Task processing method and device, medium and computing equipment

Abstract

The embodiment of the invention provides a task processing method and device, a medium and computing equipment. The method comprises the steps that request information of a task is sent to a cloud end, so that the cloud end obtains a corresponding task resource packet and generates a task synchronization instruction, a client side obtains the task resource packet indicated by the instruction and deploys the task resource packet, and corresponding end side task resources are obtained for task processing after the task is started. According to the task processing method, collaborative updating with the cloud is carried out before the task is executed, so that efficient utilization of resources and flexible expansion of the system are realized; and the task is executed through the end-side task resource deployed at the client, so that the real-time performance and the high efficiency of task processing can be improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of artificial intelligence, and more specifically, embodiments of the present invention relate to a task processing method, apparatus, medium, and computing device. Background Art

[0002] In recent years, the field of artificial intelligence (AI) has been developing rapidly, and technologies represented by deep learning have made significant progress in areas such as image recognition, natural language processing, and speech recognition.

[0003] In the current technical solutions that are mainly based on cloud computing, the data calculation process is highly dependent on the cloud environment. Network failures and cloud service interruptions may result in slow loading or even inability to effectively obtain calculation results, insufficient timeliness, and high costs.

[0004] If calculations are performed on the end side, the execution logic of the end-side model is fixed in the version and lacks cloud-based collaborative update, control, and calculation capabilities. This results in poor flexibility and dynamism in the system, limits the source of data, and greatly restricts the dimensions of the calculation results, leading to inaccurate or incomplete decisions and an inability to meet complex business needs.

[0005] Therefore, how to run machine learning algorithms and complex business computing strategies in a more real-time and efficient manner so that client devices can provide users with a more outstanding personalized experience has undoubtedly become a crucial challenge in edge computing-related technologies.

[0006] This section is intended to provide a background or context to embodiments of the invention that are recited in the claims. No description herein is admitted to be prior art by inclusion in this section. Summary of the invention

[0007] In view of this, in order to solve the above problems, embodiments of the present invention are intended to provide a task processing method, apparatus, medium and computing device.

[0008] In a first aspect of an embodiment of the present invention, a method for processing a method task is provided, which is applied to a client and includes:

[0009] Sending request information of at least one task to the cloud, so that the cloud obtains a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published by the cloud, and the request information includes task configuration information of the client sending the request information;

[0010] receiving a task synchronization instruction from the cloud, wherein the task synchronization instruction is generated by the cloud according to the request information and the found task resource package;

[0011] The task resource package indicated by the task synchronization instruction is acquired and deployed to obtain corresponding terminal-side task resources, where the terminal-side task resources are used to perform task processing after the task is started.

[0012] In some embodiments, the request information for sending at least one task to the cloud includes at least one of the following:

[0013] sending the request information periodically;

[0014] The request information is sent when the client, the setting application or the setting operation is started.

[0015] In some embodiments, when the cloud determines that the client satisfies the configuration condition and determines that the client does not have a first task, the task synchronization instruction includes an instruction to add a first task and an address of a task resource package of the first task, wherein the first task is one or more of the tasks found by the cloud;

[0016] The step of obtaining and deploying the task resource package indicated by the task synchronization instruction includes:

[0017] Download the task resource package of the first task according to the address in the task synchronization instruction;

[0018] Add resource configuration information for the first task.

[0019] In some embodiments, the task configuration information includes a version number of the task, and when the cloud determines that the client satisfies the configuration condition and determines that the client has a second task and the version number is lower than that of the cloud, the task synchronization instruction includes an instruction to update the second task, an instruction to delete the original second task, and an address of a task resource package of the second task, wherein the second task is one or more of the tasks found by the cloud;

[0020] The step of obtaining and deploying the task resource package indicated by the task synchronization instruction includes:

[0021] Download the task resource package of the second task according to the address in the task synchronization instruction, and delete the original second task;

[0022] Update resource configuration information of the second task.

[0023] In some embodiments, when the cloud determines that the client does not meet the configuration condition, or determines that the client has a third task and the third task is removed from the cloud, the task synchronization instruction includes an instruction to delete the third task, wherein the third task is one or more of the tasks found in the cloud;

[0024] The step of obtaining and deploying the task resource package indicated by the task synchronization instruction includes:

[0025] Deleting the third task;

[0026] The resource configuration information of the third task is deleted or updated.

[0027] In some embodiments, the method further includes a task initiation step, including any of the following:

[0028] Start the task by calling a task interface or executing a task calling function;

[0029] The task is triggered when the setting mechanism is executed, and the setting plan is configured in the code of the task.

[0030] In some embodiments, the method further comprises a task processing step, including at least one of the following:

[0031] Performing calculations according to the task execution code in the terminal-side task resource;

[0032] Using the intelligent model in the terminal-side task resources to perform calculations;

[0033] According to the user data or the status data of the client, the corresponding algorithm code in the terminal-side task resource is called to perform calculations.

