a development interface and an efficient execution platform for developers. It is an essential tool for the development of AI algorithms. Examples of AI frameworks include TensorFlow, PyTorch, Keras, Caffe, and MXNet. The AI ​​library may be a deep learning function library. Examples of AI library versions include versions of different libraries such as NumPy, Matplotlib, and Pandas.

[0240] See also Figure 6 , Figure 6 is a flow chart of a service processing method provided in an embodiment of the present application, the method is executed by the sixth network element, such as Figure 6 As shown, the method comprises the following steps:

[0241] Step 61: The sixth network element receives a fourth message sent by the third network element, where the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service.

[0242] Step 62: The sixth network element sends a response message of the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0243] In this embodiment, the fourth message may include but is not limited to at least one of the following:

[0244] Business logo;

[0245] Type of service;

[0246] The expected accuracy of the AI ​​unit used to verify the business;

[0247] Data storage requirements for AI units used to verify business;

[0248] Data input format for AI units used to verify business;

[0249] Generalization metrics for AI units used to validate business.

[0250] Therefore, with the help of the fourth message, the AI ​​unit required for the AI ​​service can be determined, thereby realizing the AI ​​service process.

[0251] In this embodiment, the fourth message may be an AI unit request message, a model request message, etc. The generalization index of the AI ​​unit may be as described above, which will not be described in detail here.

[0252] In this embodiment, the sixth network element and the third network element may specifically be as described above.

[0253] Optionally, the service processing method further includes:

[0254] The sixth network element receives a verification result sent by the third network element, where the verification result includes at least one of the following:

[0255] Verifying party identification;

[0256] Type of service;

[0257] Whether the AI ​​unit achieves expected performance;

[0258] Generalization indicators of AI units;

[0259] Scope of application of AI units;

[0260] The accuracy level of the AI ​​unit;

[0261] The accuracy of the AI ​​unit;

[0262] The identifier of the AI ​​unit.

[0263] Here, the verification result may be a verification result calculated by the second network element (such as an OTT server) based on the received AI unit output data. After receiving the verification result from the second network element, the third network element may forward the received verification result to the sixth network element.

[0264] Optionally, after receiving the verification result, the sixth network element may update the expected accuracy in the AI ​​unit description information according to the received verification result. It is understandable that the AI ​​unit description information in the sixth network element (such as the AI ​​model management function) includes the expected accuracy of the AI ​​unit, and after receiving the verification result of the AI ​​unit, its expected accuracy can be updated.

[0265] Combine the following Figure 7and Figure 8 The embodiments of the present application are described in detail.

[0266] Example 1

[0267] In this embodiment 1, the policy and billing function acts as a central control node. Due to the need to establish an AI verification service, the OTT server requests the policy and billing function to establish an AI service; the policy and billing function allocates corresponding AI policies according to the AI ​​service establishment request initiated by the OTT server, and the AI ​​policy is used to allocate corresponding resources to the corresponding network elements in the network; the policy and billing function shall comprehensively consider the end-to-end service requirements when allocating policies; the policy and billing function initiates the AI ​​service establishment request process to the AI ​​service management function. Figure 7 As shown in the figure, the specific AI verification business processing process includes:

[0268] Step 1. The second network element (e.g., an OTT server) sends an AI service establishment request message to the fifth network element (e.g., a network open function), wherein the request message is used to request the network to establish a corresponding AI service for it; the request message is specifically the first message mentioned above, and the information included therein may be the content included in the first message mentioned above, and to avoid repetition, it will not be repeated here.

[0269] Step 2. Optionally, the fifth network element (e.g., a network open function) authenticates the request message to determine whether the OTT server can request such AI service.

[0270] Optionally, the fifth network element (such as a network open function) can request the OTT server's OTT-related data from the UDM / UDR, including but not limited to contract data, policy data, etc., to verify whether the AI ​​service-related contract information exists; if it exists, execute subsequent processes; if it does not exist, the network open function rejects the OTT server's AI service establishment request.

[0271] Step 3. The fifth network element (eg, network open function) forwards the received AI service establishment request message to the policy charging function.

[0272] Step 4. The first network element (eg, policy and charging function) generates a corresponding AI policy according to the received AI service establishment request message. It should be noted that the first network element (eg, policy and charging function) should comprehensively consider the end-to-end service requirements of the AI ​​service when allocating the AI ​​policy.

[0273] Step 5. The first network element (eg, policy charging function) selects an AI service management function according to the received AI service establishment request message.

[0274] Optionally, the first network element (e.g., a policy charging function) may comprehensively consider some factors and use NRF or local configuration information to discover a matching AI service management function instance, and the factors considered may include at least one of the following:

[0275] -Area of ​​interest;

[0276] -UE AI task-related contract information;

[0277] -Data network name DNN;

[0278] - Slice information S-NSSAI;

[0279] -AI business logo;

[0280] -Supported AI services;

[0281] -Third network element (e.g. AI service management function) instance capabilities, such as AI service processing latency, AI service processing accuracy, AI service computing capacity, etc.

[0282] Step 6. The first network element (eg, policy charging function) sends an AI service establishment request message to the selected third network element (eg, AI service management function) to request allocation of corresponding AI resources and required models for the AI ​​service.

[0283] Optionally, the policy charging function and the AI ​​service management function may be integrated. If integrated, step 6 is implemented inside the network element.

[0284] Step 7a. The third network element (e.g., AI service management function) sends a model request message to the sixth network element (e.g., AI model management function) to determine the model information. The model request message is specifically the fourth message mentioned above, and the information included therein may be the content included in the fourth message mentioned above. To avoid repetition, it will not be repeated here.

[0285] Optionally, step 7a may be performed if at least one of the following conditions is met:

[0286] 1) The AI ​​service establishment request indicates that the OTT server does not contain model information;

[0287] 2) The AI ​​service establishment request contains indication information, indicating that interaction with the AI ​​model management function is required;

[0288] 3) The AI ​​business management function cannot obtain model information.

