Data processing method and device, core network equipment and computer readable storage medium

Abstract

The embodiment of the invention discloses a data processing method and device, core network equipment and a computer readable storage medium, and relates to the technical field of communication. The method comprises the steps that a calculation task corresponding to a perception data set is distributed to at least one computing power node, and perception data in the perception data set comes from a third-party application function entity AF; and receiving a calculation result fed back by the at least one computing power node. According to the embodiment of the invention, the sensing data from the third-party AF is collected, the calculation task corresponding to the sensing data is distributed to the at least one computing power node for calculation, and the calculation result fed back by the computing power node is received, so that the processing capability of the sensing data can be improved; and the high-quality requirements of sensing data and computing power in a future communication system can be met.

Description

Data processing method, device, core network equipment and computer-readable storage medium Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a data processing method, apparatus, core network device, and computer-readable storage medium. Background Art

[0002] Wireless sensing technology aims to acquire information about remote objects and their characteristics without physical contact. This sensing data can be analyzed to assist with radio resource management, interference mitigation, beam management, mobility, and other areas, bringing benefits across multiple market segments and verticals, such as smart transportation, aviation, enterprises, smart cities, smart homes, factories, consumer applications, and the public sector.

[0003] In future communication systems, communication equipment and terminals will have the ability to perceive the physical world and mirror the digital world. The deep integration of communication systems with multiple systems such as perception and artificial intelligence has become a new trend in technological development.

[0004] Therefore, the requirements for data and computing power for new services in future communication systems will be higher.

[0005] Summary of the Invention

[0006] The embodiments of the present disclosure provide a data processing method, apparatus, core network device, and computer-readable storage medium.

[0007] According to a first aspect of the present disclosure, a data processing method is provided, which is applied to a first network element. The method includes:

[0008] Distributing computing tasks corresponding to a perception data set to at least one computing power node, wherein the perception data in the perception data set comes from a third-party application function entity AF;

[0009] Receive a calculation result fed back by at least one of the computing power nodes.

[0010] A second aspect of the present disclosure provides a data processing method, applied to a second network element, the method including:

[0011] A perception data set is sent to the first network element, wherein the perception data in the perception data set comes from a third-party application function entity AF.

[0012] A third aspect of the present disclosure provides a data processing method, applied to a third network element, including:

[0013] Sending a first request message to the second network element, where the first request message is used to request perception data;

[0014] A response message from the second network element in response to the first request message is received, where the response message carries a perception data set, and the perception data in the perception data set comes from a third-party application function entity AF.

[0015] According to a fourth aspect of the embodiments of the present disclosure, a core network device is provided, including: a first network element, a second network element, and a third network element, wherein:

[0016] The third network element is configured to send a first request message to the second network element in response to a service request message from the UE, wherein the service request message is used to request perception computing, and the first request message is used to request perception data;

[0017] The second network element is configured to send a second request message to the corresponding third-party application function entity AF in response to the first request message, and after receiving the perception data fed back by the third-party AF to form a perception data set, feed it back to the third network element, where the second request message is used to request the perception data of each third-party AF;

[0018] The third network element is further configured to determine task deployment information based on the received perception data set and the acquired computing power information, and send the task deployment information to the second network element;

[0019] The second network element is further configured to send the received sensing data set and the task deployment information to the first network element;

[0020] The first network element is configured to send the computing task corresponding to the perception data set to at least one computing power node according to the received task deployment information, and receive the computing results fed back by each computing power node.

[0021] According to a fifth aspect of the present disclosure, a data processing device is provided, which is applied to a first network element. The device includes:

[0022] The first communication module is configured to distribute the computing tasks corresponding to the perception data set to at least one computing power node, and receive the computing results fed back by at least one of the computing power nodes, wherein the perception data in the perception data set comes from a third-party application function entity AF.

[0023] According to a sixth aspect of the present disclosure, a data processing device is provided, which is applied to a second network element. The device includes:

[0024] The second communication module is configured to send a perception data set to the first network element, wherein the perception data in the perception data set comes from a third-party application function entity AF.

[0025] According to a seventh aspect of the present disclosure, a data processing device is provided, which is applied to a third network element. The device includes:

[0026] a third communication module, configured to send a first request message to a second network element, and receive a response message from the second network element in response to the first request message;

[0027] Wherein, the first request message is used to request perception data;

[0028] The response message carries a perception data set, and the perception data in the perception data set comes from a third-party application function entity AF.

[0029] According to an eighth aspect of the present disclosure, a core network element is provided, including:

[0030] transceiver;

[0031] processor;

[0032] a memory storing computer-executable instructions;

[0033] The processor is connected to the transceiver and the memory respectively, and is configured to load and execute the computer-executable instructions to implement the method of the first aspect, the second aspect, or the third aspect.

[0034] In a ninth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, in which executable instructions are stored. The executable instructions are loaded and executed by the processor to implement the method of the first aspect, the second aspect, or the third aspect.

[0035] The technical solutions provided by the embodiments of the present disclosure may have the following beneficial effects:

[0036] By collecting perception data from third-party AFs, distributing the corresponding computing tasks to at least one computing node for calculation, and receiving the calculation results fed back by the computing nodes, the processing capability of perception data can be improved, which can meet the high-quality requirements of perception data and computing power in future communication systems.

[0037] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0039] FIG1 is a schematic diagram 1 showing a network architecture according to an exemplary embodiment;

[0040] FIG2 is a second schematic diagram showing a network architecture according to an exemplary embodiment;

[0041] FIG3 is a flowchart 1 of a data processing method according to an exemplary embodiment;

[0042] FIG4 is a second flowchart of a data processing method according to an exemplary embodiment;

[0043] FIG5 is a third flowchart of a data processing method according to an exemplary embodiment;

[0044] FIG6 is a fourth flowchart of a data processing method according to an exemplary embodiment;

[0045] FIG7 is a block diagram 1 of a data processing device according to an exemplary embodiment;

[0046] FIG8 is a second block diagram of a data processing device according to an exemplary embodiment;

[0047] FIG9 is a third block diagram of a data processing device according to an exemplary embodiment;

[0048] FIG10 is a block diagram showing a data processing apparatus 900 according to an exemplary embodiment;

[0049] FIG11 is a block diagram showing a core network device according to an exemplary embodiment. DETAILED DESCRIPTION

[0050] The following describes in detail embodiments of the present disclosure, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present disclosure and are not to be construed as limiting the present invention.

