Task processing method and apparatus, device, storage medium, system, and program

Abstract

Embodiments of the present application relate to the technical field of communications, and provide a task processing method and apparatus, a device, a storage medium, a system, and a program. The method comprises: a network device receiving task data to be processed sent by at least one target terminal device; the network device allocating available computing resources to process said task data, and obtaining result data of each piece of said task data; and sending corresponding result data to each target terminal device. The method of the present application improves the task processing effect and efficiency of a terminal device.

Description

Task processing methods, apparatus, equipment, storage media, systems and programs

[0001] This application claims priority to Chinese Patent Application No. 202510138866.7, filed on February 7, 2025, entitled “Task Processing Method, Apparatus, Device, Storage Medium, System and Program”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of communication technology, and in particular to a task processing method, apparatus, device, storage medium, system and program. Background Technology

[0003] Currently, with the development of technology, the functions and application scenarios of terminal devices are constantly expanding and deepening, making the demand for complex computing on terminal devices increasingly important. However, terminal devices are limited by their own hardware, performance, and energy consumption control, resulting in relatively weak computing power. This limitation in computing power makes it difficult for terminal devices to effectively complete data processing tasks that require high computational capabilities.

[0004] Therefore, how to improve the task processing performance and efficiency of terminal devices is an urgent problem to be solved. Summary of the Invention

[0005] This application provides a task processing method, apparatus, device, storage medium, system, and program, which are applied in the field of communication technology and can improve the task processing effect and efficiency of terminal devices.

[0006] In a first aspect, embodiments of this application propose a task processing method applied to a network device. The method includes: receiving a task request sent by at least one terminal device, the task request being used to request the network device to process pending task data of the terminal device; sending a task request response to at least one terminal device, the task request response being used to indicate whether the task request is accepted; receiving pending task data sent by at least one target terminal device, the target terminal device being the terminal device that accepts the task request; allocating available computing resources to process the pending task data, obtaining result data for each of the pending task data, the pending task data including model training data, the result data including model training result data, or, the pending task data including extended reality (XR) rendering data, the result data including XR rendering result data; and sending corresponding result data to each of the target terminal devices.

[0007] Optionally, receiving a task request sent by at least one terminal device includes: receiving N task requests sent by N terminal devices, where N is an integer greater than or equal to 1; or, receiving M task requests sent by N terminal devices, where M is an integer greater than N.

[0008] Optionally, the task request response includes acceptance information or rejection information, wherein the acceptance information is used to indicate acceptance of the task request from the terminal device, and the rejection information is used to indicate rejection of the task request from the terminal device.

[0009] Optionally, the acceptance information includes the ACK character, and the rejection information includes the NACK character.

[0010] Optionally, the task request includes a task type and / or a priority corresponding to the task type, the task type and / or the priority corresponding to the task type being used to determine whether to accept the task request.

[0011] Optionally, the task request may also include a terminal device identifier.

[0012] Optionally, the task request response may also include the terminal device identifier corresponding to the acceptance information or the rejection information.

[0013] Optionally, the method further includes: sending time information to the at least one target terminal device, the time information being used to indicate the reporting time of the task data to be processed.

[0014] Optionally, the time information is carried in system messages, or Radio Resource Control (RRC) signaling, or Downlink Control Information (DCI).

[0015] Optionally, the time information includes a time window, which is used to instruct the target terminal device to report the task data to be processed within the time window.

[0016] Optionally, the task data to be processed is carried on the Physical Uplink Control Channel (PUCCH) and / or the Physical Uplink Shared Channel (PUSCH).

[0017] Optionally, the task data to be processed may be carried in uplink data information, uplink control information, or uplink data on the data plane.

[0018] Optionally, the step of allocating available computing resources to process the pending task data and obtaining result data for each pending task data includes: obtaining the number of tasks in the pending task data; and allocating a number of available computing resources corresponding to the number of tasks to process the pending task data and obtaining the result data for each pending task data.

[0019] Optionally, the step of allocating a number of available computing resources corresponding to the number of tasks to process the task data to be processed and obtaining the result data of each task data to be processed includes: obtaining the available computing resource stream corresponding to the network device; allocating a number of available computing resource streams corresponding to the number of tasks in the available computing resource stream corresponding to the network device to process the task data to be processed and obtaining the result data of each task data to be processed.

[0020] Optionally, the available computing resource flow corresponding to the network device is the available computing resource flow of the computing node corresponding to the network device.

[0021] Optionally, the step of allocating a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams corresponding to the network device to process the task data to be processed and to obtain the result data of each task data to be processed includes: obtaining the available computing resource streams of the first computing node in the computing nodes corresponding to the network device; if the number of tasks is less than or equal to the available computing resource streams of the first computing node, then allocating a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing node to process the task data to be processed and to obtain the result data of each task data to be processed.

[0022] Optionally, it further includes: if the number of tasks is greater than the available computing resource stream of the first computing node, then allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource stream of the first computing node and the available computing resource stream of the second computing node to process the task data to be processed, and obtain the result data of each task data to be processed, wherein the second computing node is a computing node other than the first computing node among the computing nodes corresponding to the network device.

[0023] Optionally, the step of allocating a number of available computing resource streams corresponding to the number of tasks in the available computing resource stream of the first computing node to process the task data to be processed and obtain the result data of each task data to be processed includes: obtaining the available computing resource stream of a first computing unit in the first computing node, wherein the first computing node includes at least two computing units; if the number of tasks is less than or equal to the available computing resource stream of the first computing unit, then allocating a number of available computing resource streams corresponding to the number of tasks in the available computing resource stream of the first computing unit to process the task data to be processed and obtain the result data of each task data to be processed; if the number of tasks is greater than the available computing resource stream of the first computing unit, then allocating a number of available computing resource streams corresponding to the number of tasks in the available computing resource stream of the first computing unit and the available computing resource stream of the second computing unit to process the task data to be processed and obtain the result data of each task data to be processed, wherein the second computing unit is a computing unit in the first computing node other than the first computing unit.

[0024] Optionally, it further includes: determining, based on the time information, a computing resource program for the first computing unit that processes the task data to be processed, wherein the first computing unit includes at least two computing resource programs.

[0025] Secondly, embodiments of this application propose a task processing apparatus, comprising: a first receiving module, configured to receive a task request sent by at least one terminal device, the task request being used to request a network device to process pending task data of the terminal device; a first sending module, configured to send a task request response to at least one terminal device, the task request response being used to indicate whether the task request is accepted; a second receiving module, configured to receive pending task data sent by at least one target terminal device, the target terminal device being the terminal device that accepts the task request; a processing module, configured to allocate available computing resources to process the pending task data, obtaining result data for each of the pending task data, the pending task data including model training data, the result data including model training result data, or the pending task data including extended reality (XR) rendering data, the result data including XR rendering result data; and a second sending module, configured to send corresponding result data to each of the target terminal devices.

[0026] Thirdly, embodiments of this application provide a task processing apparatus, the apparatus comprising: a processor, a transceiver, and a memory; the processor being communicatively connected to the transceiver and the memory respectively; the memory storing computer-executable instructions; the transceiver communicating with external devices; and the processor executing the computer-executable instructions stored in the memory to implement the method described in the first aspect or any possible implementation thereof.

[0027] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program or instructions that, when executed on a computer, cause the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0028] Fifthly, embodiments of this application provide a computer program product including a computer program, which, when run on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0029] Sixthly, this application provides a chip or chip system including at least one processor and a communication interface. The communication interface and the at least one processor are interconnected via a circuit. The at least one processor is used to run computer programs or instructions to perform the methods described in the first aspect or any possible implementation of the first aspect. The communication interface in the chip can be an input / output interface, pins, or circuits, etc.

[0030] In one possible implementation, the chip or chip system described above in this application further includes at least one memory storing instructions. The memory can be an internal storage unit of the chip, such as a register or cache, or it can be a storage unit of the chip itself (e.g., read-only memory, random access memory, etc.).