[0289] Optionally, the AI ​​business management function may select a corresponding AI model management function according to at least one of the following:

[0290] -DNN;

[0291] -S-NSSAI;

[0292] -AI business logo;

[0293] -Supported AI services;

[0294] -Service area information;

[0295] -Supported model information.

[0296] Step 7b. The sixth network element (eg, the AI ​​model management function) sends a model request response to the third network element (eg, the AI ​​service management function) to indicate the model information.

[0297] Optionally, a third network element (eg, an AI service management function) may determine data source information based on AI model information; if the data source has been determined, steps 8a and 8b will not be executed.

[0298] Step 8a. The third network element (eg, AI service management function) sends a data source request message to the data plane management function, where the request message is used to determine the data source information.

[0299] Optionally, step 8a may be performed if at least one of the following conditions is met:

[0300] (1) The AI ​​session establishment request indicates that the OTT server does not contain data source information;

[0301] (2) The AI ​​session establishment request includes indication information indicating that interaction with the data plane management function is required;

[0302] (3) The AI ​​business management function cannot obtain data source information.

[0303] Optionally, the AI ​​service management function may select a corresponding data plane management function according to at least one of the following:

[0304] -DNN;

[0305] -S-NSSAI;

[0306] -AI business logo;

[0307] -Supported AI services;

[0308] -Service area information;

[0309] -Data source information.

[0310] Step 8b. The data plane management function sends a data source request response message to the third network element (eg, the AI ​​service management function) to indicate the data source information.

[0311] Step 9a. The third network element (e.g., AI service management function) sends AI resource request information to the seventh network element (e.g., AI resource management function). The AI ​​resource request information is specifically the fifth message mentioned above, and the information included therein may be the content included in the fifth message mentioned above. To avoid repetition, it will not be repeated here.

[0312] Step 10. The seventh network element (e.g., the AI ​​resource management function) determines a suitable fourth network element (e.g., the AI ​​resource node) according to the AI ​​resource request information and the AI ​​policy, and sends AI resource configuration information to the fourth network element (e.g., the AI ​​resource node), where the configuration information may include but is not limited to at least one of the following:

[0313] -Data source information, such as data source address;

[0314] -AI business detection information;

[0315] -AI business processing rules;

[0316] -AI framework instructions;

[0317] -AI library version indication.

[0318] Step 9b. The seventh network element (e.g., AI resource management function) sends an AI resource request response message to the third network element (e.g., AI service management function), which includes information of the fourth network element (e.g., AI resource node), and the information includes at least one of the following:

[0319] - IP address;

[0320] -ID information;

[0321] -Fully Qualified Domain Name (FQDN).

[0322] Optionally, the AI ​​resource establishment response message may also include but is not limited to at least one of the following:

[0323] AI resource address;

[0324] AI resource type;

[0325] AI resource size.

[0326] Optionally, the third network element (e.g., AI service management function), the sixth network element (e.g., AI model management function) and the seventh network element (e.g., AI resource management function) can be combined; if combined, steps 7a, 7b, 9a and 9b are implemented internally in the network element.

[0327] Step 11. The third network element (eg, AI service management function) sends an AI service establishment request response message to the first network element (eg, policy charging function), which includes information of the fourth network element (eg, AI resource node).

[0328] Step 12. The first network element (e.g., the policy charging function) sends a response message corresponding to the request message in step 1 to the OTT server to notify the result of the AI ​​service establishment request; the response message is specifically the second message mentioned above, and the information included therein may be the content included in the second message mentioned above. To avoid repetition, it will not be repeated here.

[0329] Step 13. The second network element (e.g., an OTT server) sends the first data (i.e., AI service data) to the fourth network element (e.g., an AI resource node), where the first data is, for example, a model input data set for verification.

[0330] Optionally, the first data may be forwarded via a fifth network element (eg, a network open function).

[0331] Optionally, the first data is interpretable data, or privately processed data, such as encrypted data.

[0332] Step 14. Optionally, a fourth network element (eg, an AI resource node) obtains in-network data from a data source.

[0333] Step 15. The fourth network element (eg, AI resource node) performs model reasoning.

[0334] Step 16. The fourth network element (eg, an AI resource node) sends the second data (ie, AI service data) to the OTT server, where the second data is the model output result provided by the network, such as an inference result.

[0335] Optionally, the second data may be forwarded via a fifth network element (eg, a network open function).

[0336] Optionally, the second data is interpretable data, or privately processed data, such as encrypted data.

[0337] Step 17. The seventh network element (eg, AI resource management function) sends an inference end notification to the third network element (eg, AI service management function); the third network element (eg, AI service management function) feeds back ACK to the seventh network element (eg, AI resource management function).

[0338] Step 18. The seventh network element (eg, the AI ​​resource management function) sends a resource release indication to the fourth network element (eg, the AI ​​resource node), and the fourth network element (eg, the AI ​​resource node) releases the AI ​​resources.

[0339] Step 19. The second network element (eg, OTT server) calculates the verification result.

[0340] Step 20. The second network element (e.g., OTT server) feeds back the verification result to the third network element (e.g., AI service management function), for example, by forwarding it through the fifth network element (e.g., network open function). The information included in the verification result may be the content included in the above verification result, and will not be repeated here to avoid repetition.

[0341] Step 21a. The third network element (eg, AI service management function) forwards the verification result to the sixth network element (eg, AI model management function).

[0342] Step 21b. Optionally, the third network element (eg, AI service management function) forwards the verification result to the first network element (eg, policy calculation function).

[0343] Example 2

[0344] In this embodiment 2, the AI ​​service management function serves as the central control node. Due to the need to establish an AI verification service, the OTT server requests the AI ​​service management function to establish an AI service; the AI ​​service management function receives the AI ​​service establishment request message and negotiates with the policy charging function to obtain an AI policy. Figure 8 As shown in the figure, the specific AI verification business processing process includes:

[0345] Step 1. The second network element (e.g., an OTT server) sends an AI service establishment request message to the fifth network element (e.g., a network open function), wherein the request message is used to request the network to establish a corresponding AI service for it; the request message is specifically the first message mentioned above, and the information included therein may be the content included in the first message mentioned above, and to avoid repetition, it will not be repeated here.