[0034] In some embodiments, the method further comprises a decision-making step, including at least one of the following:

[0035] Make decisions based on task processing results;

[0036] Regularly reporting task processing results to the cloud so that the cloud can make decisions based on cloud user data;

[0037] The task processing result is reported to the cloud in real time, and a decision is made based on the cloud data received and retrieved from the cloud that matches the task processing result. In a second aspect of the embodiment of the present invention, a method task processing method is provided, which is applied to the cloud, and includes:

[0038] Receiving request information of at least one task from a client, wherein the request information includes task configuration information of the client sending the request information;

[0039] Acquire a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published;

[0040] Generate a task synchronization instruction according to the request information and the found task resource package;

[0041] The task synchronization instruction is sent to the client, so that the client performs task deployment according to the task synchronization instruction to obtain corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing on the tasks started on the client.

[0042] In some embodiments, the method further includes a task resource package publishing step, including:

[0043] Acquire task resources created for the task, wherein the task resources include task execution code, intelligent model, and algorithm code set for a set situation;

[0044] Processing the task resources, uploading the processing results to a content distribution network, and obtaining a link generated by the content distribution network;

[0045] The task resource package is obtained according to the link and the task configuration of the task, and the task resource package is stored in a cloud database.

[0046] In some embodiments, the processing of the task resources includes:

[0047] Precompile part of the task execution code and / or part of the algorithm code to obtain a binary file.

[0048] In some embodiments, generating a task synchronization instruction according to the request information and the found task resource package includes:

[0049] When it is determined that the client meets the configuration conditions and that the first task does not exist on the client, the task synchronization instruction is set to include an instruction for adding a new first task and the address of a task resource package of the first task, wherein the first task is one or more of the tasks found in the cloud.

[0050] In some embodiments, the task configuration information includes a version number of the task, and generating a task synchronization instruction according to the request information and the found task resource package includes:

[0051] When it is determined that the client meets the configuration conditions and that the client has a second task and its version number is lower than that of the cloud, the task synchronization instruction is set to include an instruction to update the second task, an instruction to delete the original second task, and the address of the task resource package of the second task, wherein the second task is one or more of the tasks found in the cloud.

[0052] In some embodiments, generating a task synchronization instruction according to the request information and the found task resource package includes:

[0053] When it is determined that the client does not meet the configuration conditions, or when it is determined that the client has a third task and the third task is removed from the cloud, the task synchronization instruction is set to include an instruction to delete the third task, wherein the third task is one or more of the tasks found in the cloud.

[0054] In a third aspect of the embodiments of the present invention, a task processing device is provided, which is applied to a client and includes:

[0055] A sending unit, configured to send request information of at least one task to a cloud, so that the cloud obtains a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published by the cloud, and the request information includes task configuration information of a client sending the request information;

[0056] A synchronization unit, configured to receive a task synchronization instruction from the cloud, wherein the task synchronization instruction is generated by the cloud according to the request information and the found task resource package;

[0057] The deployment unit is used to obtain the task resource package indicated by the task synchronization instruction and deploy it to obtain the corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing after the task is started.

[0058] In some embodiments, the sending unit is specifically used for at least one of the following:

[0059] sending the request information periodically;

[0060] The request information is sent when the client, the setting application or the setting operation is started.

[0061] In some embodiments, when the cloud determines that the client satisfies the configuration condition and determines that the client does not have a first task, the task synchronization instruction includes an instruction to add a first task and an address of a task resource package of the first task, wherein the first task is one or more of the tasks found by the cloud;

[0062] The deployment unit is specifically used for:

[0063] Download the task resource package of the first task according to the address in the task synchronization instruction;

[0064] Add resource configuration information for the first task.

[0065] In some embodiments, the task configuration information includes a version number of the task, and when the cloud determines that the client satisfies the configuration condition and determines that the client has a second task and the version number is lower than that of the cloud, the task synchronization instruction includes an instruction to update the second task, an instruction to delete the original second task, and an address of a task resource package of the second task, wherein the second task is one or more of the tasks found by the cloud;

[0066] The deployment unit is specifically used for:

[0067] Download the task resource package of the second task according to the address in the task synchronization instruction, and delete the original second task;

[0068] Update resource configuration information of the second task.

[0069] In some embodiments, when the cloud determines that the client does not meet the configuration condition, or determines that the client has a third task and the third task is removed from the cloud, the task synchronization instruction includes an instruction to delete the third task, wherein the third task is one or more of the tasks found in the cloud;

[0070] The deployment unit is specifically used for:

[0071] Deleting the third task;

[0072] The resource configuration information of the third task is deleted or updated.

[0073] In some embodiments, the apparatus further comprises a task initiation unit configured to:

[0074] Start the task by calling a task interface or executing a task calling function;

[0075] The task is triggered when the setting mechanism is executed, and the setting plan is configured in the code of the task.

[0076] In some embodiments, the apparatus further comprises a task processing unit configured to:

[0077] Performing calculations according to the task execution code in the terminal-side task resource;

[0078] Using the intelligent model in the terminal-side task resources to perform calculations;

[0079] According to the user data or the status data of the client, the corresponding algorithm code in the terminal-side task resource is called to perform calculations.

[0080] In some embodiments, the apparatus further comprises a decision unit configured to:

[0081] Make decisions based on task processing results;

[0082] Regularly reporting task processing results to the cloud so that the cloud can make decisions based on cloud user data;

[0083] The task processing result is reported to the cloud in real time, and a decision is made based on the received cloud data retrieved from the cloud that matches the task processing result.