[0031] It should be understood that the second to sixth aspects of this application correspond to the technical solutions of the first aspect of this application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation are similar, and will not be repeated here.

[0032] The task processing method, apparatus, device, storage medium, system, and program provided in this application send task data to be processed to a network device through a target terminal device. The network device allocates available computing resources to process the task data to be processed, obtains result data for each task data to be processed, and sends the corresponding result data to each target terminal device, thereby breaking through the computing power limitation of the target terminal device and improving the task processing effect and efficiency of the terminal device. Attached Figure Description

[0033] Figure 1 is a schematic diagram of the structure of a task processing system applied in an embodiment of this application;

[0034] Figure 2 is a flowchart illustrating a task processing method provided in an embodiment of this application;

[0035] Figure 3 is a flowchart illustrating another task processing method provided in an embodiment of this application;

[0036] Figure 4 is a flowchart illustrating another task processing method provided in an embodiment of this application;

[0037] Figure 5 is a flowchart illustrating another task processing method provided in an embodiment of this application;

[0038] Figure 6 is a flowchart illustrating another task processing method provided in an embodiment of this application;

[0039] Figure 7 is a schematic diagram of a task processing device provided in an embodiment of this application;

[0040] Figure 8 is a schematic diagram of another task processing device provided in an embodiment of this application. Detailed Implementation

[0041] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "exemplary" or "for example" are used in the embodiments of this application to indicate that they are examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0042] In the embodiments of this application, terms such as "first" and "second" are used to distinguish identical or similar items with substantially the same function and purpose. For example, "first chip" and "second chip" are used only to distinguish different chips and do not limit their order of execution. Those skilled in the art will understand that terms such as "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different.

[0043] It should be noted that, in the embodiments of this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0044] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, a--c, bc, or abc, where a, b, and c can be single or multiple.

[0045] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0046] It should be noted that the phrase "at...time" in the embodiments of this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; the embodiments of this application do not specifically limit this. Furthermore, the display interface provided in the embodiments of this application is merely an example, and the display interface may include more or less content.

[0047] The technical solutions of this application can be applied to various communication systems, such as: Long Term Evolution (LTE) systems, LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, Universal Mobile Telecommunication System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX) communication systems, 5th Generation (5G) systems or new radio (NR) systems, and new systems that may emerge in the future, such as 6th Generation (6G) systems, etc.

[0048] To facilitate understanding of the embodiments of this application, the communication system applicable to the embodiments of this application will first be described in detail.

[0049] Figure 1 is a schematic diagram of a task processing system applied in an embodiment of this application. As shown in Figure 1, the task processing system includes: a network device and multiple terminal devices.

[0050] In this system, network devices and terminal devices can communicate via a wireless link. When the network device acts as a communication transmitter, the terminal device can act as a communication receiver; conversely, when the network device acts as a communication receiver, the terminal device can act as a communication transmitter. This application does not limit the number of network devices and terminal devices included in the communication system. Furthermore, it should be understood that Figure 1 is merely a schematic diagram, and the communication system may also include other network devices, which this application does not limit and are not shown in Figure 1.

[0051] The terminal equipment in this application embodiment can also be referred to as: user equipment (UE), mobile station (MS), mobile terminal (MT), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication equipment, user agent, or user device, etc.

[0052] Terminal devices can be devices that provide voice / data connectivity to users, such as handheld devices with wireless connectivity, in-vehicle devices, etc. Currently, examples of terminal devices include: mobile phones, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in self-driving vehicles, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, cellular phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), handheld devices with wireless communication capabilities, computing devices or other processing devices connected to wireless modems, in-vehicle devices, wearable devices, terminal devices in 5G networks, or future public land mobile communication networks. This application does not limit the scope to terminal devices in a network (PLMN), etc.

[0053] By way of example and not limitation, in this application, the terminal device can be a terminal device in an Internet of Things (IoT) system. The Internet of Things is an important component of future information technology development. Its main technical characteristic is connecting objects to networks through communication technologies, thereby realizing an intelligent network of human-machine interconnection and object-to-object interconnection. Exemplarily, the terminal device in the embodiments of this application can be a wearable device. Wearable devices, also known as wearable smart devices, are a general term for devices that apply wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that can be worn directly on the body or integrated into a user's clothing or accessories. Wearable devices are not merely hardware devices; they can also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly defined, wearable smart devices include those with comprehensive functions, large size, and the ability to achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those focused on a specific application function and requiring the use of other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0054] By way of example and not limitation, in the embodiments of this application, the terminal device can also be a terminal device in machine-type communication (MTC). Furthermore, the terminal device can also be an on-board module, on-board component, on-board chip, or on-board unit, etc., built into a vehicle as one or more components or units. The vehicle can implement the methods provided in this application through the built-in on-board module, on-board component, on-board chip, or on-board unit, etc. Therefore, the embodiments of this application can also be applied to vehicle networking, such as vehicle to everything (V2X), long term evolution-vehicle (LTE-V) technology, and vehicle-to-vehicle (V2V) technology.

[0055] The network equipment involved in this application can be a device that communicates with terminal devices. This network equipment can also be called an access network device or a wireless access network device. It can be a transmission reception point (TRP), an evolved NodeB (eNB or eNodeB) in an LTE system, a home base station (e.g., home evolved NodeB or home Node B, HNB), a base band unit (BBU), or a radio controller in a cloud radio access network (CRAN) scenario. Alternatively, the network equipment can be a relay station, access point, vehicle-mounted equipment, wearable devices, or network equipment in a 5G network or a network equipment in a future evolved PLMN network. It can also be an access point (AP) in a WLAN, or a gNB in ​​an NR system. The above-mentioned network equipment can also be a city base station, micro base station, pico base station, femtobase station, etc. This application does not limit this.

[0056] The network in which the network device resides possesses strong computing capabilities. These capabilities can be provided by computing nodes within the network or can be inherent to the network device itself. When the computing capabilities are provided by computing nodes within the network, the network device can connect to one or more computing nodes in the network. It distributes task data received from the terminal device to the computing nodes, enabling the nodes to process the task data. These computing nodes can be, for example, multi-access edge computing (MEC), distributed cloud nodes, quantum computing nodes, or computing hosts. Within a computing node, one or more computing units can be included to achieve concurrent processing of task data. These computing units can be, for example, central processing units (CPUs) or graphics processing units (GPUs).

[0057] In a network architecture, network devices may include centralized unit (CU) nodes, distributed unit (DU) nodes, RAN devices including CU nodes and DU nodes, or RAN devices including control plane CU nodes (CU-CP nodes), user plane CU nodes (CU-UP nodes), and DU nodes.

[0058] Network equipment provides services to cells. Terminal devices communicate with cells through transmission resources (e.g., frequency domain resources, or spectrum resources) allocated by the network equipment. The cell can belong to a macro base station (e.g., macro eNB or macro gNB) or to a base station corresponding to a small cell. Small cells can include: metro cells, micro cells, pico cells, femto cells, etc. These small cells have the characteristics of small coverage area and low transmission power, and are suitable for providing high-speed data transmission services.

[0059] Alternatively, the aforementioned devices and computing nodes that communicate with the terminal device can be regarded as a whole as the network device involved in this application, used to implement the functions of receiving task data sent by the terminal device and processing the task data.

[0060] Currently, the limited computing power of terminal devices is a prominent issue in several application scenarios. For example, in model training, the process involves extensive data computation and parameter adjustments, requiring robust computing capabilities. However, existing terminal devices often lack the necessary computing resources to meet the demands of model training, resulting in low efficiency and poor performance. Another example is Extended Reality (XR) scenarios, which require real-time processing and rendering of large amounts of image and scene data. When performing XR tasks on terminal devices with limited computing power, their insufficient resources cannot meet the high computational demands of XR rendering, hindering local XR rendering or leading to low rendering efficiency and poor rendering results.