[0346] Step 2. Optionally, the fifth network element (e.g., a network open function) authenticates the request message to determine whether the OTT server can request such AI service.

[0347] Optionally, the fifth network element (such as a network open function) can request the OTT server's OTT-related data from the UDM / UDR, including but not limited to contract data, policy data, etc., to verify whether the AI ​​service-related contract information exists; if it exists, execute subsequent processes; if it does not exist, the network open function rejects the OTT server's AI service establishment request.

[0348] Step 3. The fifth network element (eg, network open function) selects the AI ​​service management function according to the received request message.

[0349] Optionally, the fifth network element (e.g., a network open function) may comprehensively consider some factors and use NRF or local configuration information to discover a matching AI service management function instance, and the factors considered may include at least one of the following:

[0350] -Area of ​​interest;

[0351] -UE AI task-related contract information;

[0352] -Data network name DNN;

[0353] - Slice information S-NSSAI;

[0354] -AI business logo;

[0355] -Supported AI services;

[0356] - First network element (e.g. AI service management function) instance capabilities, such as AI service processing latency, AI service processing accuracy, AI service computing capacity, etc.

[0357] Step 4. The fifth network element (e.g., network open function) sends an AI service establishment request message to the AI ​​service management function to convert external AI service requirements into AI policies and request allocation of corresponding resources and models for the AI ​​service.

[0358] Optionally, the AI ​​service establishment request message includes at least one of the following: OTT server identifier, DNN, S-NSSAI, AI service identifier, model-related parameters, AI service management function address, AI service description information, etc.

[0359] Step 5. The first network element (eg, the AI ​​service management function) negotiates the AI ​​policy with the policy charging function.

[0360] Optionally, the first network element (eg, an AI service management function) and a policy charging function may generate a corresponding AI policy based on information carried in an AI service establishment request message.

[0361] Optionally, the first network element (eg, AI service management function) and the policy charging function should comprehensively consider the end-to-end service requirements of the AI ​​service when allocating AI policies.

[0362] Step 6a to step 9 are the same as step 7a to step 10 in the above embodiment 1 and will not be repeated here.

[0363] Step 10. The first network element (e.g., the AI ​​service management function) sends a response message corresponding to the request message in step 1 to the OTT server to notify the result of the AI ​​service establishment request. The response message is specifically the second message mentioned above, and the information included therein may be the content included in the second message mentioned above. To avoid repetition, it will not be repeated here.

[0364] Optionally, the policy charging function and the first network element (such as the AI ​​service management function) can be integrated; if integrated, step 5 is implemented inside the network element.

[0365] Step 11. The second network element (eg, an OTT server) sends the first data (ie, AI service data) to the fourth network element (eg, an AI resource node), where the first data is, for example, a model input data set for verification.

[0366] Optionally, the first data may be forwarded via a fifth network element (eg, a network open function).

[0367] Optionally, the first data is interpretable data, or privately processed data, such as encrypted data.

[0368] Step 12. Optionally, a fourth network element (eg, an AI resource node) obtains in-network data from a data source.

[0369] Step 13. The fourth network element (eg, AI resource node) performs model reasoning.

[0370] Step 14. The fourth network element (eg, an AI resource node) sends the second data (ie, AI service data) to the OTT server, where the second data is the model output result provided by the network, such as an inference result.

[0371] Optionally, the second data may be forwarded via a fifth network element (eg, a network open function).

[0372] Optionally, the second data is interpretable data, or privately processed data, such as encrypted data.

[0373] Step 15. The seventh network element (eg, AI resource management function) sends an inference end notification to the third network element (eg, AI service management function); the third network element (eg, AI service management function) feeds back ACK to the seventh network element (eg, AI resource management function).

[0374] Step 16. The seventh network element (eg, the AI ​​resource management function) sends a resource release indication to the fourth network element (eg, the AI ​​resource node), and the fourth network element (eg, the AI ​​resource node) releases the AI ​​resources.

[0375] Step 17. The second network element (eg, OTT server) calculates the verification result.

[0376] Step 18. The second network element (e.g., OTT server) feeds back the verification result to the third network element (e.g., AI service management function), for example, by forwarding it through the fifth network element (e.g., network open function). The information included in the verification result may be the content included in the above verification result, and will not be repeated here to avoid repetition.

[0377] Step 19a. The third network element (eg, AI service management function) forwards the verification result to the sixth network element (eg, AI model management function).

[0378] Step 19b. Optionally, a third network element (eg, an AI service management function) forwards the verification result to the policy calculation function.

[0379] Based on the above embodiments, it can be seen that through the solution in this application, the operator network can not only provide AI business processing services for the OTT server and expand the operator's business scenarios, but also ensure the security of OTT server data flow.

[0380] The service processing method provided in the embodiment of the present application can be executed by a service processing device. In the embodiment of the present application, the service processing device provided in the embodiment of the present application is described by taking the service processing method executed by the service processing device as an example.

[0381] See also Fig. 9 , Fig. 9 is a structural diagram of a service processing device provided in an embodiment of the present application, the device is applied to a first network element, such as Fig. 9 As shown, the service processing device 90 includes:

[0382] A first receiving module 91 is used to receive a first message sent by a second network element, where the first message is used to request to establish an AI service for the second network element, where the AI ​​service is a verification service;

[0383] The first sending module 92 is used to send a second message to the second network element, where the second message is used to respond to the first message; the first network element is a core network element, and the second network element is a third-party server.