[0051] In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0052] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a," "an," "said," and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present disclosure refers to the presence of the stated features, integers, steps, operations, elements, and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0053] It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element, or intervening elements may be present. Furthermore, "connected" or "coupled" as used herein may include wireless connections or wireless couplings. The term "and / or" as used herein includes all or any elements and all combinations of one or more of the associated listed items.

[0054] It should also be understood that although the terms first, second, third, etc. may be used to describe various information in the embodiments of the present disclosure, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0055] In the description of the present disclosure, unless otherwise specified, "multiple" means two or more than two, and other quantifiers are similar thereto; "at least one of the following", "one or more items" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, one or more items of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple; "and / or" is a type of association relationship that describes associated objects, indicating that three relationships can exist. For example, A and / or B can be represented by: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

[0056] Although operations are described in a particular order in the accompanying drawings in the disclosed embodiments, this should not be construed as requiring that the operations be performed in the particular order shown or in a serial order, or that all of the operations shown be performed to obtain the desired result. In certain circumstances, multitasking and parallel processing may be advantageous. Furthermore, sending multiple messages via the same message may also be advantageous.

[0057] The implementation environment of the embodiments of the present disclosure is first introduced below.

[0058] The technical solutions of the embodiments of the present disclosure can be applied to various communication systems. The communication system may include one or more of a 4G (the 4th Generation, fourth generation) communication system, a 5G (the 5th Generation, fifth generation) communication system, and other future wireless communication systems (such as 6G). The communication system may also include a land public mobile communication network (Public Land Mobile Network, PLMN) network, a non-terrestrial network communication system, a device-to-device (D2D) communication system, a machine-to-machine (M2M) communication system, an Internet of Things (IoT) communication system, a vehicle-to-everything (V2X) communication system, or one or more of other communication systems.

[0059] FIG1 shows a schematic diagram of a network architecture of the related art, which may specifically include the following network elements:

[0060] 1) User Equipment (UE)

[0061] User equipment (UE) includes devices that provide voice and / or data connectivity to users. Specifically, it includes devices that provide voice to users, devices that provide data connectivity to users, or devices that provide voice and data connectivity to users. For example, it may include a handheld device with wireless connection capabilities, or a processing device connected to a wireless modem. In one embodiment, the user equipment UE can be a mobile station (MS) or a mobile terminal (MT).

[0062] Specifically, the user equipment UE can be a mobile phone, a tablet computer or a computer with wireless transceiver function, and can also be a virtual reality (VR) terminal, augmented reality (AR) terminal, a wireless terminal in industrial control, a wireless terminal in unmanned driving, a wireless terminal in telemedicine, a wireless terminal in smart grid, a wireless terminal in smart city, a smart home, a vehicle-mounted terminal, etc.

[0063] 2) Access Network (AN)

[0064] An access network provides network access for authorized users in a specific area and can use transmission tunnels of varying quality based on user levels and service requirements. Access networks can utilize different access technologies. Currently, there are two types of wireless access technologies: 3rd Generation Partnership Project (3GPP) access technologies (e.g., those used in 3G, 4G, or 5G systems) and non-3GPP access technologies.

[0065] 3GPP access technologies refer to those that comply with 3GPP standards and specifications. Access networks that use 3GPP access technologies are called radio access networks (RANs). Access network equipment in 5G systems is called next-generation base stations (gNBs). Non-3GPP access technologies, such as Wi-Fi access points (APs), are not 3GPP-compliant.

[0066] An access network that implements network access functions based on wireless communication technologies is called a radio access network (RAN). The RAN manages radio resources, provides access services to user devices, and forwards control signals and user data between user devices and the core network.

[0067] 3) Access and Mobility Management Function (AMF) entity

[0068] The AMF entity is mainly used for mobility management and access management, and can be used to implement other functions of the mobility management entity (MME) in addition to session management, such as lawful interception or access authorization (or authentication).

[0069] 4) Session Management Function (SMF) entity

[0070] The SMF entity is mainly used for session management, UE Internet Protocol (IP) address allocation and management, selection of endpoints for manageable user plane functions, policy control, or charging function interfaces, and downlink data notification.

[0071] 5) User Plane Function (UPF) entity

[0072] The UPF is also called the data plane gateway, which can be used for packet routing and forwarding, or Quality of Service (QoS) processing of user plane data, etc. User data can access the data network (DN) through this network element.

[0073] 6) Policy Control Function (PCF) Entity

[0074] The PCF entity is mainly used to implement user control policy management, including QoS control, service access control, etc.

[0075] 7) Unified Data Management (UDM) Entity

[0076] The UDM entity is mainly used to implement user contract data management, roaming control, etc.

[0077] 8) Authentication Server Function (AUSF) Entity

[0078] The AUSF entity is mainly used to implement user authentication functions.

[0079] 9) Unified Data Repository (UDR) Entity

[0080] The UDR entity is mainly used to store the contract data and policy data of UDM and PCF.

[0081] 10) Network Exposure Function (NEF) Entity

[0082] The NEF entity is primarily used for capability exposure, which means exporting 5G network capabilities to external networks, such as terminal location information. The NEF can also receive external information and manage updates to certain network information.

[0083] 11) Network Repository Function (NRF) entity

[0084] The NRF entity is primarily used to manage all 5G network functions that support service-oriented interfaces. These NFs must first register with the NRF. When NFs search for each other, they query the NRF to find each other. This function is somewhat similar to the DNS in 4G networks, but the NRF function is far more complex. Failure of the NRF can have a significant impact on the network.

[0085] 12) Application Function (AF) Entity

[0086] AF entities generally refer to various apps that can interact directly or indirectly with the 5G network. Indirect interaction means that the AF interacts with other 5G NFs through the NEF.

[0087] It should be understood that the AMF entity, SMF entity, UPF entity, etc. shown in Figure 1 can be understood as network elements used to implement different functions in the core network, for example, they can be combined into network slices as needed. These core network network elements can be independent devices or integrated into the same device to implement different functions, which is not limited in this disclosure.

[0088] It should also be understood that the above naming is only used to distinguish different functions, and does not mean that these network elements are independent physical devices. The present disclosure does not limit the specific form of the above network elements. For example, they can be integrated into the same physical device, or they can be different physical devices. In addition, the above naming is only for the convenience of distinguishing different functions, and should not constitute any limitation to the present disclosure. The present disclosure does not exclude the possibility of adopting other naming in 5G networks and other networks in the future. For example, in a 6G network, some or all of the above network elements may use the terminology in 5G, or may use other names, etc. A unified explanation is given here, and no further details are given below.