[0061] Therefore, the limitation of computing power in terminal devices not only affects their functionality in specific fields but also restricts technological development and innovation across the entire industry, preventing many emerging applications based on powerful computing capabilities from being successfully implemented on terminal devices. Thus, overcoming the computing power limitations of terminal devices and improving their task processing performance and efficiency is an urgent problem to be solved.

[0062] The inventors have discovered that with the expansion and performance enhancement of data centers on the network side, and the widespread adoption of distributed computing and cloud computing technologies, the computing power of the network side is becoming increasingly powerful. Simultaneously, with the development of wireless communication technology, the transmission rate between terminal devices and network devices is becoming more efficient and stable, enabling the rapid transmission of large amounts of data in a short time. In view of this, this application provides a task processing method in which a target terminal device sends task data to a network device, the network device allocates available computing resources to process the task data, obtains result data for each task, and sends the corresponding result data to each target terminal device. This overcomes the computing power limitations of the target terminal device and improves the task processing effect and efficiency of the terminal device.

[0063] The task processing method of this application will be described in detail below with reference to the accompanying drawings. The execution subject of the embodiments shown in this application is a network device, and the specific form and number of each device shown are merely examples and should not constitute any limitation on the implementation of the method provided in this application.

[0064] The terminal device in this application embodiment can be the terminal device itself, or a chip, chip system, or processor that supports the terminal device in implementing task processing methods, or a logic module or software that can implement all or part of the terminal device's functions. The network device in this application embodiment can be the network device itself, or a chip, chip system, or processor that supports the network device in implementing task processing methods, or a logic module or software that can implement all or part of the network device's functions. This application does not impose specific limitations in this regard.

[0065] Figure 2 is a flowchart illustrating a task processing method provided in an embodiment of this application. As shown in Figure 2, the method may include:

[0066] S201. Receive task data to be processed sent by at least one target terminal device.

[0067] The target terminal device is any one of multiple terminal devices that are connected to the network device. The data to be processed can be, for example, model training data (model parameters, training data, etc.), XR rendering data, complex computational data, big data stream analysis data, or other data that requires high computing power to process.

[0068] Optionally, the task data to be processed can be sent to the network device by the target terminal device through uplink data information (such as uplink data information in the current 5G system), uplink control information (UCI) (such as UCI in the current 5G system), data plane uplink data, IoT protocol signaling (such as Message Queuing Telemetry Transport Signaling (MQTT), Constrained Application Protocol Signaling (CoAP), etc.), quantum communication signaling, etc. For example, the task data to be processed can be carried in a specific field, data segment, or data packet of any of the above-mentioned information, data, or signaling, and sent to the network device so that the network device receives the task data to be processed sent by at least one target terminal device.

[0069] For example, if the target terminal device uses uplink data reporting, taking the current 5G system as an example, the target terminal device can encapsulate the task data to be processed into appropriate data packets according to the specifications of the 5G protocol stack. These data packets will be mapped to the Physical Uplink Shared Channel (PUSCH) of the physical layer for transmission. The network device can extract the uplink data information from the PUSCH channel and further parse out the task data to be processed carried therein.

[0070] For example, if the target terminal device uses UCI reporting, taking a 5G system as a reference, UCI information can be carried on the Physical Uplink Control Channel (PUCCH) and / or PUSCH channel. The target terminal device can embed the task data to be processed into specific fields of the UCI. For example, the task data to be processed can be embedded into the Scheduling Request field (SR) or Channel State Information field (CSI) field in the UCI. The network device parses the UCI information from the PUCCH or PUSCH channel and then extracts the task data to be processed from it.

[0071] S202. Allocate available computing resources to process the data of the tasks to be processed, and obtain the result data of each task to be processed.

[0072] Available computing resources refer to the computing resources provided by computing nodes in the network. Network devices can determine the available computing resources that each computing node can provide based on the status of each computing node and its internal resources. For example, network devices can monitor the status of available computing resources in the network in real time according to the resource management system of their network, including but not limited to the computing capabilities of each computing node and each computing unit, the number of currently allocated computing nodes and computing units, the number of remaining allocable computing nodes and computing units, memory usage, and storage resources.

[0073] The result data for each task to be processed is related to that task data. For example, if the task data to be processed is model training data, the corresponding result data is model training result data (e.g., including the trained model, model parameters, etc.); if the task data to be processed is XR rendering data, the corresponding result data is XR rendering result data (e.g., the rendered XR image, etc.); if the task data to be processed is complex computational data, the corresponding result data is computational result data, etc. This application does not limit the specific types of the task data to be processed or the corresponding result data.

[0074] Network devices can allocate available computing resources to each pending task based on available computing resources and the data of tasks to be processed, taking into account factors such as the priority of each pending task, the availability of computing resources, and overall system performance optimization through task scheduling algorithms. For example, if the pending task data is rendering data with high real-time requirements, computing resources can be allocated to it first; if the pending task data is model training data with high computational complexity but relatively low real-time requirements, resources can be allocated reasonably while ensuring the overall performance of computing nodes. For example, available computing resources can be allocated based on the number of pending tasks; or, available computing resources can be allocated based on the task type of the pending task data; or, available computing resources can be allocated based on both the task type and the number of pending tasks. This application does not impose specific restrictions on how task scheduling is performed.

[0075] Optionally, the network device can also allocate different available computing resources to the data received at different times to obtain the result data of each task.

[0076] Optionally, network devices can also process the data of the tasks to be processed through collaborative processing between computing nodes and collaborative processing of computing units within computing nodes, so as to obtain the result data of each task to be processed.

[0077] S203. Send the corresponding result data to each target terminal device.

[0078] Network devices can determine which target terminal devices to send corresponding result data to based on the target terminal devices corresponding to each pending task data pair. For example, each pending task data pair may include an identifier for the target terminal device, and the network device will send the corresponding result data to the target terminal device corresponding to that identifier based on that identifier.

[0079] The network device sends the corresponding result data to each target terminal device, which can be achieved in a manner corresponding to the target terminal device sending the task data to be processed to the network device in the aforementioned step S201.

[0080] For example, if the task data to be processed is sent to the network device by the target terminal device via uplink data information, the network device can send the result data to the target terminal device via downlink data information; if the task data to be processed is sent to the network device by the target terminal device via UCI, the network device can send the result data to the target terminal device via downlink control information (DCI); if the task data to be processed is sent to the network device by the target terminal device via IoT protocol signaling, the network device can also send the result data to the target terminal device via the corresponding IoT protocol signaling; if the task data to be processed is sent to the network device by the target terminal device via quantum communication signaling, the network device can also send the result data to the target terminal device via the corresponding quantum communication signaling, and so on.

[0081] The method provided in this application embodiment sends task data to be processed to a network device through a target terminal device. The network device allocates available computing resources to process the task data to be processed, obtains result data for each task data to be processed, and sends the corresponding result data to each target terminal device, thereby breaking through the computing power limitation of the target terminal device and improving the task processing effect and efficiency of the terminal device.

[0082] The following section, taking the allocation of available computing resources based on the number of tasks as an example, details how the available computing resources are allocated in step S202 to process the task data to be processed and obtain the result data of each task data to be processed. Figure 3 is a flowchart illustrating another task processing method provided in an embodiment of this application. As shown in Figure 3, step S202 may specifically include:

[0083] S301, Number of tasks for which data to be processed is obtained.

[0084] Specifically, network devices can count the received pending task data to obtain the number of tasks. For example, a task counter can be set in the network device, and the counter will increment each time a new pending task data is received. Each pending task data can be treated as a single task, or the data can be grouped according to its characteristics before counting. For instance, received pending task data can be categorized by task type, grouping tasks of the same type together, and counting each group as a single task.