[0384] Optionally, the first message includes at least one of the following:

[0385] The identification of the AI ​​unit used for the verification service;

[0386] Type of service;

[0387] A first indication indicating the format of input or output data of the AI ​​unit used for the verification service;

[0388] A second instruction indicates a performance verification method of the AI ​​unit;

[0389] A third instruction, indicating a reporting format of the verification result of the verification service;

[0390] Classification of verification objects of the verification service;

[0391] a fourth indication, indicating a privacy mode of the AI ​​unit for the authentication service provided by the second network element;

[0392] Description information of the AI ​​unit for the authentication service provided by the second network element;

[0393] Demand information for the AI ​​service;

[0394] The QoE requirements of the AI ​​service.

[0395] Optionally, the second message includes at least one of the following:

[0396] Relevant information of the AI ​​resource node used to perform the verification business;

[0397] a fifth indication, where the fifth indication is used to indicate a verification indicator of the AI ​​service, or to indicate that the second network element determines the verification indicator of the AI ​​service;

[0398] The verification indicator threshold of the AI ​​service;

[0399] Parameter items that need to be reported in the verification result of the verification service.

[0400] Optionally, the service processing device 90 further includes:

[0401] The second sending module is used to send a third message to a third network element, where the third message is used to request allocation of AI resources or required AI units for the AI ​​service.

[0402] The service processing device 90 provided in the embodiment of the present application can achieve Figure 2 The various processes implemented in the business processing method embodiment shown achieve the same technical effect, and will not be described again here to avoid repetition.

[0403] See also Fig.10 , Fig.10 is a structural diagram of a service processing device provided in an embodiment of the present application, the device is applied to a second network element, such as Fig.10 As shown, the service processing device 100 includes:

[0404] The third sending module 101 is used to send a first message to the first network element, where the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service;

[0405] The second receiving module 102 is used to receive a second message sent by the first network element, wherein the second message is used to respond to the first message.

[0406] Optionally, the first message includes at least one of the following:

[0407] The identification of the AI ​​unit used for the verification service;

[0408] Type of service;

[0409] A first indication indicating the format of input or output data of the AI ​​unit used for the verification service;

[0410] A second instruction, indicating a performance verification method of the AI ​​unit used for the verification service;

[0411] A third instruction, indicating a reporting format of the verification result of the verification service;

[0412] Verify the classification of objects;

[0413] a fourth indication, indicating a privacy mode of the AI ​​unit for the authentication service provided by the second network element;

[0414] Description information of the AI ​​unit for the authentication service provided by the second network element;

[0415] Demand information for the AI ​​service;

[0416] The QoE requirements of the AI ​​service.

[0417] Optionally, the second message includes at least one of the following:

[0418] Relevant information about AI resource nodes;

[0419] a fifth indication, where the fifth indication is used to indicate a verification indicator of the AI ​​service, or to indicate that the second network element determines the verification indicator of the AI ​​service;

[0420] The verification indicator threshold of the AI ​​service;

[0421] Report parameter items.

[0422] Optionally, the service processing device 100 further includes:

[0423] The fourth sending module is used to send first data to a fourth network element, wherein the first data includes input data of the AI ​​unit.

[0424] Optionally, the fourth sending module is specifically used to: send the first data to the fourth network element through a fifth network element.

[0425] Optionally, the service processing device 100 further includes:

[0426] The third receiving module is used to receive second data sent by the fourth network element, wherein the second data includes the output result of the AI ​​unit.

[0427] Optionally, the service processing device 100 further includes:

[0428] A fifth sending module is configured to send a verification result to a third network element, where the verification result includes at least one of the following:

[0429] Verifying party identification;

[0430] The type of service used for the verification service;

[0431] Whether the AI ​​unit achieves expected performance;

[0432] A generalization indicator of the AI ​​unit;

[0433] The scope of application of the AI ​​unit;

[0434] The accuracy level of the AI ​​unit;

[0435] The accuracy of the AI ​​unit;

[0436] AI unit identifier.

[0437] Optionally, the generalization index of the AI ​​unit includes at least one of the following:

[0438] First information, the first information including: an identifier of a first data set, an identifier of a second data set, and a difference in an indicator of the AI ​​unit under the second data set and the first data set, the first data set being a data set for AI unit training, and the second data set being a data set for AI unit verification;

[0439] second information, the second information comprising: a sixth indication, an indicator threshold of the AI ​​unit under a supportable data set, the sixth indication being used to indicate a data set that the AI ​​unit can support;

[0440] third information, the third information including: an identifier of a first scenario, an identifier of a second scenario, and a difference in an indicator of the AI ​​unit in the second scenario and the first scenario, the first scenario being a scenario during AI unit training, and the second scenario being a scenario during AI unit verification;

[0441] Fourth information, the fourth information comprising: a seventh indication, an indicator threshold of the AI ​​unit in a supportable scenario, the seventh indication being used to indicate a scenario that the AI ​​unit can support;

[0442] Fifth information, the fifth information including: an identifier of a first field, an identifier of a second field, and a difference between an indicator of the AI ​​unit in the second field and the first field, the first field being a field during AI unit training, and the second field being a field during AI unit verification;

[0443] The sixth information includes: an eighth indication and an indicator threshold of the AI ​​unit in a supportable field, and the eighth indication is used to indicate the supportable field of the AI ​​unit.

[0444] The service processing device 100 provided in the embodiment of the present application can realize Figure 3 The various processes implemented in the business processing method embodiment shown achieve the same technical effect, and will not be described again here to avoid repetition.

[0445] See also Fig.11 , Fig.11 is a structural diagram of a service processing device provided in an embodiment of the present application, and the device is applied to a third network element, such as Fig.11 As shown, the service processing device 110 includes:

[0446] A sixth sending module 111, configured to send a fourth message to a sixth network element, where the fourth message is used to request an AI unit required for an AI service, where the AI ​​service is a verification service;

[0447] The fourth receiving module 112 is used to receive a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0448] Optionally, the fourth message includes at least one of the following:

[0449] Business logo;

[0450] The type of service used for the verification service;

[0451] The expected accuracy of the AI ​​unit used for the verification service;

[0452] Data storage requirements of the AI ​​unit used for the verification service;

[0453] The data input format of the AI ​​unit used for the verification service;

[0454] The generalizability indicator of the AI ​​unit used for the verification business.