[0089] Future communication systems, such as the sixth-generation mobile communication system (6G), have become a global research hotspot. A variety of new vertical application scenarios, represented by smart cities, smart transportation, intelligent manufacturing, and smart homes, will emerge in the 6G era. These will require communication equipment and terminals to have the ability to perceive the physical world and mirror the digital world. The deep integration of communication systems with multiple systems such as perception and artificial intelligence has become a new trend in technological development.

[0090] The development of communication and perception has always been independent and relatively parallel. Therefore, in 6G interawareness convergence, it is necessary to consider both the differences and commonalities between communication and perception, and create minimalist, efficient, and easy-to-deploy 6G interawareness convergence equipment and networking models. 6G networks will provide users with a more personalized service experience, and network status and resource supply should be aligned with user needs. Through the collaboration and sharing of interawareness computing software and hardware resources, network elements within this network will achieve a deep integration and mutually beneficial enhancement of multi-dimensional perception, collaborative communication, and intelligent computing capabilities, thereby enabling the network to intelligently interact and process new types of information flows and achieve wide-area intelligent collaboration.

[0091] In order to enable the collection and calculation of third-party AF perception data to better meet the new services and high-quality requirements for data and computing power emerging in 5G networks and other future networks, the embodiments of the present disclosure propose a network architecture as shown in Figure 2.

[0092] FIG2 shows a schematic diagram of a network architecture applicable to the method provided by an embodiment of the present disclosure. The network architecture is based on the network architecture shown in FIG2 and adds the following network elements:

[0093] 1) Scheduler network element: It is mainly used to schedule tasks related to business data according to business needs;

[0094] 2) Input network element: It is mainly used to input business data;

[0095] 3) Calculation network element: It is mainly used to control the calculation of business data, such as the distribution of calculation tasks, collection, summary and analysis of calculation results, etc.

[0096] 4) Output network element: It is mainly used to output service data;

[0097] 5) Storage network element: It is mainly used to store business data and / or related information.

[0098] For example, in the solution of the embodiment of the present disclosure, the Storage network element is used to store information about computing nodes that provide computing power support to the core network. In other words, a computing power node that can provide computing power support to the core network completes computing power registration in the Storage network element of the core network, indicating that it can execute computing power tasks (also known as computing power calculation tasks or computing tasks) allocated by the core network.

[0099] Computing power information may include information about the computing performance of the corresponding device, such as the amount of data transmitted per second, the AI ​​model used to calculate the data, whether only specific types of data can be calculated, etc. It should be understood that other information related to computing performance is not excluded.

[0100] The computing power nodes include one or more of the UE side, the core network side and the third-party computing power nodes.

[0101] It should be understood that the above-mentioned network architecture is merely an example of a network architecture described from the perspective of a traditional point-to-point architecture and a service-oriented architecture. The network architecture applicable to the embodiments of the present disclosure is not limited thereto. Any network architecture that can realize the functions of the above-mentioned network elements is applicable to the embodiments of the present disclosure.

[0102] It should be understood that the Scheduler NE, Input NE, Calculation NE, Output NE, Storage NE, etc. shown in Figure 2 can be understood as NEs used to implement different functions in the core network, for example, which can be combined into network slices as needed. These core network NEs can be independent devices or integrated into the same device to implement different functions, which is not limited in this disclosure.

[0103] It should also be understood that the naming of the above network elements is only used to distinguish different functions and does not mean that these network elements are independent physical devices. The present disclosure does not limit the specific form of the above network elements. For example, they can be integrated into the same physical device or they can be different physical devices. In addition, the above naming is only for the convenience of distinguishing different functions and should not constitute any limitation to the present disclosure. The present disclosure does not exclude the possibility of adopting other naming in other networks in the future. For example, in a 6G network, other names may also be used in the above network elements. A unified explanation is given here and no further details are given below.

[0104] It should be noted that, in the network architecture shown in FIG2 , only some network elements may participate in the data processing method of the embodiment of the present disclosure.

[0105] The following describes some application scenarios of the data processing method in the embodiment of the present disclosure. The data processing method in the embodiment of the present disclosure can be applied to the following scenarios, for example:

[0106] Real-time environmental monitoring: By processing the perceived wireless signals, the system reconstructs the environmental map, further improving positioning accuracy and enabling environmental-related applications such as dynamic 3D map-assisted driving, pedestrian flow statistics, intrusion detection, and traffic detection.

[0107] Autonomous vehicles / drones: Autonomous vehicles / drones share some common functional requirements. For example, they should support detect and avoid (DAA) to avoid obstacles. Furthermore, autonomous vehicles / drones should be able to monitor path information, such as selecting routes and complying with traffic regulations. Therefore, processing sensory data can help with obstacle avoidance and path monitoring.

[0108] Air pollution monitoring: The quality of received wireless signals exhibits different attenuation characteristics depending on changes in air humidity, particulate matter (PM) concentration, carrier frequency, etc. Therefore, processing the sensed data can assist in weather or air quality detection.

[0109] Indoor healthcare and intrusion detection: By processing the sensed data, respiratory rate estimation, respiratory depth estimation, apnea detection, vital sign monitoring of the elderly, and indoor intrusion detection can be achieved.

[0110] It should be noted that, under different scenario requirements, the types of perception data acquired by the third-party application function entity AF may be different.

[0111] For example, the sensing data may be the location and channel environment of the third-party application function entity AF, which can be used to help narrow the beam scanning range and shorten the beam training time.

[0112] For another example, the perception data may be the position, speed, motion trajectory, and channel environment of the third-party application function entity AF for beam prediction, which can reduce the overhead of beam measurement and the delay of beam tracking.

[0113] For another example, the perception data may be attributes (direction, size, shape, etc.) of the third-party application function entity AF and the channel environment, which may be used to improve the performance of channel estimation.

[0114] In addition to the above examples, the sensing data may also be data such as the trajectory of the third-party application function entity AF. In addition, the location of the third-party application function entity AF includes longitude information and latitude information.

[0115] It should also be noted that perception data can be expressed in the form of text, pictures, videos, voice, etc.

[0116] It should also be noted that the perception data may be data perceived by the third-party application function entity AF itself, or may be data received by the third-party application function entity AF from an external environment.

[0117] Based on the above network architecture, in order to realize the collection and calculation of third-party AF perception data, various embodiments of the disclosed method are proposed.

[0118] FIG3 is a flowchart of a data processing method according to an exemplary embodiment. As shown in FIG3 , the data processing method is used for a first network element in a core network device, including:

[0119] S11. Distribute computing tasks corresponding to a perception data set to at least one computing power node, wherein the perception data in the perception data set comes from a third-party application function entity AF.