[0085] Optionally, the network device can also perform a duplicate check on the received task data. By comparing the task's identification information and the characteristics of the task data, it can determine whether there are duplicate tasks. If a duplicate task is found, the task counter will not count it again, but will treat it as the same task for subsequent processing to ensure the accuracy of the count.

[0086] S302. Based on the number of tasks, allocate a corresponding number of available computing resources to process the data of the tasks to be processed, and obtain the result data of each task to be processed.

[0087] One possible implementation is to categorize network devices according to task characteristics, such as high, medium, and low complexity. By combining this with a pre-defined resource requirement model, the types of resources required for different task categories are determined. Then, based on the task category, a corresponding number of available computing resources are allocated to process the task data, obtaining the results for each task.

[0088] Another possible implementation is to obtain the available computing resource streams corresponding to the network devices, and allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams corresponding to the network devices to process the data of the tasks to be processed, and obtain the result data of each task data.

[0089] In this implementation, the available computing resource flow corresponding to the network device can be the available computing resource flow possessed by the network device itself, or it can be the available computing resource flow possessed by the computing node associated with the network device. When the available computing resource flow corresponding to the network device is the available computing resource flow possessed by the computing node associated with the network device, an available computing resource flow can be, for example, a computing node, or an available computing resource flow can be, for example, a computing unit in a computing node.

[0090] Network devices can determine the appropriate available computing resource streams from among numerous available streams based on their current load, remaining processing capacity, and idle time, thus allocating a number of available computing resource streams corresponding to the number of tasks. These available computing resource streams then process the task data to obtain the results for each task. For example, one available computing resource stream can process one task.

[0091] Optionally, in determining available computing resource flows, network devices can prioritize available computing resource flows with lower loads and a high degree of matching between processing power and task requirements. For example, for simple text processing tasks, available computing resource flows with moderate processing power but currently light loads can be selected; for complex graphics rendering tasks, available computing resource flows with powerful graphics processing capabilities and relatively idle capacity can be prioritized.

[0092] The following section, taking the available computing resource stream corresponding to the network device as the available computing resource stream of the computing node corresponding to the network device as an example, details how to allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource stream corresponding to the network device to process the task data to be processed and obtain the result data of each task data to be processed. Figure 4 is a flowchart illustrating another task processing method provided in an embodiment of this application. As shown in Figure 4, the method may specifically include:

[0093] S401. Obtain the available computing resource flow of the first computing node in the computing nodes corresponding to the network device.

[0094] The first computing node is a computing node allocated by the network device for processing the data of the task to be processed. This first computing node may be determined by the network device based on factors such as the computing performance, stability, load, and idle time of each computing node, or it may be determined by combining the status of each computing node and the characteristics of the data of the task to be processed.

[0095] Optionally, the network device can monitor the status of each computing node to obtain the available computing resource flow in each computing node. After determining the first computing node, the network device can determine the available computing resource flow of the first computing node from the available computing resource flows in each computing node. Alternatively, after determining the first computing node, the network device can communicate and interact with the first computing node to actively obtain the available computing resource flow in the first computing node, or determine the available computing resource flow in the first computing node based on the available computing resource flow reported periodically or at regular intervals by the first computing node.

[0096] If the number of tasks is less than or equal to the available computing resource flow of the first computing node, it indicates that the available computing resource flow of the first computing node can meet the computing resource requirements of these tasks, and the pending task data received by the network device can be processed without the need for cooperation with other computing nodes, and step S402 is executed; if the number of tasks is greater than the available computing resource flow of the first computing node, it indicates that the available computing resource flow of the first computing node is insufficient to meet the computing resource requirements of these tasks, and cooperation with other computing nodes is required to process the pending task data received by the network device, and step S403 is executed.

[0097] S402. Allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing node to process the data of the tasks to be processed, and obtain the result data of each task to be processed.

[0098] One possible implementation is to directly allocate a number of available computing resource streams corresponding to the number of tasks from the available computing resource streams of the first computing node to process the data of the tasks to be processed. Based on the processing results of each available computing resource stream, the result data of each task to be processed is obtained. For example, one computing unit in the first computing node is one available computing resource stream, and each computing unit processes the data corresponding to one task to obtain the result data of each task to be processed.

[0099] Another possible implementation involves allocating resources based on the available computing resource streams of each computing unit in the first computing node. In this implementation, the allocation of a corresponding number of available computing resource streams from the available computing resource streams of the first computing node to process the task data can be achieved through the following sub-steps:

[0100] S4021. Obtain the available computing resource flow of the first computing unit in the first computing node.

[0101] The first computing node includes at least two computing units. Each computing unit includes at least one available computing resource stream. The first computing unit is any one of the at least two computing units.

[0102] Optionally, the network device can monitor the status of each computing unit in each computing node to obtain the available computing resource flow of each computing unit in each computing node. After determining the first computing node, the network device can obtain the available computing resource flow belonging to the first computing unit from the available computing resource flow in the first computing node. Alternatively, after determining the first computing node, the network device can communicate and interact with the first computing node to actively obtain the available computing resource flow of the first computing unit in the first computing node, or determine the available computing resource flow of the first computing unit in the first computing node based on the available computing resource flow reported periodically or at regular intervals by the first computing node.

[0103] If the number of tasks is less than or equal to the available computing resource flow of the first computing unit, it indicates that the available computing resource flow of the first computing unit can meet the computing resource requirements of these tasks, and the pending task data received by the network device can be processed without the need for collaboration with other computing units in the first computing node, and step S4022 is executed; if the number of tasks is greater than the available computing resource flow of the first computing unit, it indicates that the available computing resource flow of the first computing unit is insufficient to meet the computing resource requirements of these tasks, and collaboration with other computing units in the first computing node is required to process the pending task data received by the network device, and step S4023 is executed.

[0104] S4022. Allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing unit to process the data of the tasks to be processed, and obtain the result data of each data of the tasks to be processed.

[0105] In this step, the network device can directly allocate a number of available computing resource streams corresponding to the number of tasks to process the data to be processed based on the computing performance, stability, load, and idle time of each available computing resource stream in the first computing unit, and obtain the result data of each data to be processed.

[0106] S4023. Allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing unit and the second computing unit to process the data of the tasks to be processed, and obtain the result data of each data of the tasks to be processed.

[0107] The second computing unit is the computing unit in the first computing node other than the first computing unit.

[0108] Network devices can formulate allocation schemes based on the available resource flows and the number of tasks in two computing units. For example, all available resource flows in the first computing unit can be allocated to some tasks, and then, based on the remaining number of tasks, a corresponding number of available resource flows from the second computing unit can be selected and allocated to the remaining tasks. Alternatively, the network device can calculate the current load of the two computing units and, according to the principle of load balancing, allocate tasks to the computing unit with the lower load. If the load of the first computing unit is lower than that of the second computing unit, available computing resource flows are first allocated from the first computing unit to process some tasks. As the load of the first computing unit increases, when a certain threshold is reached, available computing resource flows are then allocated from the second computing unit to process subsequent tasks, ensuring that the load of the two computing units is as balanced as possible.

[0109] After the network devices complete the allocation, the first computing unit and the second computing unit allocate computing resources to the tasks according to the number of tasks allocated, process the data of the tasks to be processed, and obtain the result data of each task to be processed.

[0110] S403. Allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing node and the second computing node to process the data of the tasks to be processed, and obtain the result data of each task to be processed.

[0111] The second computing node is the computing node other than the first computing node among the computing nodes corresponding to the network device.

[0112] Network devices can formulate allocation schemes based on the available resource flows and the number of tasks on two computing nodes. For example, all available resource flows on the first computing node can be allocated to a portion of the tasks, and then, based on the remaining number of tasks, a corresponding number of available resource flows on the second computing node can be selected and allocated to the remaining tasks. Alternatively, the network device can calculate the current load of the two computing nodes and, according to the principle of load balancing, allocate tasks to the computing node with the lower load. If the load of the first computing node is lower than that of the second computing node, available computing resource flows are first allocated to the first computing node to process some tasks. As the load of the first computing node increases, when a certain threshold is reached, available computing resource flows are then allocated to the second computing node to process subsequent tasks, ensuring that the load on the two computing nodes is as balanced as possible.