[0455] Optionally, the generalization index of the AI ​​unit includes at least one of the following:

[0456] First information, the first information including: an identifier of a first data set, an identifier of a second data set, and a difference in an indicator of the AI ​​unit under the second data set and the first data set, the first data set being a data set for AI unit training, and the second data set being a data set for AI unit verification;

[0457] second information, the second information comprising: a sixth indication, an indicator threshold of the AI ​​unit under a supportable data set, the sixth indication being used to indicate a data set that the AI ​​unit can support;

[0458] third information, the third information including: an identifier of a first scenario, an identifier of a second scenario, and a difference in an indicator of the AI ​​unit in the second scenario and the first scenario, the first scenario being a scenario during AI unit training, and the second scenario being a scenario during AI unit verification;

[0459] Fourth information, the fourth information comprising: a seventh indication, an indicator threshold of the AI ​​unit in a supportable scenario, the seventh indication being used to indicate a scenario that the AI ​​unit can support;

[0460] Fifth information, the fifth information including: an identifier of a first field, an identifier of a second field, and a difference between an indicator of the AI ​​unit in the second field and the first field, the first field being a field during AI unit training, and the second field being a field during AI unit verification;

[0461] The sixth information includes: an eighth indication and an indicator threshold of the AI ​​unit in a supportable field, and the eighth indication is used to indicate the supportable field of the AI ​​unit.

[0462] Optionally, the service processing device 110 further includes:

[0463] A seventh sending module is configured to send a fifth message to a seventh network element, where the fifth message is used to request AI resources for the AI ​​service, and the fifth message includes at least one of the following:

[0464] Data storage requirements;

[0465] Handling latency requirements;

[0466] the format of input or output data;

[0467] AI unit information;

[0468] Data source information;

[0469] Calculation amount.

[0470] Optionally, the service processing device 110 further includes:

[0471] A fifth receiving module is configured to receive a verification result sent by the second network element, where the verification result includes at least one of the following:

[0472] Verifying party identification;

[0473] Type of service;

[0474] Whether the AI ​​unit achieves expected performance;

[0475] A generalization indicator of the AI ​​unit;

[0476] The scope of application of the AI ​​unit;

[0477] The accuracy level of the AI ​​unit;

[0478] The accuracy of the AI ​​unit;

[0479] The AI ​​unit identifier.

[0480] Optionally, the service processing device 110 further includes:

[0481] An eighth sending module is configured to send a verification result to the first network element or the sixth network element, where the verification result includes at least one of the following:

[0482] Verifying party identification;

[0483] Type of service;

[0484] Whether the AI ​​unit achieves expected performance;

[0485] A generalization indicator of the AI ​​unit;

[0486] The scope of application of the AI ​​unit;

[0487] The accuracy level of the AI ​​unit;

[0488] The accuracy of the AI ​​unit;

[0489] The identification of the AI ​​unit.

[0490] The service processing device 110 provided in the embodiment of the present application can realize Figure 4 The various processes implemented in the business processing method embodiment shown achieve the same technical effect, and to avoid repetition, they will not be described again here.

[0491] See also Fig.12 , Fig.12 is a structural diagram of a service processing device provided in an embodiment of the present application, the device is applied to a fourth network element, such as Fig.12 As shown, the service processing device 120 includes:

[0492] A sixth receiving module 121, configured to receive first data sent by a second network element, where the first data includes input data of an AI unit;

[0493] A processing module 122, configured to perform AI unit processing according to the first data;

[0494] The ninth sending module 123 is used to send second data to the second network element, where the second data includes the output result of the AI ​​unit.

[0495] Optionally, the sixth receiving module 121 is specifically used to: receive the first data sent by the second network element through a fifth network element.

[0496] Optionally, the ninth sending module 123 is specifically used to: send the second data to the second network element through the fifth network element.

[0497] Optionally, the service processing device 120 further includes:

[0498] The release module is used to release AI resources after completing AI unit processing.

[0499] Optionally, the service processing device 120 further includes:

[0500] A seventh receiving module is configured to: receive configuration information sent by a seventh network element, where the configuration information is used to configure AI resources, and the configuration information includes at least one of the following:

[0501] A ninth instruction, wherein the ninth instruction is used to indicate an AI framework;

[0502] A tenth indication, the tenth indication is used to indicate an AI library version;

[0503] Data source information;

[0504] AI business detection information;

[0505] AI business processing rules.

[0506] The service processing device 120 provided in the embodiment of the present application can realize Figure 5 The various processes implemented in the business processing method embodiment shown achieve the same technical effect, and will not be described again here to avoid repetition.

[0507] See also Fig.13 , Fig.13 is a schematic diagram of the structure of a service processing device provided in an embodiment of the present application, the device is applied to a sixth network element, such as Fig.13 As shown, the service processing device 130 includes:

[0508] An eighth receiving module 131, configured to receive a fourth message sent by a third network element, where the fourth message is used to request an AI unit required for an AI service, where the AI ​​service is a verification service;

[0509] The tenth sending module 132 is used to send a response message of the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0510] Optionally, the fourth message includes at least one of the following:

[0511] Business logo;

[0512] The type of service used for the verification service;

[0513] The expected accuracy of the AI ​​unit used for the verification service;

[0514] Data storage requirements of the AI ​​unit used for the verification service;

[0515] The data input format of the AI ​​unit used for the verification service;

[0516] The generalizability indicator of the AI ​​unit used for the verification business.

[0517] Optionally, the service processing device 130 further includes:

[0518] An eighth receiving module is configured to receive a verification result sent by the third network element, where the verification result includes at least one of the following:

[0519] Verifying party identification;

[0520] Type of service;

[0521] Whether the AI ​​unit achieves expected performance;

[0522] A generalization indicator of the AI ​​unit;

[0523] The scope of application of the AI ​​unit;

[0524] The accuracy level of the AI ​​unit;

[0525] The accuracy of the AI ​​unit;

[0526] The identification of the AI ​​unit.