[0084] In a fourth aspect of the embodiments of the present invention, a task processing device is provided, which is applied in a cloud, and includes:

[0085] A receiving unit, configured to receive request information of at least one task from a client, wherein the request information includes task configuration information of the client sending the request information;

[0086] An acquisition unit, configured to acquire a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published;

[0087] A generating unit, configured to generate a task synchronization instruction according to the request information and the found task resource package;

[0088] The sending unit is used to send the task synchronization instruction to the client, so that the client performs task deployment according to the task synchronization instruction to obtain corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing on the tasks started on the client.

[0089] In some embodiments, the apparatus further comprises a publishing unit, configured to:

[0090] Acquire task resources created for the task, wherein the task resources include task execution code, intelligent model, and algorithm code set for a set situation;

[0091] Processing the task resources, uploading the processing results to a content distribution network, and obtaining a link generated by the content distribution network;

[0092] The task resource package is obtained according to the link and the task configuration of the task, and the task resource package is stored in a cloud database.

[0093] In some embodiments, when the publishing unit is used to process the task resources, it is specifically used to:

[0094] Precompile part of the task execution code and / or part of the algorithm code to obtain a binary file.

[0095] In some embodiments, the generating unit is specifically used for:

[0096] When it is determined that the client meets the configuration conditions and that the first task does not exist on the client, the task synchronization instruction is set to include an instruction for adding a new first task and the address of a task resource package of the first task, wherein the first task is one or more of the tasks found in the cloud.

[0097] In some embodiments, the task configuration information includes a version number of the task, and the generating unit is specifically configured to:

[0098] When it is determined that the client meets the configuration conditions and that the client has a second task and its version number is lower than that of the cloud, the task synchronization instruction is set to include an instruction to update the second task, an instruction to delete the original second task, and the address of the task resource package of the second task, wherein the second task is one or more of the tasks found in the cloud.

[0099] In some embodiments, the task configuration information includes a version number of the task, and the generating unit is specifically configured to:

[0100] When it is determined that the client does not meet the configuration conditions, or when it is determined that the client has a third task and the third task is removed from the cloud, the task synchronization instruction is set to include an instruction to delete the third task, wherein the third task is one or more of the tasks found in the cloud.

[0101] In a fifth aspect of the embodiments of the present invention, a readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned task processing method is implemented. In a sixth aspect of the embodiments of the present invention, a computing device is provided, including: a processor, a memory; the memory is used to store the computer program; the processor is used to execute the above-mentioned task processing method by calling the computer program.

[0102] The implementation method of the present invention sends task request information to the cloud, so that the cloud obtains the corresponding task resource package and generates a task synchronization instruction. The client obtains the task resource package indicated by the instruction and deploys it, and obtains the corresponding end-side task resources for task processing after the task is started. The task processing method performs collaborative updates with the cloud before executing the task, achieving efficient resource utilization and flexible expansion of the system; and by executing tasks with the end-side task resources deployed on the client, the real-time and efficiency of task processing can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, in which:

[0104] Figure 1 The application scenario diagram of the task processing method according to the embodiment of the present invention is schematically shown;

[0105] Figure 2 A flowchart of a task processing method according to an embodiment of the present invention is schematically shown;

[0106] Figure 3 A flowchart schematically shows another task processing method according to an embodiment of the present invention;

[0107] Figure 4 A block diagram of a task processing device according to an embodiment of the present invention is schematically shown;

[0108] Figure 5 A block diagram schematically shows another task processing device according to an embodiment of the present invention;

[0109] Figure 6 A schematic diagram of a medium according to an embodiment of the present invention is schematically shown;

[0110] Figure 7 A schematic diagram of a computing device according to an embodiment of the present invention is schematically shown.

[0111] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0112] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0113] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, device, apparatus, method or computer program product. Therefore, the present disclosure may be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0114] According to an embodiment of the present invention, a task processing method, medium, apparatus and computing device are proposed.

[0115] It should be understood herein that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction rather than having any limiting meaning.

[0116] The principle and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0117] In the current technical solutions that are mainly based on cloud computing, the data calculation process is highly dependent on the cloud environment. Network failures and cloud service interruptions may result in slow loading or even inability to effectively obtain calculation results, insufficient timeliness, and high costs.

[0118] If calculations are performed on the end side, the execution logic of the end-side model is fixed in the version and lacks cloud-based collaborative update, control, and calculation capabilities. This results in poor flexibility and dynamism in the system, limits the source of data, and greatly restricts the dimensions of the calculation results, leading to inaccurate or incomplete decisions and an inability to meet complex business needs.

[0119] Therefore, how to run machine learning algorithms and complex business computing strategies in a more real-time and efficient manner so that client devices can provide users with a more outstanding personalized experience has undoubtedly become a crucial challenge in edge computing-related technologies.

[0120] In view of this, the present invention proposes a task processing method, which sends task request information to the cloud so that the cloud obtains the corresponding task resource package and generates a task synchronization instruction. The client obtains the task resource package indicated by the instruction and deploys it, and obtains the corresponding end-side task resources for task processing after the task is started. The task processing method performs collaborative updates with the cloud before executing the task, achieving efficient resource utilization and flexible expansion of the system; and by executing tasks with the end-side task resources deployed on the client, the real-time and efficiency of task processing can be improved.