[0113] After the network devices are allocated, the first computing node and the second computing node allocate computing resources to the tasks according to the number of tasks allocated, process the data of the tasks to be processed, and obtain the result data of each task to be processed.

[0114] For example, the first computing node and the second computing node mentioned in the above embodiments can be computing hosts. The first computing node is computing host 1 under the network corresponding to the network device, and the second computing node is computing host 2 under the network corresponding to the network device. The computing unit in the computing node can be a GPU card; therefore, the first computing unit can be GPU card 1, and the second computing unit can be GPU card 2. When computing host 1 and computing host 2 need to collaboratively process the task data to be processed, multi-node collaboration can be achieved through the computing host's Message Passing Interface (MPI) to coordinate the GPU resources of computing host 1 and computing host 2 for distributed computing.

[0115] The method provided in this application embodiment obtains the available computing resource flow of the first computing node in the computing node corresponding to the network device. If the number of tasks is less than or equal to the available computing resource flow of the first computing unit, then a number of available computing resource flows corresponding to the number of tasks are allocated in the available computing resource flow of the first computing node to process the task data to be processed, thereby obtaining the result data of each task data to be processed. If the number of tasks is greater than the available computing resource flow of the first computing unit, then a number of available computing resource flows corresponding to the number of tasks are allocated in the available computing resource flow of the first computing node and the available computing resource flow of the second computing node to process the task data to be processed, thereby obtaining the result data of each task data to be processed, thereby improving the processing efficiency and processing effect of the task data to be processed.

[0116] In one possible implementation, the network device may also send time information in advance to at least one target terminal device, wherein the time information is used to indicate the reporting time of the task data to be processed, that is, to indicate the time when each target terminal device sends the task data to be processed to the network device.

[0117] The time information can be, for example, indicating a specific moment or a time window (i.e., a certain period of time). When the time information indicates a specific moment, it can include that moment to instruct the target terminal device receiving the time information to send the task data to be processed to the network device at that moment. When the time information indicates a time window, it can include that time window to instruct the target terminal device receiving the time information to send the task data to be processed to the network device at any time within that time window.

[0118] Optionally, the time information may also include an initial time (or reference time), which is used in combination with the time included in the time information or a time window to explicitly indicate a specific time and time window. For example, assuming the initial time is 0, and the time included in the time information is 20ms, the target terminal device is instructed to send the task data to be processed to the network device 20ms after the time has elapsed, with time 0 as the reference; or if the time included in the time information is between 20ms and 30ms, the target terminal device is instructed to send the task data to be processed to the network device at any time before the time has elapsed 30ms after the time has elapsed 20ms, with time 0 as the reference.

[0119] Alternatively, this initial time can be pre-configured in the network device and the terminal device. Or, the initial time can be pre-configured in the network device, which synchronizes it with the terminal device before sending time information, etc.

[0120] Optionally, the time information can be carried in system messages, Radio Resource Control (RRC) signaling, or DCI, etc. For example, if the time information is carried in a system message sent to the target terminal device, the time information can be encoded in a specific field of the system message, and the network device periodically broadcasts system messages. When the target terminal device powers on or accesses the network, it receives and parses the system messages listened to from the network device to obtain the time information. If the time information is carried in an RRC sent to the target terminal device, the time information can be carried in a specific RRC message, such as a connection reconfiguration message. The network device sends the time information to the target terminal device via RRC signaling based on changes in the target terminal device's status or system requirements. If the time information is carried in a DCI sent to the target terminal device, the network device can set time-related parameters in the DCI according to service requirements and resource availability, and the terminal device obtains the time information by parsing the DCI.

[0121] In the implementation where the network device pre-sends time information to at least one target terminal device, optionally, the network device can also determine the computing resource program of the first computing unit for processing each task data based on the time information. The first computing unit includes at least two computing resource programs.

[0122] In this implementation, each target terminal device can determine the time when it sends its own pending task data to the network device based on the received time information, and then send its corresponding pending task data at the corresponding time. On the network device side, the network device will receive multiple pending task data sent by multiple target terminal devices at different times.

[0123] Taking time information, including time windows, as an example, multiple pending task data received by the network device in the first time window can be allocated to the first computing resource program of the first computing unit that processes each pending task data; multiple pending task data received by the network device in the next time window can be allocated to any other computing resource program of the first computing unit that processes each pending task data.

[0124] For example, taking the time window included in the time information as Δt, and the initial time as T by default, the multiple pending task data received by the network device within the time period T+Δt are assigned to the first computing resource program of the first computing unit that processes each pending task data; the multiple pending task data received within the time period T+2Δt are assigned to the second computing resource program of the first computing unit that processes each pending task data; the multiple pending task data received within the time period T+3Δt are assigned to the third computing resource program of the first computing unit that processes each pending task data, and so on.

[0125] By using different computing resource programs and utilizing the corresponding available computing resource streams, multiple pending task data corresponding to each computing resource program are processed to obtain the processing results of these multiple pending task data.

[0126] Optionally, when multiple computing units need to process the data of the task to be processed in a coordinated manner, the above-mentioned computing resource program and the allocation of available computing resource streams can be executed for each computing unit so that the processing of multiple data of the task to be processed can be completed through the coordination of multiple computing units, and the processing results of the multiple data of the task to be processed can be obtained.

[0127] The method provided in this application embodiment allows a network device to pre-instruct each target terminal device on the time to send data to be processed, thereby allocating computing resources to process multiple data to be processed received at different times, which improves the parallel efficiency of the data to be processed and thus enhances the task processing efficiency of the target terminal devices.

[0128] Figure 5 is a flowchart illustrating another task processing method provided in an embodiment of this application. As shown in Figure 5, the method may further include:

[0129] S501, Receive a task request sent by at least one terminal device.

[0130] The task request is used to request the network device to process the pending task data of the terminal device. After receiving the task request from the terminal device, the network device can determine whether to accept and process the pending task data corresponding to the task request.

[0131] One possible implementation is that network devices can determine whether to accept and process the pending task data corresponding to a task request based on their corresponding computing resources. For example, if the network device's computing resource status indicators, such as CPU utilization, GPU utilization, remaining memory space, and network bandwidth usage, are all within normal ranges, and there are sufficient idle computing resources available for allocation, then the network device can determine that it is capable of processing new pending task data and can accept the task request sent by the terminal device. Conversely, if certain computing resource status indicators are close to or exceed thresholds, such as GPU utilization reaching over 90% and remaining memory space less than 10%, it indicates that current computing resources are strained and processing capacity is nearing saturation. In this case, to ensure the normal processing of existing tasks and the overall stability of the system, the network device can refuse to accept the task request.

[0132] Another possible implementation is that the network device can determine whether to accept and process the task data corresponding to the task request based on the task request. For example, the network device can perform in-depth analysis of key information in the task request (such as at least one of the following: task type, task priority, expected data volume, and required processing time). If the task type matches the task type that the network device is good at processing, the network device can accept the task request; and / or, if the task corresponding to the task request has a high priority, the network device can accept the task request; and / or, the network device can estimate the impact of the expected data volume and required processing time of the task corresponding to the task request on its own resources, and if the impact is within the range that its own resources can bear, the network device can accept the task request, etc.

[0133] In this implementation, the task request may include at least one of the following: task type, priority corresponding to the task type, etc., so that the network device can determine whether to accept the task request based on the task type and priority corresponding to the task type in the task request.