[0527] Optionally, the service processing device 130 further includes:

[0528] An updating module is used to update the expected accuracy in the AI ​​unit description information according to the verification result.

[0529] The service processing device 130 provided in the embodiment of the present application can realize Figure 6 The various processes implemented in the business processing method embodiment shown achieve the same technical effect, and to avoid repetition, they will not be described again here.

[0530] Optionally, an embodiment of the present application further provides a communication system, including: a first network element, a second network element, a third network element, a fourth network element and a sixth network element, wherein:

[0531] The first network element is used to: receive a first message sent by the second network element, the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service; send a second message to the second network element, and the second message is used to respond to the first message;

[0532] The second network element is used to: send a first message to the first network element, where the first message is used to request to establish an AI service for the second network element; and receive a second message sent by the first network element, where the second message is used to respond to the first message;

[0533] The third network element is used to: send a fourth message to the sixth network element, where the fourth message is used to request an AI unit required for the AI ​​service, and receive a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service;

[0534] The fourth network element is configured to: receive first data sent by the second network element, the first data including input data of the AI ​​unit; perform AI unit processing according to the first data; and send second data to the second network element, the second data including output results of the AI ​​unit;

[0535] The sixth network element is used to: receive a fourth message sent by the third network element, where the fourth message is used to request the AI ​​unit required for the AI ​​service; and send a response message to the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

[0536] Optionally, the communication system further includes a fifth network element, wherein:

[0537] The fourth network element is further configured to: receive first data sent by the second network element through the fifth network element, and send second data to the second network element through the fifth network element.

[0538] Optionally, the communication system further includes a seventh network element, wherein:

[0539] The third network element is further used to: send a fifth message to the seventh network element, where the fifth message is used to request AI resources for the AI ​​service;

[0540] The fourth network element is further used to: receive configuration information sent by the seventh network element, where the configuration information is used to configure AI resources.

[0541] like Fig.14 As shown, an embodiment of the present application also provides a communication device 140, including a processor 141 and a memory 142, and the memory 142 stores programs or instructions that can be executed on the processor 141. When the program or instruction is executed by the processor 141, the various steps of the above-mentioned business processing method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0542] The embodiment of the present application also provides a communication device, including a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the steps of the above-mentioned service processing method embodiment. The communication device embodiment corresponds to the above-mentioned method embodiment, and each implementation process and implementation method of the above-mentioned method embodiment can be applied to the communication device embodiment and can achieve the same technical effect.

[0543] Specifically, the embodiment of the present application also provides a network side device. Fig.15 As shown, the network side device 150 includes: a processor 151, a network interface 152 and a memory 153. The network interface 152 is, for example, a common public radio interface (CPRI).

[0544] Specifically, the network side device 150 of the embodiment of the present application also includes: instructions or programs stored in the memory 153 and executable on the processor 151. The processor 151 calls the instructions or programs in the memory 153 to execute the above-mentioned business processing method and achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0545] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned business processing method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0546] The processor is the processor in the terminal described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk. In some examples, the readable storage medium may be a non-transient readable storage medium.

[0547] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned business processing method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0548] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0549] The embodiments of the present application further provide a computer program / program product, which is stored in a storage medium and is executed by at least one processor to implement the various processes of the above-mentioned business processing method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0550] The embodiment of the present application also provides a communication system, including: a first network element, a second network element, a third network element, a fourth network element and a sixth network element, wherein the first network element can be used to perform the following steps: Figure 2 The steps of the method described above, the second network element can be used to perform Figure 3 The steps of the method described above, the third network element can be used to perform Figure 4 The steps of the method described above, the fourth network element can be used to perform Figure 5 The steps of the method described above, the sixth network element can be used to perform Figure 6 The steps of the method are described.

[0551] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0552] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of a computer software product plus a necessary general hardware platform, and of course, can also be implemented by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, disk, CD, etc.), including several instructions to enable a terminal or a network-side device to execute the methods described in each embodiment of the present application.

[0553] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms of implementation methods without departing from the purpose of the present application and the scope of protection of the claims, and these implementation methods are all within the protection of the present application.

Claims

1. A business processing method, characterized in that: include: The first network element receives a first message sent by the second network element, wherein the first message is used to request to establish an artificial intelligence AI service for the second network element, and the AI ​​service is a verification service; The first network element sends a second message to the second network element, where the second message is used to respond to the first message; the first network element is a core network element, and the second network element is a third-party server.

2. The method according to claim 1, characterized in that The first message includes at least one of the following: The identification of the AI ​​unit used for the verification service; The type of service used for the verification service; A first indication indicating the format of input or output data of the AI ​​unit used for the verification service; A second instruction, indicating a performance verification method of the AI ​​unit used for the verification service; A third instruction, indicating a reporting format of the verification result of the verification service; Classification of verification objects of the verification service; a fourth indication, indicating a privacy mode of the AI ​​unit for the authentication service provided by the second network element; Description information of the AI ​​unit for the authentication service provided by the second network element; Demand information for the AI ​​service; Quality of experience (QoE) requirements for the AI ​​service; or, The second message includes at least one of the following: Relevant information of the AI ​​resource node used to perform the verification service; a fifth indication, where the fifth indication is used to indicate a verification indicator of the AI ​​service, or to indicate that the second network element determines the verification indicator of the AI ​​service; The verification indicator threshold of the AI ​​service; Parameter items that need to be reported in the verification result of the verification service.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: The first network element sends a third message to the third network element, where the third message is used to request allocation of AI resources or required AI units for the AI ​​service.

4. A business processing method, characterized in that: include: The second network element sends a first message to the first network element, wherein the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service; The second network element receives a second message sent by the first network element, where the second message is used to respond to the first message; the first network element is a core network element, and the second network element is a third-party server.