[0121] Exemplary Methods

[0122] Combine the following Figure 1 For application scenarios, refer to Figures 2 to 3 The method for task processing according to an exemplary embodiment of the present invention is described. It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principle of the present invention, and the embodiments of the present invention are not limited in this respect. On the contrary, the embodiments of the present invention can be applied to any applicable scenario.

[0123] like Figure 1 The figure shows an application scenario diagram of a task processing method in an embodiment of the present invention. Figure 1It includes: a cloud platform (cloud) 10 and a client 20.

[0124] The cloud 10 is a computing resource pool composed of a large number of servers and other network devices, which provides various services to users through the network. The client 20 is a terminal device that can interact with the user, such as a personal computer, mobile phone, tablet computer, smart device, etc.

[0125] In the embodiment of the present invention, the cloud 10 can exchange information with the client 20, the cloud 10 can receive request information from the client 20, and can also send resources or instructions to the client 20. Developers can upload task resources to the cloud 10 for storage or publication by the cloud 10.

[0126] Figure 2 A flowchart of a task processing method provided by an embodiment of the present invention is shown. The method can be performed by Figure 1 The client executes in Figure 2 As shown, the method may at least include the following steps:

[0127] S201, sending request information of at least one task to the cloud, so that the cloud obtains a task resource package corresponding to the task according to the request information.

[0128] In the embodiments of the present disclosure, the task refers to a function in a client application, which is not specific to any user interaction mode and can be actively triggered by the user or not perceived by the user, and is used to complete specific data processing or service provision.

[0129] For example, the task can be the audio track separation task in a video editing app, or it can be a function in a shopping app or a media app that makes corresponding recommendation decisions based on the different levels of users' willingness to pay.

[0130] In some embodiments, the timing of the request can be controlled by a timer cycle built into the client to periodically send the request information. For example, the timer can be used to control the sending of the task request information on a daily basis.

[0131] In some embodiments, the request information may be sent when the client, the setting application, or the setting operation is started. Specifically, it may be sent when the client is started, or when the application to which the task belongs is started. For example, if the task may be a track separation task in a video editing APP, the request information is sent when the video editing APP is started; the request information may also be sent when the setting operation is started. Still taking the track separation task as an example, the setting operation may be set to a video import and load operation.

[0132] In this step, the request information is used to enable the cloud to obtain the task resource package corresponding to the task. The task resource package is pre-published by the cloud. The task resource package is a collection of software and hardware resources required to perform the task.

[0133] In some embodiments, the task resource package can be released in the following ways:

[0134] First, developers create and write task resources on the cloud platform. Task resources include code, task configuration, and resources required for task execution, such as neural network-related models or large language models. The code includes task execution code for executing code logic and algorithm code for implementing extended functions.

[0135] Next, the deployment parameters of the task are set through the cloud, such as the client type (such as Android, iOS, etc.) and the client application version (such as >= 1.0.1) to be sent.

[0136] After that, the process of deploying tasks on the cloud platform begins. In this process, in order to ensure security and optimize the delivery cost, the code files can be encrypted to prevent resources from being illegally obtained and tampered with; and the code files can be compressed to reduce the amount of data transmission and the delivery cost. After encryption and compression, the processing results of the task resources are obtained.

[0137] Finally, the processing result is uploaded to the content delivery network (CDN), and the link generated by the content delivery network is obtained. The content delivery network is a distributed server system used to accelerate the delivery of Internet content. Afterwards, the task resource package is obtained according to the link and the task configuration of the task, and the task resource package is stored in the cloud database for subsequent query and synchronization.

[0138] In some embodiments, a method of precompiling a portion of the script code (eg, a portion of the task execution code and / or a portion of the algorithm code) is adopted instead of a direct execution mode.

[0139] The precompilation process involves the pre-construction of specific script code to generate an efficiently executable intermediate code or machine code form, such as a binary file. Compared with direct execution, this precompilation method enhances security and effectively prevents the code from being maliciously tampered with, stolen, or injected during operation. At the same time, precompilation significantly improves computing efficiency. For example, when dealing with complex tasks such as calculating users' willingness to pay in real time, data processing and analysis can be completed at a faster speed. In addition, in application scenarios such as calculating willingness to pay based on user behavior data, the precompiled code can quickly and efficiently process users' multi-dimensional behavior data (such as browsing trajectory, operation frequency, dwell time, etc.), quickly derive accurate willingness to pay scores, and provide timely and reliable data support for subsequent business decisions.

[0140] In the embodiment of the present disclosure, the request information includes the task configuration information of the client sending the request information. In one example, the request information includes the existing task list and the corresponding task version number of the client.

[0141] S202, receiving a task synchronization instruction from the cloud.

[0142] The task synchronization instruction is generated by the cloud based on the request information and the found task resource package, and is used to indicate how to handle the client's task resources, such as adding new task resources, updating task resources, or deleting task resources, and the synchronization instruction can also indicate the address for obtaining task resources. Specifically, the cloud compares the client task configuration information in the request information with the task configuration and link in the found task resource package, and generates a corresponding synchronization instruction based on the comparison result.

[0143] S203: Acquire the task resource package indicated by the task synchronization instruction and deploy it to obtain corresponding terminal-side task resources.

[0144] In some embodiments, the task resource package can be downloaded according to the address indicated by the task synchronization instruction, and then the client initializes the local script running environment and dynamically loads the code and configuration file in the task resource package to obtain the terminal-side task resource. The terminal-side task resource is used to perform task processing after the task is started.