[0134] Optionally, the task request may also include the identifier of the terminal device that sent the task request (e.g., the name, identity ID, etc. of the terminal device), so that the network device can determine which terminal device the task request comes from, and further facilitate the network device to return task request responses to each terminal device for each task request, ensuring the accuracy and efficiency of the network device sending task request responses to the terminal devices.

[0135] Specifically, a task request can be sent by the target terminal device to the network device via uplink data information (such as uplink data information in current 5G systems), UCI (such as UCI in current 5G systems), data plane uplink data, IoT protocol signaling (such as MQTT, CoAP, etc.), quantum communication signaling, etc. For example, the task request can be carried in a specific field, data segment, or data packet of any of the above-mentioned information, data, or signaling, and sent to the network device so that the network device can receive the task data to be processed sent by at least one target terminal device. This task request can be carried on the Physical Uplink Control Channel (PUCCH) and / or the Physical Uplink Shared Channel (PUSCH).

[0136] Optionally, each terminal device may send only one task request or send multiple task requests. That is, the network device may receive N task requests from N terminal devices, where N is an integer greater than or equal to 1 (i.e., each terminal device sends only one task request); or, the network device may receive M task requests from N terminal devices, where M is an integer greater than N (i.e., at least one terminal device sends at least two task requests). Correspondingly, the pending task data is similar to the task requests; each target terminal device may send only one pending task data or send multiple pending task data, which will not be elaborated further.

[0137] S502, Send a task request response to at least one terminal device.

[0138] The task request response is used to indicate whether a terminal device is the target terminal device; that is, it indicates whether the network device accepts the task requests sent by each terminal device. If the task request response indicates that the network device accepts the task request sent by the terminal device, then the terminal device is the target terminal device and can subsequently send the pending task data corresponding to its task request to the network device. If the task request response indicates that the network device rejects the task request sent by the terminal device, then the terminal device is not the target terminal device and cannot subsequently send the pending task data corresponding to its task request to the network device.

[0139] Optionally, the task request response may include acceptance or rejection information. Acceptance information indicates that the terminal device is the target terminal device, while rejection information indicates that the terminal device is not the target terminal device. For example, the acceptance information may include an ACK character, indicating that the network device accepts the task request; the rejection information may include a NACK character, indicating that the network device rejects the task request. Alternatively, the acceptance information may include a 1, indicating that the network device accepts the task request; the rejection information may include a 0, indicating that the network device rejects the task request, and so on. It should be understood that the specific implementation of the acceptance and rejection information can be set according to actual needs and is not limited to the aforementioned ACK / NACK characters or 1 / 0 implementation.

[0140] Optionally, the task request response may also include the identifier of the terminal device that sent the task request (e.g., the name, identity ID, etc. of the terminal device), so that the network device can determine which terminal device to send the task request response to, ensuring the accuracy and efficiency of the network device in sending the task request response to the terminal device.

[0141] Optionally, the time information in the foregoing embodiments may also be included in the task request response.

[0142] Specifically, the task request response is sent by the target terminal device to the network device via uplink data information (such as uplink data information in current 5G systems), UCI (such as UCI in current 5G systems), data plane uplink data, IoT protocol signaling (such as MQTT, CoAP, etc.), quantum communication signaling, etc. For example, the task request can be carried in a specific field, data segment, or data packet of any of the above-mentioned information, data, or signaling, and sent to the network device so that the network device can receive the task data to be processed sent by at least one target terminal device. This task request can be carried on the Physical Uplink Control Channel (PUCCH) and / or the Physical Uplink Shared Channel (PUSCH).

[0143] Specifically, the task request response sent by the network device to each terminal device can be implemented in a manner corresponding to the task request sent by the terminal device to the network device in the aforementioned step S501.

[0144] For example, if the task request is sent by the terminal device to the network device via uplink data information, the network device can send the task request response to the terminal device via downlink data information; if the task request is sent by the terminal device to the network device via UCI, the network device can send the task request response to the terminal device via DCI; if the task request is sent by the terminal device to the network device via IoT protocol signaling, the network device can also send the task request response to the terminal device via the corresponding IoT protocol signaling; if the task request is sent by the terminal device to the network device via quantum communication signaling, the network device can also send the task request response to the terminal device via the corresponding quantum communication signaling, and so on.

[0145] The method provided in this application embodiment involves a network device receiving task requests from at least one terminal device and determining whether to approve each terminal device's task request based on its own scheduling algorithm. Depending on whether the task request from each terminal device is accepted or rejected, a task request response corresponding to each task request is sent to each terminal device to indicate whether each terminal device can subsequently process its pending task data using network-side computing resources. This improves the network device's scheduling efficiency for pending task data from multiple terminal devices, further enhancing the task processing effect and efficiency of the terminal devices.

[0146] For ease of understanding, a possible complete flow of the task processing method in the foregoing embodiments is described below as an example. Figure 6 is a schematic flowchart of another task processing method provided in an embodiment of this application. As shown in Figure 6, the method may include:

[0147] S601. At least one terminal device sends a task request to the network device.

[0148] Accordingly, the network device receives a task request sent by at least one terminal device.

[0149] For example, terminal devices 1 through n all send task requests to the network device. The task request sent by terminal device 1 is task request Q1, the task request sent by terminal device 2 is task request Q2, and so on, with the task request sent by terminal device n being task request Qn.

[0150] This step can be referred to as step S501 above, and will not be repeated here.

[0151] S602, The network device determines the task request response corresponding to each task request.

[0152] The task request response is used to instruct the network device to accept or reject the task request.

[0153] For example, the network device only accepts task requests from terminal device 1 and terminal device 2.

[0154] S603. The network device sends a task request response to at least one terminal device.

[0155] Accordingly, at least one terminal device receives a task request response sent by the network device.

[0156] For example, the network device only sends a task request response indicating acceptance of the task request to terminal device 1 and terminal device 2. That is, the task request response sent to terminal device 1 and terminal device 2 includes the ACK field, while the task request response sent to other terminal devices includes the NACK field.

[0157] This step can be referred to as step S502 above, and will not be repeated here.

[0158] S604. The network device sends time information to the target terminal device.

[0159] Correspondingly, the target terminal device receives the time information sent by the network device.

[0160] For example, the time information indicates a time window Δt, the reference time (i.e. the initial time) of which is the time T when the network device sends the task request response.

[0161] S605. At least one target terminal device sends pending task data to the network device based on time information.

[0162] Correspondingly, the network device receives pending task data sent by at least one target terminal device based on time information.

[0163] For example, terminal device 1 and terminal device 2 are target terminal devices, and they send task data D1 and task data D2 to the network device within the time window Δt.

[0164] S606, The network device allocates computing resources to each pending task based on time information.

[0165] S607. The network device obtains the available computing resource flow of the first computing node in the computing node corresponding to the network device.

[0166] If the number of tasks is less than or equal to the available computing resources of the first computing node, proceed to steps S608-S610; if the number of tasks is greater than the available computing resources of the first computing node, proceed to step S611.

[0167] S608. Obtain the available computing resource flow of the first computing unit in the first computing node.

[0168] If the number of tasks is less than or equal to the available computing resource flow of the first computing unit, proceed to step S609; if the number of tasks is greater than the available computing resource flow of the first computing unit, proceed to step S610.

[0169] S609. Allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing unit to process the data to be processed, and use the computing resource program corresponding to each data to be processed to obtain the result data of each data to be processed.

[0170] Perform step S612.

[0171] S610. Allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing unit and the second computing unit to process the data to be processed, and use the computing resource program corresponding to each data to be processed to obtain the result data of each data to be processed.

[0172] Perform step S612.

[0173] S611. Allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing node and the second computing node to process the data to be processed, and use the computing resource program corresponding to each data to be processed to obtain the result data of each data to be processed.

[0174] Perform step S612.

[0175] S612, The network device sends the corresponding result data to each target terminal device.

[0176] Correspondingly, each target terminal device receives the result data corresponding to its target terminal device sent by the network device.