[0120] S12. Receive calculation results fed back by at least one of the computing power nodes.

[0121] In the above scheme, by collecting perception data from third-party AF, distributing the corresponding computing tasks to at least one computing power node for calculation, and receiving the calculation results fed back by the computing power node, the processing capability of perception data can be improved, which can meet the high-quality requirements of perception data and computing power in future communication systems.

[0122] In some embodiments, further comprising:

[0123] S13a (not shown in the drawings), sending the calculation result to a network element for outputting the calculation result; and / or,

[0124] S13b (not shown in the drawings), sending the calculation result to the user equipment UE through the user plane network element, and the UE is a UE with perception calculation requirements.

[0125] In this embodiment, by collecting perception data from a third-party AF, distributing its corresponding computing tasks to at least one computing power node for calculation, and receiving the calculation results fed back by the computing power node, the calculation results can be sent to the network element for outputting the calculation results for output, and / or, sent to the UE requesting perception service calculation through the user plane network element, thereby providing a basis for subsequent use of the data.

[0126] For example, in this embodiment, the form of the network element output result for outputting the calculation result may include audio, screen display, specific operation of the Internet of Things device, etc., and other output methods are not excluded. This embodiment does not impose any limitations on this.

[0127] In some embodiments, before sending the calculation result, the method further includes:

[0128] The calculation results are analyzed and summarized.

[0129] In this embodiment, by collecting perception data from a third-party AF, distributing the corresponding computing tasks to at least one computing power node for calculation, and receiving the calculation results fed back by the computing power node, the calculation results can be analyzed and summarized, and then sent to the network element for outputting the calculation results for output, and / or, sent to the UE requesting perception service calculation through the user plane network element, thereby providing a better basis for the subsequent use of the data.

[0130] Exemplarily, in this embodiment, the calculation results from various computing power results are classified and summarized according to business type (for example: voice, image, text, etc.) or business requirements (voice recognition, text keyword extraction, image rendering, etc.) or size (within 500M, greater than 500M, etc.).

[0131] In some embodiments, S11 may specifically include: distributing the computing task corresponding to the perception data set to at least one computing power node according to the task deployment information for performing perception computing.

[0132] In this embodiment, the computing tasks corresponding to the perception data collected from the third-party AF can be distributed to at least one computing power node according to the task deployment information for performing perception computing, which can make the use of computing power resources more reasonable and effectively improve the data processing capability.

[0133] In some embodiments, further comprising:

[0134] S14 (not shown in the drawings): receiving the task deployment information sent by the second network element, where the task deployment information includes: the perception data in the perception data set and information of the corresponding computing nodes.

[0135] In this embodiment, since the task deployment information from the second network element includes the perception data in the perception data set and the information of the corresponding computing power nodes, the computing tasks corresponding to the perception data collected from the third-party AF are distributed to the corresponding computing power nodes according to the task deployment information for performing perception calculations, which can make the use of computing power resources more reasonable and effectively improve the data processing capabilities.

[0136] In some embodiments, the method further includes: receiving the perception data set sent by the second network element.

[0137] In this embodiment, the perception data from the third-party AF may be collected by receiving the perception data set sent by the second network element.

[0138] Exemplarily, the perception data in the perception data set may be processed by the second network element, for example, the perception data may be classified and aggregated according to data size, data type, etc., to form a summary analysis result of the perception data.

[0139] The computing power nodes in the above embodiments may include: at least one of UE, core network equipment and third-party computing power nodes, and / or at least one of any one of UE, core network equipment and third-party computing power nodes.

[0140] Exemplarily, if there is one computing power node, it can be any one of the UE side, the core network side, and the third-party computing power node. If there are two computing power nodes, it can be any two of the UE side, the core network side, and the third-party computing power node, or it can be two UEs, or two core network devices or network elements, or two third-party computing power nodes. If there are multiple computing power nodes, it can be multiple UEs, or multiple core network devices or network elements, or multiple third-party computing power nodes, or it can be a combination of UEs, core network devices or network elements, and third-party computing power nodes. The embodiments of this disclosure do not impose any restrictions on this.

[0141] It should be noted that the first network element in the embodiment of the present disclosure may include but is not limited to the Calculation network element in the core network architecture as shown in 2, or a network element with calculation function in other core network architectures in the future.

[0142] FIG4 is a second flowchart of a data processing method according to an exemplary embodiment. As shown in FIG4 , the data processing method is used for a second network element in a core network device, including:

[0143] S21. Send a perception data set to a first network element, where the perception data in the perception data set comes from a third-party application function entity AF.

[0144] In this embodiment, the second network element sends the perception data from the third-party application function entity AF to the first network element, providing a data basis for subsequent perception calculation.

[0145] In some embodiments, the perception data in the perception data set may be processed by the second network element. For example, the second network element may classify and aggregate the perception data according to data size, data type, etc., to form a summary analysis result of the perception data, and then send it to the first network element.

[0146] In some embodiments, further comprising:

[0147] S22 (not shown in the drawings): receiving a first request message sent by a third network element, where the first request message is used to request sensing data;

[0148] S23 (not shown in the drawings): In response to the first request message, obtain the perception data set.

[0149] In this embodiment, the second network element obtains a perception data set in response to a first request message sent by the third network element for requesting perception data, and sends the data set to the first network element to provide a data basis for subsequent perception calculation.

[0150] Exemplarily, the first request message may include information related to the third-party AF, such as an identifier, a location, a sensing area, a sensing data reporting period, etc. of the third-party AF.

[0151] In some embodiments, S23 may specifically include:

[0152] In response to the first request message, sending a second request message to the corresponding at least one third-party application function entity AF, where the second request message is used to request perception data of each third-party AF;

[0153] Receive the perception data sent by the at least one third-party AF to obtain the perception data set.

[0154] In this embodiment, the second network element can send a second request message for requesting perception data of a third-party AF to the corresponding at least one third-party application function entity AF in response to the first request message for requesting perception data sent by the third network element, and receive the perception data sent by each third-party AF.

[0155] In the above solution, the sensing data transmitted by the at least one third-party AF through the user plane network element may be received.

[0156] Exemplarily, the second request message may include information related to the third-party AF, such as the third-party AF's identifier, location, sensing area, sensing data reporting period, etc. It may also include other information related to the sensing data, such as the sensing data collection time period and collection location, etc.

[0157] In some embodiments, the method further comprises:

[0158] S24 (not shown in the drawings): sending a response message in response to the first request message to a third network element, where the response message carries the sensing data set;

[0159] S25 (not shown in the drawings): receiving task deployment information for performing perception computing sent by the third network element, where the task deployment information is obtained based on the perception data set.