[0145] The implementation method of the present invention sends task request information to the cloud, so that the cloud obtains the corresponding task resource package and generates a task synchronization instruction. The client obtains the task resource package indicated by the instruction and deploys it, and obtains the corresponding end-side task resources for task processing after the task is started. The task processing method performs collaborative updates with the cloud before executing the task, achieving efficient resource utilization and flexible expansion of the system; and by executing tasks with the end-side task resources deployed on the client, the real-time and efficiency of task processing can be improved.

[0146] In some embodiments, a task synchronization instruction may be generated according to the request information and the found task resource package in the following manner.

[0147] In the first case, the one or more tasks found in the cloud are referred to as first tasks. If it is determined that the client meets the configuration conditions and it is determined that the client does not have the first task, the task synchronization instruction includes an instruction to add the first task and the address of the task resource package of the first task.

[0148] For this task, the cloud can obtain the configuration issued by the task, such as the issued client type and the issued client application version. If it is determined that the type and application version of the client sending the request information meet the configuration, it is further determined from the client task configuration information whether the client has the first task. If not, a new instruction and the task resource address of the first task are issued.

[0149] After receiving the task synchronization instruction, the client deploys according to the task resource package indicated by the instruction, including: downloading the task resource package of the first task according to the address in the task synchronization instruction, and locally adding the resource configuration information of the first task to update the client task configuration information. If the resource task package is encrypted and compressed, the client decrypts and decompresses it accordingly after downloading the task resource package.

[0150] Through the above method, when there is a new task that needs to be pushed to the client that meets the conditions, the cloud platform can promptly and accurately deliver instructions and resources to the client, thereby realizing rapid deployment of tasks.

[0151] In the second case, the one or more tasks found in the cloud are called second tasks. If it is determined that the client meets the configuration conditions, and it is determined that the client has a second task and the version number is lower than that of the cloud, the task synchronization instruction includes an instruction to update the second task, an instruction to delete the original second task, and the address of the task resource package of the second task.

[0152] Similarly, for this task, the cloud can obtain the configuration issued by the task, such as the issued client type and the issued client application version. If it is determined that the type and application version of the client sending the request information meet the configuration, it is further determined from the client task configuration information whether the client has a second task. If it does exist, but the version is lower than the current cloud version, an update instruction, a delete instruction, and the task resource address of the second task are issued.

[0153] After receiving the task synchronization instruction, the client deploys the task resource package indicated by the instruction, including: downloading the task resource package of the second task according to the address in the task synchronization instruction, deleting the original second task; and updating the resource configuration information of the second task, that is, updating the client task configuration information. If the resource task package is encrypted and compressed, the client decrypts and decompresses it accordingly after downloading the task resource package.

[0154] Through the above methods, it is ensured that the client is always kept in sync with the platform tasks to obtain the latest functions and performance optimizations.

[0155] In the third case, the one or more tasks found in the cloud are called third tasks. If it is determined that the client does not meet the configuration condition, or it is determined that the client has a third task and the third task is removed from the cloud, the task synchronization instruction includes an instruction to delete the third task.

[0156] Similarly, for this task, the cloud can obtain the configuration issued for the task, such as the issued client type and the issued client application version. If it is determined that the type or application version of the client that sent the request information does not meet the configuration, a deletion instruction is issued; or, if it is determined that the client has a third task but the task has been removed from the cloud, a deletion instruction is also issued.

[0157] After receiving the task synchronization instruction, the client performs deployment according to the task resource package indicated by the instruction, including: deleting the third task, and deleting or updating the resource configuration information of the third task.

[0158] The above methods can help to clean up unnecessary tasks in a timely manner, release client resources, and improve system efficiency and stability.

[0159] Based on the traditional mode in which the server only issues resources, the embodiment of the present invention generates and issues task synchronization instructions based on the request information and the found task resource package, thereby increasing the dynamic instruction control of the cloud. This method brings many advantages. First, the instructions issued by the cloud are highly flexible. For example, when it is detected that a task has security risks or does not comply with business rules, the cloud can issue instructions in a timely manner to take the task offline, effectively preventing the execution of illegal tasks on the client and ensuring the overall security of the system. In addition, the task execution process can be dynamically adjusted according to different business needs and client status, such as limiting the frequency of issuing related instructions during the daytime server peak period, and speeding up the issuance of instructions during the evening off-peak period, thereby saving cloud server costs.

[0160] After completing the deployment of the task resource package and obtaining the corresponding end-side task resources, wait for the client to execute the task.

[0161] There are at least two ways for a client to start a task for execution:

[0162] (1) Active execution: The client starts the task by calling the task interface or executing the task call function. This method gives the client the ability to actively initiate tasks in specific scenarios, meeting the user's personalized needs and specific business process requirements.

[0163] (2) Passive triggering: The task is triggered when the set mechanism is executed, and the set plan is configured in the code of the task. For example, the task may be triggered when entering a certain page, playing a song, etc. This method makes the execution of tasks more intelligent and automated, and can automatically respond according to user behavior and system status, improving user experience and system efficiency.

[0164] After the task is triggered, the client's computing engine automatically executes the loaded code to perform client operations.