5. The method according to claim 4, characterized in that The first message includes at least one of the following: The identification of the AI ​​unit used for the verification service; The type of service used for the verification service; A first indication indicating the format of input or output data of the AI ​​unit used for the verification service; A second instruction, indicating a performance verification method of the AI ​​unit used for the verification service; A third instruction, indicating a reporting format of the verification result of the verification service; Classification of verification objects of the verification service; a fourth indication, indicating a privacy mode of the AI ​​unit for the authentication service provided by the second network element; Description information of the AI ​​unit for the authentication service provided by the second network element; Demand information for the AI ​​service; QoE requirements of the AI ​​service; or, The second message includes at least one of the following: Relevant information of the AI ​​resource node used to perform the verification service; a fifth indication, where the fifth indication is used to indicate a verification indicator of the AI ​​service, or to indicate that the second network element determines the verification indicator of the AI ​​service; The verification indicator threshold of the AI ​​service; Parameter items that need to be reported in the verification result of the verification service.

6. The method according to claim 4 or 5, characterized in that: The method further comprises: The second network element sends first data to the fourth network element, wherein the first data includes input data of the AI ​​unit.

7. The method according to claim 6, characterized in that The second network element sending the first data to the fourth network element includes: The second network element sends the first data to the fourth network element through the fifth network element.

8. The method according to claim 6 or 7, characterized in that: The method further comprises: The second network element receives second data sent by the fourth network element, wherein the second data includes an output result of the AI ​​unit.

9. The method according to any one of claims 5 to 8, characterized in that: The method further comprises: The second network element sends a verification result to the third network element, wherein the verification result includes at least one of the following: Verifying party identification; The type of service used for the verification service; Whether the AI ​​unit achieves expected performance; A generalization indicator of the AI ​​unit; The scope of application of the AI ​​unit; The accuracy level of the AI ​​unit; The accuracy of the AI ​​unit; AI unit identifier.

10. The method according to claim 9, characterized in that The generalization index of the AI ​​unit includes at least one of the following: First information, the first information including: an identifier of a first data set, an identifier of a second data set, and a difference in an indicator of the AI ​​unit under the second data set and the first data set, the first data set being a data set for AI unit training, and the second data set being a data set for AI unit verification; second information, the second information comprising: a sixth indication, an indicator threshold of the AI ​​unit under a supportable data set, the sixth indication being used to indicate a data set that the AI ​​unit can support; third information, the third information including: an identifier of a first scenario, an identifier of a second scenario, and a difference in an indicator of the AI ​​unit in the second scenario and the first scenario, the first scenario being a scenario during AI unit training, and the second scenario being a scenario during AI unit verification; Fourth information, the fourth information comprising: a seventh indication, an indicator threshold of the AI ​​unit in a supportable scenario, the seventh indication being used to indicate a scenario that the AI ​​unit can support; Fifth information, the fifth information including: an identifier of a first field, an identifier of a second field, and a difference between an indicator of the AI ​​unit in the second field and the first field, the first field being a field during AI unit training, and the second field being a field during AI unit verification; The sixth information includes: an eighth indication and an indicator threshold of the AI ​​unit in a supportable field, and the eighth indication is used to indicate the supportable field of the AI ​​unit.

11. A business processing method, characterized in that: include: The third network element sends a fourth message to the sixth network element, wherein the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service; The third network element receives a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

12. The method according to claim 11, characterized in that The fourth message includes at least one of the following: Business logo; Type of service; The expected accuracy of the AI ​​unit used for the verification service; Data storage requirements of the AI ​​unit used for the verification service; The data input format of the AI ​​unit used for the verification service; The generalizability indicator of the AI ​​unit used for the verification business.

13. The method according to claim 12, characterized in that The generalization index of the AI ​​unit includes at least one of the following: First information, the first information including: an identifier of a first data set, an identifier of a second data set, and a difference in an indicator of the AI ​​unit under the second data set and the first data set, the first data set being a data set for AI unit training, and the second data set being a data set for AI unit verification; second information, the second information comprising: a sixth indication, an indicator threshold of the AI ​​unit under a supportable data set, the sixth indication being used to indicate a data set that the AI ​​unit can support; third information, the third information including: an identifier of a first scenario, an identifier of a second scenario, and a difference in an indicator of the AI ​​unit in the second scenario and the first scenario, the first scenario being a scenario during AI unit training, and the second scenario being a scenario during AI unit verification; Fourth information, the fourth information comprising: a seventh indication, an indicator threshold of the AI ​​unit in a supportable scenario, the seventh indication being used to indicate a scenario that the AI ​​unit can support; Fifth information, the fifth information including: an identifier of a first field, an identifier of a second field, and a difference between an indicator of the AI ​​unit in the second field and the first field, the first field being a field during AI unit training, and the second field being a field during AI unit verification; The sixth information includes: an eighth indication and an indicator threshold of the AI ​​unit in a supportable field, and the eighth indication is used to indicate the supportable field of the AI ​​unit.

14. The method according to any one of claims 11 to 13, characterized in that: The method further comprises: The third network element sends a fifth message to the seventh network element, wherein the fifth message is used to request AI resources for the AI ​​service, and the fifth message includes at least one of the following: Data storage requirements; Handling latency requirements; the format of input or output data; AI unit information; Data source information; Calculation amount.

15. The method according to any one of claims 11 to 14, characterized in that The method further comprises: The third network element receives a verification result sent by the second network element, wherein the verification result includes at least one of the following: Verifying party identification; Type of service; Whether the AI ​​unit achieves expected performance; A generalization indicator of the AI ​​unit; The scope of application of the AI ​​unit; The accuracy level of the AI ​​unit; The accuracy of the AI ​​unit; The AI ​​unit identifier.

16. The method according to any one of claims 11 to 15, characterized in that The method further comprises: The third network element sends a verification result to the first network element or the sixth network element, wherein the verification result includes at least one of the following: Verifying party identification; Type of service; Whether the AI ​​unit achieves expected performance; A generalization indicator of the AI ​​unit; The scope of application of the AI ​​unit; The accuracy level of the AI ​​unit; The accuracy of the AI ​​unit; The identification of the AI ​​unit.