[0177] For example, send result data F1 to terminal device 1, send result data F2 to terminal device 2, and send result data Fn to terminal device n.

[0178] Figure 7 is a schematic diagram of a task processing device provided in an embodiment of this application. It is understood that this task processing device can correspondingly implement the operations or steps of the network devices in the aforementioned method embodiments. The task processing device can be a network device or a component configurable on a network device, such as a chip or chip module. As shown in Figure 7, the task processing device may include: a first receiving module 11, a first sending module 12, a second receiving module 13, a processing module 14, and a second sending module 15. Optionally, the first receiving module 11, the first sending module 12, the second receiving module 13, and the second sending module 15 can be integrated into the transceiver module or separated.

[0179] The first receiving module 11 is used to receive a task request sent by at least one terminal device, the task request being used to request the network device to process the task data to be processed by the terminal device.

[0180] The first sending module 12 is used to send a task request response to at least one terminal device, the task request response being used to indicate whether the task request is accepted.

[0181] The second receiving module 13 is used to receive task data to be processed sent by at least one target terminal device, wherein the target terminal device is the terminal device that accepts the task request.

[0182] The processing module 14 is used to allocate available computing resources to process the task data to be processed and obtain the result data of each task data to be processed. The task data to be processed includes model training data and the result data includes model training result data, or the task data to be processed includes extended reality XR rendering data and the result data includes XR rendering result data.

[0183] The second sending module 15 is used to send the corresponding result data to each target terminal device.

[0184] Optionally, the first receiving module 11 is specifically used to receive N task requests sent by N terminal devices, where N is an integer greater than or equal to 1. Alternatively, it can receive M task requests sent by N terminal devices, where M is an integer greater than N.

[0185] Optionally, the task request response may include acceptance information or rejection information. Acceptance information indicates that the task request from the terminal device is accepted, while rejection information indicates that the task request from the terminal device is rejected.

[0186] Optionally, the accept message includes the ACK character, and the reject message includes the NACK character.

[0187] Optionally, the task request may include a task type and / or a priority corresponding to the task type. The task type and / or the priority corresponding to the task type are used to determine whether to accept the task request.

[0188] Optionally, the task request may also include the terminal device identifier.

[0189] Optionally, the task request response may also include the terminal device identifier corresponding to the acceptance or rejection information.

[0190] Optionally, the first sending module 12 is also used to send time information to at least one target terminal device, the time information being used to indicate the reporting time of the task data to be processed.

[0191] Optionally, time information may be carried in system messages, radio resource control signaling (RRC), or downlink control information (DCI).

[0192] Optionally, the time information includes a time window, which is used to instruct the target terminal device to report the data of the task to be processed within the time window.

[0193] Optionally, the task data to be processed is carried on the Physical Uplink Control Channel (PUCCH) and / or the Physical Uplink Shared Channel (PUSCH).

[0194] Optionally, the data to be processed can be carried in uplink data information, uplink control information, or uplink data on the data plane.

[0195] Optionally, the processing module 14 is specifically used to obtain the number of tasks to be processed. Based on the number of tasks, it allocates a corresponding number of available computing resources to process the task data and obtains the result data for each task.

[0196] Optionally, processing module 14 is specifically used to obtain the available computing resource streams corresponding to the network devices. It allocates a number of available computing resource streams corresponding to the number of tasks from the available computing resource streams corresponding to the network devices to process the data of the tasks to be processed, and obtains the result data of each task.

[0197] Optionally, the available computing resource flow corresponding to the network device is the available computing resource flow of the computing node corresponding to the network device.

[0198] Optionally, the processing module 14 is specifically used to obtain the available computing resource stream of the first computing node among the computing nodes corresponding to the network device. If the number of tasks is less than or equal to the available computing resource stream of the first computing node, then a number of available computing resource streams corresponding to the number of tasks are allocated in the available computing resource stream of the first computing node to process the task data to be processed, and the result data of each task data to be processed is obtained.

[0199] Optionally, the processing module 14 is further configured to allocate a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing node and the available computing resource streams of the second computing node to process the task data to be processed, and obtain the result data of each task data to be processed, if the number of tasks is greater than the available computing resource stream of the first computing node. The second computing node is a computing node other than the first computing node in the computing nodes corresponding to the network device.

[0200] Optionally, processing module 14 is specifically used to obtain the available computing resource streams of the first computing unit in the first computing node. If the number of tasks is less than or equal to the available computing resource streams of the first computing unit, then a number of available computing resource streams corresponding to the number of tasks are allocated in the available computing resource streams of the first computing unit to process the task data to be processed, and the result data of each task data to be processed is obtained. If the number of tasks is greater than the available computing resource streams of the first computing unit, then a number of available computing resource streams corresponding to the number of tasks are allocated in the available computing resource streams of the first computing unit and the available computing resource streams of the second computing unit to process the task data to be processed, and the result data of each task data to be processed is obtained. The first computing node includes at least two computing units, and the second computing unit is a computing unit in the first computing node other than the first computing unit.

[0201] Optionally, the processing module 14 is also used to determine the computing resource program of the first computing unit for processing the task data to be processed based on the time information, wherein the first computing unit includes at least two computing resource programs.

[0202] The task processing device provided in this embodiment can execute the actions of the network device in the aforementioned method embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0203] Optionally, the task processing device may further include at least one storage module, which may include data and / or instructions. Other modules in the task processing device (e.g., receiving module, sending module, processing module, etc.) may read the data and / or instructions in the storage module to implement the corresponding method.

[0204] It should be noted that, in the above embodiments, the transmitting module can actually be a transmitter, and the receiving module can actually be a receiver, or the transmitting and receiving modules can be implemented through a transceiver, or through a communication port. The processing module can be implemented in software via a processing element, or in hardware. For example, the processing module can be at least one separately established processing element, or it can be integrated into a chip in the aforementioned device. Alternatively, it can be stored as program code in the memory of the aforementioned device, and its functions can be called and executed by a processing element of the aforementioned device. Furthermore, all or part of these modules can be integrated together, or they can be implemented independently. The processing element mentioned here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions.

[0205] For example, these modules can be one or more integrated circuits configured to implement the above methods, such as one or more application-specific integrated circuits (ASICs), one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs). As another example, when a module is implemented by a processing element calling program code, that processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together to implement a system-on-a-chip (SOC).

[0206] Figure 8 is a schematic diagram of another task processing device provided in an embodiment of this application. As shown in Figure 8, the communication device 800 may include at least one processor 801, a memory 802, and a transceiver 803. The processor 801, transceiver 803, and memory 802 communicate with each other through an internal connection path. The memory 802 is used to store instructions, and the processor 801 is used to execute the instructions stored in the memory 802 to control the transceiver 803 to send and / or receive instruction information.

[0207] The communication device can be, for example, the network device mentioned above, or the terminal device mentioned above.

[0208] It should be understood that the communication device can correspond to the terminal device in the above method embodiments or the network device in the above method embodiments. It can be used to execute the various steps and / or processes executed by the terminal device or the network device in the above method embodiments. Optionally, the memory 802 may include read-only memory and random access memory, and provide instructions and data to the processor 801. A portion of the memory 802 may also include non-volatile random access memory. The memory 802 can be a separate device or integrated into the processor 801. The processor 801 can be used to execute the instructions stored in the memory 802, and when the processor 801 executes the instructions stored in the memory, the processor 801 is used to execute the various steps and / or processes of the above method embodiments.

[0209] The transceiver 803 may include a transmitter and a receiver. The transceiver 803 may further include an antenna, which may be one or more. The processor 801 and memory 802 may be integrated with the transceiver 803 on different chips. For example, the processor 801 and memory 802 may be integrated in a baseband chip, and the transceiver 803 may be integrated in a radio frequency chip. Alternatively, the processor 801 and memory 802 may be integrated with the transceiver 803 on the same chip. This application does not limit this.