[0165] In some embodiments, the computing engine may include three modules: a script execution engine, a model reasoning engine, and a client extension capability and data layer. The script execution engine is used to perform operations based on the task execution code in the end-side task resources, that is, to provide code logic operation capabilities; the model reasoning engine is used to perform operations using the intelligent model in the end-side task resources, that is, to provide model reasoning operation capabilities; the client extension capability and data layer is used to call the corresponding algorithm code in the end-side task resources for operations based on user data or client status data, that is, to provide user behavior data and extension capabilities, etc.

[0166] The computing engine's operating methods include code logic operations, code-driven neural network model operations, and code-driven end-side large model operations, and ultimately obtain the corresponding calculation results. The diverse computing methods enable the client to adapt to different computing needs and scenarios.

[0167] In the disclosed embodiments, making decisions based on the task processing results mainly includes the following methods: (1) The client directly makes the next decision based on the task processing results.

[0168] For example, if the result of the task is to calculate the user's purchase intention score, if it exceeds a certain standard, a more suitable product purchase method will be provided. This method is suitable for scenarios with poor network environment or high real-time requirements. The client can make decisions independently, improving the system's response speed and user experience.

[0169] (2) Regularly report the task processing results to the cloud so that the cloud can make decisions based on the cloud user data. The client regularly reports the local calculation results to the cloud. The cloud uses the client's calculation results as a partial factor and performs secondary calculations with the cloud user data to obtain the final calculation results for business scenario decision-making. For example, the risk behavior characteristics calculated by the client are jointly calculated with the cloud data to obtain the final risk index for risk control, etc.

[0170] This approach fully leverages the computing power and data advantages of the cloud, and combined with the local calculation results of the client, can provide more accurate and comprehensive decision support.

[0171] (3) Reporting the task processing results to the cloud in real time, and making decisions based on the cloud data retrieved from the cloud that matches the task processing results.

[0172] The client transmits the calculation results to the cloud in real time. The cloud uses the calculation results of the client as input, combines them with relevant data on the server, and sends the data to the client. For example, it combines the user characteristics calculated on the client side with the content recommended by the server to make more timely personalized recommendations.

[0173] This method can achieve real-time collaboration between the end and the cloud for business scenarios with complex data, providing users with more personalized and accurate services. Through the above various intelligent decision-making methods, the embodiments of the present invention can provide different intelligent decision-making methods to adapt to different application scenarios, achieve the collaboration of end-to-end cloud computing results, and provide users with a better experience and more intelligent decision support.

[0174] In some embodiments, a client access layer is also constructed, which includes a variety of client UI display methods such as pop-up windows, push notifications, lists, etc. After making a decision based on the task execution results, different display methods can be selected according to the specific application scenario to present the relevant content more intelligently on the user's client screen to provide a better user experience.

[0175] The following describes in detail the task processing method proposed in the embodiment of the present invention by taking the task of calculating the user's real-time willingness to pay in a media APP as an example.

[0176] In today's digital recommendation environment, accurately grasping the user's willingness to buy is of vital importance for companies to formulate recommendation strategies and improve recommendation efficiency. Traditional recommendation methods often lack accurate insights into the user's real-time status, making it difficult to achieve personalized and accurate recommendation push. According to the task processing method proposed in an embodiment of the present invention, a recommendation method decision model corresponding to different willingness to pay levels is constructed through real-time monitoring and calculation of the user's real-time willingness to pay, so as to improve the accuracy and effectiveness of the recommendation. The method comprises the following steps:

[0177] First, the developer creates a task on the cloud platform and writes a real-time willingness algorithm related to the task. The algorithm is designed to analyze the real-time behavior data of users in various application scenarios, and calculates the user's purchase willingness through comprehensive analysis of multi-dimensional data such as browsing history, dwell time, and operation frequency. For example, when a user frequently browses certain pages or listens to certain types of songs in an application, the algorithm can accurately quantify their purchase possibility based on the weight distribution of these behavior data.

[0178] After completing the algorithm code writing, use the deployment configuration interface provided by the cloud platform to set the deployment parameters of the task in detail. This includes the configuration of task distribution for user groups of specific mobile operating system versions, such as setting tasks to be distributed only to users of Android version 10 and above. In addition, other related parameters such as task triggering conditions and execution priority can also be configured. After completing the setting of all configuration information, the task deployment process of the cloud platform is triggered.

[0179] In this process, in the embodiment of the present invention, the platform uses pre-compilation processing technology for some key codes in the task. Pre-compilation processing can not only effectively enhance the security of the code and prevent the code from being maliciously tampered with or reverse analyzed, but also significantly improve the execution performance of the code and reduce the resource consumption and response time when the task is running on the client.

[0180] By uploading the above processing results to the content distribution network, a link to the task can be obtained, and the link and the task configuration are stored in a cloud database, thereby obtaining a task resource package corresponding to the task.

[0181] When the media app in the client is started, it sends the request information of the task to the cloud. The cloud searches for the task in the database, generates a task synchronization instruction based on the task resource package and request information, and sends it to the client. The client obtains the task resource package based on the task synchronization instruction and deploys it locally to obtain the corresponding end-side task resources.

[0182] Assume that the passive trigger mode is pre-configured in the task. When the user visits a specific page or clicks a specific button in the media APP, the client background automatically starts the task. After the task is started, the real-time behavior data generated by the user on the client is used as the algorithm input to run the end-side task resources, that is, the pre-written purchase intention calculation algorithm. Through the comparative analysis of the user's current behavior and historical behavior data and the fusion calculation of multi-dimensional data, the user's real-time willingness to pay score is finally obtained, and the score is saved in the client's local or cloud database for subsequent recommendation decisions.