[0160] In this embodiment, the second network element may feed back the collected third-party AF perception data to the third network element, and receive task deployment information for perception calculation sent by the third network element, where the task deployment information is obtained based on the collected third-party AF perception data.

[0161] In some embodiments, the method further comprises:

[0162] S26 (not shown in the drawings): sending the task deployment information to the first network element, where the task deployment information includes: the perception data in the perception data set and information of the corresponding computing nodes.

[0163] In this embodiment, the second network element can send the task deployment information from the third network element to the first network element. Since the task deployment information includes the perception data in the perception data set and the information of the corresponding computing power nodes, the first network element can distribute the computing tasks corresponding to the perception data collected from the third-party AF to the corresponding computing power nodes according to the task deployment information for performing perception calculations, which can make the use of computing power resources more reasonable and effectively improve the data processing capabilities.

[0164] It should be noted that the second network element in the embodiment of the present disclosure may include but is not limited to the Input network element in the core network architecture as shown in 2, or a network element with data input function in other core network architectures in the future.

[0165] It should also be noted that the third network element in the embodiment of the present disclosure may include but is not limited to the Scheduler network element in the core network architecture as shown in 2, or a network element with task scheduling function in other core network architectures in the future.

[0166] FIG5 is a flowchart of a third data processing method according to an exemplary embodiment. As shown in FIG5 , the data processing method is used by a third network element in a core network device, including:

[0167] S31. Send a first request message to a second network element, where the first request message is used to request perception data;

[0168] S32. Receive a response message from the second network element in response to the first request message, where the response message carries a perception data set, and the perception data in the perception data set comes from a third-party application function entity AF.

[0169] In this embodiment, the third network element can send a first request message to the second network element for requesting perception data, and receive a response message from the second network element in response to the first request message, which carries perception data from the third-party application function entity AF, thereby obtaining the perception data of the third-party AF and providing a basis for subsequent allocation and scheduling of computing resources.

[0170] In some embodiments, further comprising:

[0171] S33 (not shown in the drawings): determining task deployment information for performing perception computing based on the computing power information and the perception data set, wherein the computing power information includes information about computing power nodes that provide computing power support for the core network;

[0172] S34 (not shown in the drawings): sending the task deployment information to the second network element.

[0173] In this embodiment, the third network element can determine which perception data is calculated by which computing node or nodes based on the perception data and computing power information, thereby forming task deployment information and sending it to the second network element.

[0174] In some embodiments, further comprising:

[0175] S35 (not shown in the drawings), obtain the computing power information from the storage network element, where the storage network element is used to store information about computing power nodes that provide computing power support for the core network.

[0176] In this embodiment, the storage network element stores information about computing nodes that can provide computing power support for the core network. The third network element can directly retrieve all computing power information currently stored in the storage network element to prepare for the subsequent determination of the allocation of computing power resources for perception computing.

[0177] In some embodiments, further comprising:

[0178] S36 (not shown in the drawings), receiving a service request message from the UE, where the service request message is used to request perception computing;

[0179] S37 (not shown in the drawings): In response to the service request message, send the first request message to the second network element.

[0180] In this embodiment, the third network element sends a first request message to the second network element in response to the service request message of the UE for requesting to perform perception computing, so as to request perception data for performing perception computing.

[0181] In the above embodiment, the service request message includes: at least one of the identifier of the UE, the service type, and the service requirement.

[0182] Exemplarily, the UE identifier may be a Subscriber Permanent Identifier (SUPI); service types may include: voice, text, image, video, etc.; service requirements may include: voice recognition, text keyword extraction, image rendering, etc.

[0183] It should be understood that the embodiments of the present disclosure do not exclude other service types and service requirements, as well as other identifiers of the UE.

[0184] In the above embodiment, the task deployment information includes: the perception data in the perception data set and the corresponding computing nodes.

[0185] For example, assuming that the perception data set includes: text data, image data, and voice data, where the text data includes text data 1, the image data includes image data 1 (image data less than 500M) and image data 2 (image data greater than 500M), and the voice data includes voice data 1 (Chinese voice data), voice data 2 (English voice data), and voice data 3 (voice data in other languages); the information of the computing power node may include: one or more of: the location, type, number, identifier, name, etc. of the computing power node, then the task deployment information may be shown in the following table:

[0186] It should be noted that the contents listed in the above table are only for illustrating the task deployment information in the embodiment of the present disclosure, and do not constitute any limitation to the embodiment of the present disclosure, nor do they exclude that the content of the task deployment information may also include other information corresponding to perception computing, as well as other forms of expression.

[0187] FIG6 is a fourth flowchart of a data processing method according to an exemplary embodiment. As shown in FIG6 , the data processing method is used with a core network device. The core network device may include: a first network element, a second network element, and a third network element, as well as a storage network element and a network element for outputting calculation results. The method includes:

[0188] S101. The UE sends a service request message to the AMF, where the service request message is used to request perception computing.

[0189] In this embodiment, the service request message may also be referred to as a perceptual computing service request message. The service request message may include a Subscriber Permanent Identifier (SUPI), a service type, a service requirement, and the like.

[0190] Among them, business types may include: voice, text, image, video, etc.; business needs may include: voice recognition, text keyword extraction, image rendering, etc.

[0191] It should be understood that the embodiments of the present disclosure do not exclude other business types and business requirements.

[0192] S102. AMF forwards the received service request message to the third network element (which may correspond to the Scheduler network element in the network framework shown in Figure 2), so that the third network element establishes a service with the UE.

[0193] S103. In response to the received service request message, the third network element sends a first request message to the second network element (which may correspond to the Input network element in the network framework shown in Figure 2), where the first request message is used to request perception data.

[0194] In this embodiment, the first request message may be referred to as a third-party AF perception data input request message. Specifically, the third network element may determine the corresponding third-party AF based on the service requirements in the service request message, and send the first request message to the second network element to request the input of the third-party AF perception data.

[0195] For example, if the service requirement is voice recognition, voice data is required, and the third network element may send a request to the second network element to request input of third-party AF perceived voice data.

[0196] S104. In response to receiving the first request message, the second network element sends a second request message to one or more corresponding third-party AF application function entities. The second request message is used to request perception data of each third-party AF.

[0197] Specifically, the second network element may send a second request message to one or more third-party AF application function entities through a Network Exposure Function (NEF) entity. The second request message may be referred to as sensing data input request information.

[0198] S105. The third-party AF application function entity uploads the sensing data to the second network element.