[0210] Optionally, the communication device is a component configured in a terminal device or network device, such as a chip or chip system.

[0211] The transceiver 803 can also be a communication interface, such as an input interface and / or an output interface, circuitry, etc. The transceiver 803, processor 801, and memory 802 can all be integrated into the same chip, such as within a baseband chip.

[0212] It should be understood that the aforementioned communication device can be one or more chips. For example, the communication device can be a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a system-on-chip (SoC), a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), a microcontroller unit (MCU), a programmable logic device (PLD), or other integrated chips.

[0213] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0214] It should be noted that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuitry in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0215] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memories described herein are intended to include, but are not limited to, these and any other suitable types of memory.

[0216] This application also provides a task processing system, which includes the terminal device and network device described in the foregoing embodiments.

[0217] This application also provides a chip that stores a computer program, which, when executed by the chip, implements the methods described in the above embodiments.

[0218] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores program instructions, and when the program instructions are executed, the method in the above embodiments is implemented.

[0219] This application also provides a computer program product including executable instructions stored in a readable storage medium. At least one processor of a communication device can read the executable instructions from the readable storage medium, and the execution of the executable instructions by the at least one processor enables the communication device to implement the task processing methods provided in the various embodiments described above.

[0220] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A task processing method, characterized in that, The method is applied to a network device, and the method includes: The network device receives a task request sent by at least one terminal device, the task request being used to request the network device to process the pending task data of the terminal device. Send a task request response to at least one of the terminal devices, the task request response indicating whether the task request is accepted; Receive task data to be processed sent by at least one target terminal device, wherein the target terminal device is the terminal device that accepts the task request; Allocate available computing resources to process the task data to be processed, and obtain result data for each task data to be processed. The task data to be processed includes model training data, and the result data includes model training result data. Alternatively, the task data to be processed includes extended reality XR rendering data, and the result data includes XR rendering result data. Send the corresponding result data to each of the target terminal devices.

2. The method according to claim 1, characterized in that, Receiving a task request sent by at least one terminal device includes: Receive N task requests sent by N terminal devices, where N is an integer greater than or equal to 1; or, Receive M task requests sent by N terminal devices, where M is an integer greater than N.

3. The method according to claim 2, characterized in that, The task request response includes an acceptance message or a rejection message. The acceptance message indicates that the task request from the terminal device is accepted, and the rejection message indicates that the task request from the terminal device is rejected.

4. The method according to claim 3, characterized in that, The acceptance message includes the ACK character, and the rejection message includes the NACK character.

5. The method according to claim 4, characterized in that, The task request includes a task type and / or a priority corresponding to the task type. The task type and / or the priority corresponding to the task type are used to determine whether to accept the task request.

6. The method according to claim 5, characterized in that, The task request also includes a terminal device identifier.

7. The method according to claim 6, characterized in that, The task request response also includes the terminal device identifier corresponding to the acceptance information or the rejection information.

8. The method according to any one of claims 1-7, characterized in that, The method further includes: Time information is sent to the at least one target terminal device, the time information being used to indicate the reporting time of the task data to be processed.

9. The method according to claim 8, characterized in that, The time information is carried in system messages, or Radio Resource Control (RRC) messages, or Downlink Control Information (DCI) messages.

10. The method according to claim 9, characterized in that, The time information includes a time window, which is used to instruct the target terminal device to report the pending task data within the time window.

11. The method according to claim 10, characterized in that, The task data to be processed is carried on the Physical Uplink Control Channel (PUCCH) and / or the Physical Uplink Shared Channel (PUSCH).

12. The method according to claim 11, characterized in that, The task data to be processed is carried in uplink data information, uplink control information, or uplink data on the data plane.

13. The method according to claim 12, characterized in that, The allocation of available computing resources to process the pending task data and obtain result data for each pending task data includes: The number of tasks for which the pending task data is obtained; Based on the number of tasks, allocate a corresponding number of available computing resources to process the task data to be processed, and obtain the result data for each task data to be processed.

14. The method according to claim 13, characterized in that, The step of allocating a corresponding number of available computing resources to process the pending task data based on the number of tasks, and obtaining the result data for each of the pending task data, includes: Obtain the available computing resource stream corresponding to the network device; The number of available computing resource streams corresponding to the number of tasks are allocated from the available computing resource streams corresponding to the network device to process the task data to be processed, and the result data of each task data to be processed is obtained.

15. The method according to claim 14, characterized in that, The available computing resource flow corresponding to the network device is the available computing resource flow of the computing node corresponding to the network device.

16. The method according to claim 15, characterized in that, The process of allocating a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams corresponding to the network device to process the task data to be processed, and obtaining the result data of each task data to be processed, includes: Obtain the available computing resource flow of the first computing node among the computing nodes corresponding to the network device; If the number of tasks is less than or equal to the available computing resource stream of the first computing node, then a number of available computing resource streams corresponding to the number of tasks are allocated in the available computing resource stream of the first computing node to process the task data to be processed, and the result data of each task data to be processed is obtained.

17. The method according to claim 16, characterized in that, Also includes: If the number of tasks is greater than the available computing resource stream of the first computing node, then a number of available computing resource streams corresponding to the number of tasks are allocated in the available computing resource stream of the first computing node and the available computing resource stream of the second computing node to process the task data to be processed, and obtain the result data of each task data to be processed. The second computing node is the computing node other than the first computing node among the computing nodes corresponding to the network device.

18. The method according to claim 16, characterized in that, The step of allocating a number of available computing resource streams corresponding to the number of tasks in the available computing resource streams of the first computing node to process the task data to be processed, and obtaining the result data of each task data to be processed, includes: Obtain the available computing resource flow of the first computing unit in the first computing node, wherein the first computing node includes at least two computing units; If the number of tasks is less than or equal to the available computing resource stream of the first computing unit, then a number of available computing resource streams corresponding to the number of tasks are allocated in the available computing resource stream of the first computing unit to process the task data to be processed, and the result data of each task data to be processed is obtained. If the number of tasks is greater than the available computing resource stream of the first computing unit, then a number of available computing resource streams corresponding to the number of tasks are allocated in the available computing resource stream of the first computing unit and the available computing resource stream of the second computing unit to process the task data to be processed, and obtain the result data of each task data to be processed. The second computing unit is a computing unit in the first computing node other than the first computing unit.

19. The method according to claim 18, characterized in that, Also includes: Based on the time information, the computing resource program of the first computing unit for processing the task data to be processed is determined, and the first computing unit includes at least two computing resource programs.

20. A task processing device, characterized in that, include: The first receiving module is configured to receive a task request sent by at least one terminal device, wherein the task request is used to request the network device to process the task data to be processed by the terminal device. A first sending module is configured to send a task request response to at least one of the terminal devices, the task request response being used to indicate whether the task request is accepted. The second receiving module is used to receive task data to be processed sent by at least one target terminal device, wherein the target terminal device is the terminal device that accepts the task request; A processing module is used to allocate available computing resources to process the task data to be processed and obtain result data for each task data to be processed. The task data to be processed includes model training data and the result data includes model training result data. Alternatively, the task data to be processed includes extended reality (XR) rendering data and the result data includes XR rendering result data. The second sending module is used to send corresponding result data to each of the target terminal devices.

21. A task processing device, characterized in that, The device includes a processor, a transceiver, and a memory; the processor is communicatively connected to both the transceiver and the memory. The memory stores computer-executed instructions; The transceiver communicates and interacts with external devices. The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-19.

22. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-19.

23. A chip system, characterized in that, It includes at least one processor and a communication interface, the communication interface and the at least one processor being interconnected via a line, the at least one processor being configured to run a computer program or instructions to perform the method as described in any one of claims 1-19.

24. A computer program product, characterized in that, Includes a computer program that, when run, causes a computer to perform the method as described in any one of claims 1-19.

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