[0183] By setting the user's real-time willingness to pay as a key decision factor, a variety of recommendation methods can be precisely regulated and adapted. For example, when it is detected that the user is in a specific real-time willingness to pay range, a matching recommendation activity strategy is launched in a targeted manner, including but not limited to the setting of promotional discount combinations, the selection of channels and frequencies for recommending information push, the formulation and implementation of personalized recommendation plans, etc., so as to achieve efficient allocation of recommendation resources and maximize the recommendation effect, while enhancing the adaptability and flexibility of recommendation activities in different user willingness to pay scenarios, and improving the accuracy and effectiveness of overall recommendation activities, so as to achieve better business recommendation goals and enhance market competitiveness.

[0184] Figure 3 A flowchart of another task processing method provided by an embodiment of the present invention is shown. The method can be performed by Figure 1 In the cloud execution. Figure 3 As shown, the method may at least include the following steps:

[0185] S301, receiving request information of at least one task from a client, where the request information includes task configuration information of the client sending the request information.

[0186] The request information may be sent by the client at a fixed time, or may be sent when the client, a setting application, or a setting operation is started.

[0187] S302: Acquire a task resource package corresponding to the task according to the request information, where the task resource package is pre-published.

[0188] After receiving the request information, the cloud searches the cloud database to obtain the task resource package corresponding to the requested task. The task resource package is pre-published by the cloud. The task resource package is a collection of software and hardware resources required to perform the task.

[0189] In some embodiments, the task resource package can be released in the following ways:

[0190] First, developers create and write task resources on the cloud platform. Task resources include code, task configuration, and resources required for task execution, such as neural network-related models or large language models. The code includes task execution code for executing code logic and algorithm code for implementing extended functions.

[0191] Next, the deployment parameters of the task are set through the cloud, such as the client type (such as Android, iOS, etc.) and the client application version (such as >= 1.0.1) to be sent.

[0192] After that, the process of deploying tasks on the cloud platform begins. In this process, in order to ensure security and optimize the delivery cost, the code files can be encrypted to prevent resources from being illegally obtained and tampered with; and the code files can be compressed to reduce the amount of data transmission and the delivery cost. After encryption and compression, the processing results of the task resources are obtained.

[0193] Finally, the processing result is uploaded to the content delivery network (CDN), and the link generated by the content delivery network is obtained. The content delivery network is a distributed server system used to accelerate the delivery of Internet content. Afterwards, the task resource package is obtained according to the link and the task configuration of the task, and the task resource package is stored in the cloud database for subsequent query and synchronization.

[0194] S303: Generate a task synchronization instruction according to the request information and the found task resource package.

[0195] The task synchronization instruction is used to indicate how to process the client's task resources, such as adding new task resources, updating task resources, or deleting task resources, and the synchronization instruction can also indicate the address for obtaining task resources. Specifically, the cloud compares the client task configuration information in the request information with the task configuration and link in the task resource package being searched, and generates a corresponding synchronization instruction based on the comparison result.

[0196] S304: Send the task synchronization instruction to the client, so that the client performs task deployment according to the task synchronization instruction to obtain corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing on the task started on the client.

[0197] The client can download the task resource package according to the address specified by the task synchronization instruction. After that, the client initializes the local script running environment and dynamically loads the code and configuration file in the task resource package to obtain the end-side task resources. The end-side task resources are used to perform task processing after the task is started.

[0198] In some embodiments, a method of precompiling a portion of the script code (eg, a portion of the task execution code and / or a portion of the algorithm code) is adopted instead of a direct execution mode.

[0199] The precompilation process involves the pre-construction of specific script code to generate an efficiently executable intermediate code or machine code form, such as a binary file. Compared with direct execution, this precompilation method enhances security and effectively prevents the code from being maliciously tampered with, stolen, or injected during operation. At the same time, precompilation significantly improves computing efficiency. For example, when dealing with complex tasks such as calculating users' willingness to pay in real time, data processing and analysis can be completed at a faster speed. In addition, in application scenarios such as calculating willingness to pay based on user behavior data, the precompiled code can quickly and efficiently process users' multi-dimensional behavior data (such as browsing trajectory, operation frequency, dwell time, etc.), quickly derive accurate willingness to pay scores, and provide timely and reliable data support for subsequent business decisions.

[0200] In some embodiments, a task synchronization instruction may be generated according to the request information and the found task resource package in the following manner.

[0201] In the first case, the one or more tasks found in the cloud are referred to as first tasks. If it is determined that the client meets the configuration conditions and it is determined that the client does not have the first task, the task synchronization instruction includes an instruction to add the first task and the address of the task resource package of the first task.

[0202] For this task, the cloud can obtain the configuration issued by the task, such as the issued client type and the issued client application version. If it is determined that the type and application version of the client sending the request information meet the configuration, it is further determined from the client task configuration information whether the client has the first task. If not, a new instruction and the task resource address of the first task are issued.

[0203] Through the above method, when there is a new task that needs to be pushed to the client that meets the conditions, the cloud platform can promptly and accurately deliver instructions and resources to the client, thereby realizing rapid deployment of tasks.