[0199] Specifically, the perception data may be uploaded to the second network element via the user plane network element.

[0200] S106. The second network element summarizes and analyzes the received perception data.

[0201] Specifically, the second network element may classify and summarize the perception data according to the data size, data type, etc., to form a summary analysis result of the perception data.

[0202] S107. The second network element sends the summary analysis result of the perception data to the third network element.

[0203] S108: The third network element obtains computing power information from the storage network element (which may correspond to the storage network element in the network framework shown in FIG2 ). The computing power information includes information about computing power nodes that provide computing power support for the core network.

[0204] Specifically, in this embodiment, the computing power information may also be referred to as computing power registration information. The third network element may directly retrieve all computing power information currently stored in the storage network element.

[0205] For example, computing power information may include information about the computing performance of the corresponding device, such as the amount of data transmitted per second, the AI ​​model used when calculating data, whether only specific types of data can be calculated, etc. It should be understood that other information related to computing performance is not excluded.

[0206] S109. The third network element performs task deployment based on the acquired computing power information and the summary analysis results of the received perception data to obtain task deployment information.

[0207] Specifically, based on the summary analysis results of the perception data and the computing power information, it is possible to determine which perception data is calculated by which computing power node or nodes, thereby forming task deployment information.

[0208] S110. The third network element sends task deployment information to the second network element.

[0209] S111. The second network element sends the sensing data and task deployment information to the first network element (which may correspond to the Calculation network element in the network framework shown in FIG2 ).

[0210] S112. The first network element sends the computing task to the corresponding computing power node according to the task deployment information.

[0211] In this embodiment, there may be one or more computing power nodes, including UE side, core network side, and third-party computing power nodes. Exemplarily, there is one computing power node, which can be any one of the UE side, the core network side, and the third-party computing power node. There are two computing power nodes, which can be any two of the UE side, the core network side, and the third-party computing power nodes, or can be two UEs, or two core network devices or network elements, or two third-party computing power nodes. There are multiple computing power nodes, which can be multiple UEs, or multiple core network devices or network elements, or multiple third-party computing power nodes, or can be a combination of UEs, core network devices or network elements, and third-party computing power nodes. This embodiment does not impose any restrictions on this.

[0212] S113. Each computing power node returns the calculation result to the first network element.

[0213] S114. The first network element summarizes and analyzes the calculation results fed back by all computing power nodes.

[0214] After the first network element summarizes and analyzes the calculation results from each computing power node, it can output the calculation results by executing step S115a, and / or execute step S115b to feed back the calculation results to the UE that requests the perception calculation.

[0215] S115a. The first network element sends the calculation result to a network element for outputting the calculation result (which may correspond to the Output network element in the network framework shown in FIG2 ).

[0216] S116. The network element for outputting the calculation result outputs the result.

[0217] In this embodiment, the output form of the result may include audio, screen display, specific operation of the IoT device, etc.

[0218] S15b. The first network element sends the calculation result to the UE through the user plane network element.

[0219] The solution of the above embodiment collects perception data from the third-party AF and fully utilizes the computing resources of the UE side, the core network, and the third party for calculation and analysis, thereby supporting and meeting the new services emerging in 5G networks and other future networks, as well as the high-quality requirements for data and computing power.

[0220] Fig. 7 is a block diagram 1 of a data processing device according to an exemplary embodiment. The data processing device is applied to a first network element. Referring to Fig. 7 , the device includes: a first communication module 10 .

[0221] The first communication module 10 is configured to distribute the computing tasks corresponding to the perception data set to at least one computing power node, and receive the computing results fed back by at least one of the computing power nodes, wherein the perception data in the perception data set comes from a third-party application function entity AF.

[0222] In some embodiments, the first communication module 10 is further configured to: send the calculation result to a network element for outputting the calculation result; and / or send the calculation result to a user equipment UE through a user plane network element, where the UE is a UE with a perceived computing requirement.

[0223] In some embodiments, the device further includes: a first processing module 20 .

[0224] The first processing module 20 is configured to analyze and summarize the calculation results.

[0225] In some embodiments, the first communication module 10 is configured to distribute the computing task corresponding to the perception data set to at least one computing power node according to the task deployment information for performing perception computing.

[0226] In some embodiments, the first communication module 10 is further configured to: receive the task deployment information sent by the second network element, where the task deployment information includes: the perception data in the perception data set and information of the corresponding computing nodes.

[0227] In some embodiments, the first communication module 10 is further configured to: receive the sensing data set sent by the second network element.

[0228] The computing power nodes in the above embodiments may include: at least one of UE, core network equipment and third-party computing power nodes, and / or at least one of any one of UE, core network equipment and third-party computing power nodes.

[0229] Regarding the apparatus in the above embodiment, the specific manner in which each unit performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here.

[0230] In actual applications, the specific structures of the above-mentioned first communication module 10 and the first processing module 20 can be implemented by a central processing unit (CPU), a microprocessor (MCU), a digital signal processor (DSP) or a programmable logic controller (PLC) in the data processing device or the terminal to which the data processing device belongs.

[0231] The data processing device described in this embodiment can be set in the core network equipment.

[0232] Those skilled in the art should understand that the functions of each unit in the data processing apparatus of the embodiments of the present disclosure can be understood with reference to the aforementioned description of the data processing method applied to the first network element. The functions of each unit in the data processing apparatus of the embodiments of the present disclosure can be implemented by analog circuits that implement the functions described in the embodiments of the present disclosure, or by software that executes the functions described in the embodiments of the present disclosure and runs on a terminal.

[0233] The data processing device described in the embodiment of the present disclosure collects perception data from a third-party AF and fully utilizes the computing resources of the UE side, the core network, and the third party for computational analysis, thereby supporting and meeting the new services and high-quality requirements for data and computing power that will emerge in 5G networks and other future networks.

[0234] FIG8 is a second block diagram of a data processing device according to an exemplary embodiment. The data processing device is applied to a second network element. Referring to FIG8 , the device includes a second communication module 30 .

[0235] The second communication module 30 is configured to send a perception data set to the first network element, wherein the perception data in the perception data set comes from a third-party application function entity AF.

[0236] In some embodiments, the second communication module 30 is configured to: send a second request message to the corresponding at least one third-party application function entity AF in response to the first request message, wherein the second request message is used to request the perception data of each third-party AF; receive the perception data sent by the at least one third-party AF to obtain the perception data set.

[0237] In the above solution, the second communication module 30 is configured to receive the sensing data transmitted by the at least one third-party AF through the user plane network element.