17. A business processing method, characterized in that: include: The fourth network element receives first data sent by the second network element, where the first data includes input data of the AI ​​unit; The fourth network element performs AI unit processing according to the first data; The fourth network element sends second data to the second network element, where the second data includes an output result of the AI ​​unit.

18. The method according to claim 17, characterized in that The fourth network element receiving the first data sent by the second network element includes: The fourth network element receives the first data sent by the second network element through the fifth network element; or, The fourth network element sending second data to the second network element includes: The fourth network element sends the second data to the second network element through the fifth network element.

19. The method according to claim 17 or 18, characterized in that The method further comprises: After completing the AI ​​unit processing, the fourth network element releases the AI ​​resources.

20. The method according to any one of claims 17 to 19, characterized in that The method further comprises: The fourth network element receives configuration information sent by the seventh network element, wherein the configuration information is used to configure AI resources, and the configuration information includes at least one of the following: A ninth instruction, wherein the ninth instruction is used to indicate an AI framework; A tenth indication, the tenth indication is used to indicate an AI library version; Data source information; AI business detection information; AI business processing rules.

21. A business processing method, characterized in that: include: The sixth network element receives a fourth message sent by the third network element, wherein the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service; The sixth network element sends a response message of the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

22. The method according to claim 21, characterized in that The fourth message includes at least one of the following: Business logo; Type of service; The expected accuracy of the AI ​​unit used for the verification service; Data storage requirements of the AI ​​unit used for the verification service; The data input format of the AI ​​unit used for the verification service; The generalizability indicator of the AI ​​unit used for the verification business.

23. The method according to claim 21 or 22, characterized in that The method further comprises: The sixth network element receives a verification result sent by the third network element, wherein the verification result includes at least one of the following: Verifying party identification; Type of service; Whether the AI ​​unit achieves expected performance; A generalization indicator of the AI ​​unit; The scope of application of the AI ​​unit; The accuracy level of the AI ​​unit; The accuracy of the AI ​​unit; The identification of the AI ​​unit.

24. The method according to claim 23, characterized in that The method further comprises: The sixth network element updates the expected accuracy in the AI ​​unit description information according to the verification result.

25. A service processing device, characterized in that: include: A first receiving module, configured to receive a first message sent by a second network element, wherein the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service; The first sending module is used to send a second message to the second network element, where the second message is used to respond to the first message; the second network element is a third-party server.

26. A service processing device, characterized in that: include: A third sending module is used to send a first message to the first network element, wherein the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service; The second receiving module is used to receive a second message sent by a first network element, where the second message is used to respond to the first message; the first network element is a core network element, and the second network element is a third-party server.

27. A service processing device, characterized in that: include: a sixth sending module, configured to send a fourth message to a sixth network element, wherein the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service; The fourth receiving module is used to receive a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

28. A service processing device, characterized in that: include: A sixth receiving module, configured to receive first data sent by a second network element, where the first data includes input data of the AI ​​unit; A processing module, configured to perform AI unit processing according to the first data; A ninth sending module is used to send second data to the second network element, where the second data includes the output result of the AI ​​unit.

29. A service processing device, characterized in that: include: an eighth receiving module, configured to receive a fourth message sent by a third network element, wherein the fourth message is used to request an AI unit required for an AI service, and the AI ​​service is a verification service; A tenth sending module is used to send a response message of the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

30. A communication system, characterized in that: include: A first network element, a second network element, a third network element, a fourth network element and a sixth network element, wherein: The first network element is used to: receive a first message sent by the second network element, the first message is used to request to establish an AI service for the second network element, and the AI ​​service is a verification service; send a second message to the second network element, and the second message is used to respond to the first message; The second network element is used to: send a first message to the first network element, where the first message is used to request to establish an AI service for the second network element; and receive a second message sent by the first network element, where the second message is used to respond to the first message; The third network element is used to: send a fourth message to the sixth network element, where the fourth message is used to request an AI unit required for the AI ​​service, and receive a response message to the fourth message returned by the sixth network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service; The fourth network element is configured to: receive first data sent by the second network element, the first data including input data of the AI ​​unit; perform AI unit processing according to the first data; and send second data to the second network element, the second data including output results of the AI ​​unit; The sixth network element is used to: receive a fourth message sent by the third network element, where the fourth message is used to request the AI ​​unit required for the AI ​​service; and send a response message to the fourth message to the third network element, where the response message is used to indicate the AI ​​unit required for the AI ​​service.

31. The communication system according to claim 30, characterized in that The communication system further includes a fifth network element, wherein: The fourth network element is further configured to: receive first data sent by the second network element through the fifth network element, and send second data to the second network element through the fifth network element.

32. The communication system according to claim 30, characterized in that The communication system further includes a seventh network element, wherein: The third network element is further used to: send a fifth message to the seventh network element, where the fifth message is used to request AI resources for the AI ​​service; The fourth network element is further used to: receive configuration information sent by the seventh network element, where the configuration information is used to configure AI resources.

33. A communication device, characterized in that: It includes a processor and a memory, the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, it implements the steps of the business processing method as described in any one of claims 1 to 3, or implements the steps of the business processing method as described in any one of claims 4 to 10, or implements the steps of the business processing method as described in any one of claims 11 to 16, or implements the steps of the business processing method as described in any one of claims 17 to 20, or implements the steps of the business processing method as described in any one of claims 21 to 24.

34. A readable storage medium, characterized in that: The readable storage medium stores programs or instructions, and when the programs or instructions are executed by the processor, they implement the steps of the business processing method as described in any one of claims 1 to 3, or implement the steps of the business processing method as described in any one of claims 4 to 10, or implement the steps of the business processing method as described in any one of claims 11 to 16, or implement the steps of the business processing method as described in any one of claims 17 to 20, or implement the steps of the business processing method as described in any one of claims 21 to 24.

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