[0238] In some embodiments, the second communication module 30 is further configured to:

[0239] Sending a response message in response to the first request message to a third network element, where the response message carries the sensing data set;

[0240] Receive task deployment information for performing perception computing sent by the third network element, where the task deployment information is obtained based on the perception data set.

[0241] In some embodiments, the second communication module 30 is further configured to: send the task deployment information to the first network element, where the task deployment information includes: the perception data in the perception data set and information of the corresponding computing nodes.

[0242] Regarding the apparatus in the above embodiment, the specific manner in which each unit performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here.

[0243] In practical applications, the specific structure of the second communication module 30 can be implemented by the data processing device or the camera, sensor, etc. belonging to the data processing device.

[0244] The data processing device described in this embodiment can be set in the core network equipment.

[0245] Those skilled in the art will appreciate that the functions of each unit in the data processing apparatus according to the embodiments of the present disclosure can be understood with reference to the aforementioned description of the data processing method applied to the second network element. The functions of each unit in the data processing apparatus according to the embodiments of the present disclosure can be implemented by analog circuits that implement the functions described in the embodiments of the present disclosure, or by software that executes the functions described in the embodiments of the present disclosure and runs on a base station.

[0246] The data processing device described in the embodiment of the present disclosure collects perception data from a third-party AF, distributes the corresponding computing tasks to at least one computing node for calculation, and receives the calculation results fed back by the computing node, thereby improving the processing capability of the perception data and meeting the high-quality requirements of perception data and computing power in future communication systems.

[0247] FIG9 is a block diagram 3 of a data processing device according to an exemplary embodiment. The data processing device is applied to a third network element. Referring to FIG9 , the device includes a third communication module 40 .

[0248] The third communication module 40 is configured to send a first request message to the second network element, and receive a response message from the second network element in response to the first request message;

[0249] Wherein, the first request message is used to request perception data;

[0250] The response message carries a perception data set, and the perception data in the perception data set comes from a third-party application function entity AF.

[0251] In some embodiments, the third communication module 40 is further configured to:

[0252] Determining task deployment information for performing perception computing based on the computing power information and the perception data set, wherein the computing power information includes information about computing power nodes that provide computing power support for the core network;

[0253] The task deployment information is sent to the second network element.

[0254] In some embodiments, the apparatus further includes: a second processing module 50 .

[0255] The second processing module is configured to obtain the computing power information from a storage network element, where the storage network element is used to store information about computing power nodes that provide computing power support for the core network.

[0256] In some embodiments, the third communication module 40 is further configured to:

[0257] receiving a service request message from a UE, where the service request message is used to request perception computing;

[0258] In response to the service request message, the first request message is sent to the second network element.

[0259] In the above embodiment, the service request message includes: at least one of the identifier of the UE, the service type, and the service requirement.

[0260] Regarding the apparatus in the above embodiment, the specific manner in which each unit performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here.

[0261] In practical applications, the specific structures of the third communication unit 40 and the second processing module 50 can be implemented by the data processing device.

[0262] The data processing device described in this embodiment can be set in the core network equipment.

[0263] Those skilled in the art will appreciate that the functions of each unit in the data processing apparatus of the embodiments of the present disclosure can be understood with reference to the aforementioned description of the data processing method applied to the third network element. The functions of each unit in the data processing apparatus of the embodiments of the present disclosure can be implemented by analog circuits that implement the functions described in the embodiments of the present disclosure, or by software that executes the functions described in the embodiments of the present disclosure and runs on a base station.

[0264] The data processing device described in the embodiment of the present disclosure collects perception data from a third-party AF, distributes the corresponding computing tasks to at least one computing node for calculation, and receives the calculation results fed back by the computing node, thereby improving the processing capability of the perception data and meeting the high-quality requirements of perception data and computing power in future communication systems.

[0265] FIG10 is a block diagram illustrating a method for implementing a data processing apparatus 900 according to an exemplary embodiment. Referring to FIG10 , the apparatus 900 includes a processing component 922, which further includes one or more processors, and a memory resource represented by a memory 932 for storing instructions executable by the processing component 922, such as an application. The application stored in the memory 932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 922 is configured to execute instructions to perform the above-mentioned data processing method applied to a core network element (such as the above-mentioned first network element, the above-mentioned second network element, or the above-mentioned third network element).

[0266] The device 900 may also include a power supply component 926 configured to perform power management of the device 900, a wired or wireless network interface 950 configured to connect the device 900 to a network, and an input / output (I / O) interface 958. The device 900 may operate based on an operating system stored in the memory 932, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or the like.

[0267] FIG11 is a block diagram of a core network device according to an exemplary embodiment. Referring to FIG11 , the core network device includes: a first network element 60, a second network element 70 and a third network element 80, wherein:

[0268] The third network element 80 is configured to send a first request message to the second network element 70 in response to a service request message from the UE, wherein the service request message is used to request perception calculation, and the first request message is used to request perception data;

[0269] The second network element 70 is configured to send a second request message to the corresponding third-party application function entity AF in response to the first request message, and after receiving the perception data fed back by the third-party AF to form a perception data set, feed it back to the third network element 80, where the second request message is used to request the perception data of each third-party AF;

[0270] The third network element 80 is further configured to determine task deployment information based on the received perception data set and the acquired computing power information, and send the task deployment information to the second network element 70;

[0271] The second network element 70 is further configured to send the received sensing data set and the task deployment information to the first network element 60;

[0272] The first network element 60 is configured to send the computing task corresponding to the perception data set to at least one computing power node according to the received task deployment information, and receive computing results fed back by each computing power node.

[0273] In some embodiments, the core network device further includes: a storage network element 90 and a network element 100 for outputting calculation results, wherein:

[0274] The storage network element 90 is configured to store information of computing nodes that provide computing support for the core network;

[0275] The third network element 80 is configured to obtain the computing power information from the storage network element;

[0276] The first network element 60 is further configured to analyze and summarize the calculation results and send them to the UE or the network element 100 for outputting the calculation results.

[0277] The core network device in this embodiment collects perception data from a third-party AF, distributes the corresponding computing tasks to at least one computing node for calculation, and receives the calculation results fed back by the computing node, thereby improving the processing capability of the perception data and meeting the high-quality requirements of perception data and computing power in future communication systems.

[0278] In an exemplary embodiment, the present disclosure further provides a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the steps of the data perception method provided by the present disclosure. For example, the computer-readable storage medium may be a non-transitory computer-readable storage medium including instructions, for example, the memory 932 of the above-mentioned device 900 including instructions, and the above-mentioned instructions may be executed by the processing component 922 of the device 900 to complete the above-mentioned data processing method. For example, the non-transitory computer-readable storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0279] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program executable by a programmable device, and has a code portion for executing the above data processing method when executed by the programmable device.

[0280] The technical solutions described in the embodiments of the present disclosure can be arbitrarily combined without conflict.

[0281] Other embodiments of the present invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the invention that follow from the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the following claims.

[0282] It should be understood that the present invention is not limited to the exact construction described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A data processing method, characterized in that: Applied to the first network element, including: Distribute computing tasks corresponding to a perception data set to at least one computing power node, wherein the perception data in the perception data set comes from a third-party application function entity AF; Receive a calculation result fed back by at least one of the computing power nodes.

2. The method according to claim 1, characterized in that: Also includes: Sending the calculation result to a network element for outputting the calculation result; and / or, The calculation result is sent to a user equipment UE through a user plane network element, and the UE is a UE with a perceived calculation requirement.

3. The method according to claim 2, characterized in that Before sending the calculation result, the method further includes: The calculation results are analyzed and summarized.

4. The method according to any one of claims 1 to 3, characterized in that The step of distributing the computing task corresponding to the perception data set to at least one computing power node includes: According to the task deployment information for performing perception computing, the computing task corresponding to the perception data set is distributed to at least one computing power node.

5. The method according to claim 4, characterized in that Also includes: The task deployment information sent by the second network element is received, where the task deployment information includes: the perception data in the perception data set and information of the corresponding computing power nodes.

6. The method according to any one of claims 1 to 5, characterized in that Also includes: Receive the perception data set sent by the second network element.

7. The method according to any one of claims 1 to 6, characterized in that The computing power node includes: at least one of UE, core network equipment and third-party computing power nodes, and / or at least one of any one of UE, core network equipment and third-party computing power nodes.

8. A data processing method, characterized in that: Applied to the second network element, including: A perception data set is sent to the first network element, wherein the perception data in the perception data set comes from a third-party application function entity AF.

9. The method according to claim 8, characterized in that Also includes: receiving a first request message sent by a third network element, where the first request message is used to request perception data; In response to the first request message, the perception data set is acquired.

10. The method according to claim 9, characterized in that The step of acquiring the perception data set in response to the first request message includes: In response to the first request message, sending a second request message to the corresponding at least one third-party application function entity AF, where the second request message is used to request the perception data of each third-party AF; The sensing data sent by the at least one third-party AF is received to obtain the sensing data set.

11. The method according to claim 10, characterized in that The receiving the sensing data sent by the at least one third-party AF includes: Receive the perception data transmitted by the at least one third-party AF through the user plane network element.

12. The method according to any one of claims 9 to 11, characterized in that: Also includes: Sending a response message in response to the first request message to a third network element, wherein the response message carries the sensing data set; Receive task deployment information for performing perception computing sent by the third network element, where the task deployment information is obtained based on the perception data set.

13. The method according to claim 12, characterized in that Also includes: The task deployment information is sent to the first network element, where the task deployment information includes: the perception data in the perception data set and information of the corresponding computing power nodes.

14. A data processing method, characterized in that: Applied to the third network element, including: Sending a first request message to the second network element, where the first request message is used to request perception data; A response message from the second network element in response to the first request message is received, where the response message carries a perception data set, and the perception data in the perception data set comes from a third-party application function entity AF.

15. The method according to claim 14, characterized in that Also includes: Determine task deployment information for performing perception computing according to the computing power information and the perception data set, wherein the computing power information includes information of computing power nodes that provide computing power support for the core network; The task deployment information is sent to the second network element.

16. The method according to claim 15, characterized in that Also includes: The computing power information is obtained from a storage network element, where the storage network element is used to store information about computing power nodes that provide computing power support for the core network.

17. The method according to any one of claims 14 to 16, characterized in that: Also includes: receiving a service request message from a UE, where the service request message is used to request perception computing; In response to the service request message, the first request message is sent to the second network element.

18. The method according to claim 17, characterized in that The service request message includes: at least one of the identifier of the UE, the service type, and the service requirement.

19. The method according to any one of claims 15 to 18, wherein the task deployment information comprises: The perception data and corresponding computing nodes in the perception data set.

20. A core network device, characterized in that: include: A first network element, a second network element and a third network element, wherein: The third network element is configured to send a first request message to the second network element in response to a service request message from the UE, wherein the service request message is used to request perception computing, and the first request message is used to request perception data; The second network element is configured to send a second request message to the corresponding third-party application function entity AF in response to the first request message, and after receiving the perception data fed back by the third-party AF to form a perception data set, feed it back to the third network element, where the second request message is used to request the perception data of each third-party AF; The third network element is further configured to determine task deployment information according to the received perception data set and the acquired computing power information, and send the task deployment information to the second network element; The second network element is further configured to send the received sensing data set and the task deployment information to the first network element; The first network element is configured to send the computing task corresponding to the perception data set to at least one computing power node according to the received task deployment information, and receive the computing results fed back by each computing power node.

21. The core network device according to claim 20, characterized in that: It also includes: a storage network element and a network element for outputting calculation results, wherein: The storage network element is configured to store information of computing nodes that provide computing support for the core network; The third network element is configured to obtain the computing power information from the storage network element; The first network element is further configured to analyze and summarize the calculation results and send them to the UE or the network element for outputting the calculation results.

22. A data processing device, characterized in that: Applied to the first network element, including: The first communication module is configured to distribute the computing task corresponding to the perception data set to at least one computing power node, and receive the computing result fed back by at least one computing power node, wherein the The perception data in the perception data set comes from the third-party application function entity AF.

23. A data processing device, characterized in that: Applied to the second network element, including: The second communication module is configured to send a perception data set to the first network element, wherein the perception data in the perception data set comes from a third-party application function entity AF.

24. A data processing device, characterized in that: Applied to the third network element, including: a third communication module, configured to send a first request message to a second network element, and receive a response message from the second network element in response to the first request message; Wherein, the first request message is used to request sensing data; The response message carries a perception data set, and the perception data in the perception data set comes from a third-party application function entity AF.

25. A core network element, characterized in that: include: Transceiver; processor; a memory storing computer executable instructions; Wherein, the processor is connected to the transceiver and the memory respectively, and is configured to load and execute the computer executable instructions to implement any method according to claims 1 to 7, or claims 8 to 13, or claims 14 to 19.

26. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer-readable storage medium stores executable instructions, and the executable instructions are loaded and executed by the processor to implement any one of the methods described in claims 1 to 10, or claims 8 to 13, or claims 14 to 19.

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