[0204] In the second case, the one or more tasks found in the cloud are called second tasks. If it is determined that the client meets the configuration conditions, and it is determined that the client has a second task and the version number is lower than that of the cloud, the task synchronization instruction includes an instruction to update the second task, an instruction to delete the original second task, and the address of the task resource package of the second task.

[0205] Similarly, for this task, the cloud can obtain the configuration issued by the task, such as the issued client type and the issued client application version. If it is determined that the type and application version of the client sending the request information meet the configuration, it is further determined from the client task configuration information whether the client has a second task. If it does exist, but the version is lower than the current cloud version, an update instruction, a delete instruction, and the task resource address of the second task are issued.

[0206] Through the above methods, it is ensured that the client is always kept in sync with the platform tasks to obtain the latest functions and performance optimizations.

[0207] In the third case, the one or more tasks found in the cloud are called third tasks. If it is determined that the client does not meet the configuration condition, or it is determined that the client has a third task and the third task is removed from the cloud, the task synchronization instruction includes an instruction to delete the third task.

[0208] Similarly, for this task, the cloud can obtain the configuration issued for the task, such as the issued client type and the issued client application version. If it is determined that the type or application version of the client that sent the request information does not meet the configuration, a deletion instruction is issued; or, if it is determined that the client has a third task but the task has been removed from the cloud, a deletion instruction is also issued.

[0209] The above methods can help to clean up unnecessary tasks in a timely manner, release client resources, and improve system efficiency and stability.

[0210] In summary, the task processing method according to the embodiment of the present invention has the following beneficial technical effects:

[0211] (1) This method achieves the coordinated update of the client and the cloud. The cloud can send down resources such as running code and neural network models, and the client can run these codes and models for calculation. This method gives the system powerful cloud synchronization capabilities and completely gets rid of the dependence on client version updates.

[0212] (2) Pre-build specific script codes to generate efficient executable intermediate codes or machine codes, effectively preventing the code from being maliciously tampered with, stolen, or injected during operation. At the same time, pre-compilation significantly improves computing efficiency;

[0213] (3) In an off-network environment, the client can still rely on local computing resources to perform calculations, ensuring business continuity and reliability. In addition, using the client's local data for calculations greatly improves the real-time nature of the calculation results. At the same time, local data can promptly reflect the current business status and user needs, making the calculation results more accurate and practical. This is of great significance for some application scenarios with high real-time requirements, such as real-time problem intelligent diagnosis, instant decision-making, etc.

[0214] (4) By transferring part of the computing tasks to the client, the computing workload on the server (cloud) can be effectively reduced by using local computing on the client, thereby reducing the computing cost of the server, allowing the server to focus on more complex management tasks and improve resource utilization efficiency;

[0215] (5) Synchronize the client's calculation results with the cloud. Not only can the client get the calculation results in real time for experience optimization, but the server can also perceive the relevant data for mixed calculation. For example, the server can combine the client's calculation results with the server's calculation results to obtain the risk control decision results for risk equipment identification.

[0216] Exemplary Devices

[0217] After introducing the medium of the exemplary embodiment of the present invention, next, reference is made to Figure 4 and Figure 5 A device according to an exemplary embodiment of the present invention is described.

[0218] The implementation process of the functions and effects of each module in the following device is specifically detailed in the implementation process of the corresponding steps in the above method, which will not be repeated here. For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can be referred to the partial description of the method embodiment.

[0219] Figure 4 A task processing device according to an embodiment of the present invention is schematically shown, and the device is applied to a client, and the device includes:

[0220] A sending unit 401 is used to send request information of at least one task to the cloud, so that the cloud obtains a task resource package corresponding to the task according to the request information, the task resource package is pre-published by the cloud, and the request information includes task configuration information of the client sending the request information;

[0221] A synchronization unit 402 is used to receive a task synchronization instruction from the cloud, where the task synchronization instruction is generated by the cloud according to the request information and the found task resource package;

[0222] The deployment unit 403 is used to obtain the task resource package indicated by the task synchronization instruction and deploy it to obtain the corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing after the task is started.

[0223] In some embodiments, the sending unit is specifically used for at least one of the following:

[0224] sending the request information periodically;

[0225] The request information is sent when the client, the setting application or the setting operation is started.

[0226] In some embodiments, when the cloud determines that the client satisfies the configuration condition and determines that the client does not have a first task, the task synchronization instruction includes an instruction to add a first task and an address of a task resource package of the first task, wherein the first task is one or more of the tasks found by the cloud;

[0227] The deployment unit is specifically used for:

[0228] Download the task resource package of the first task according to the address in the task synchronization instruction;

[0229] Add resource configuration information for the first task.

[0230] In some embodiments, the task configuration information includes a version number of the task, and when the cloud determines that the client satisfies the configuration condition and determines that the client has a second task and the version number is lower than that of the cloud, the task synchronization instruction includes an instruction to update the second task, an instruction to delete the original second task, and an address of a task resource package of the second task, wherein the second task is one or more of the tasks found by the cloud;

[0231] The deployment unit is specifically used for:

[0232] Download the task resource package of the second task according to the address in the task synchronization instruction, and delete the original second task;

[0233] Update resource configuration information of the second task.

[0234] In some embodiments, when the cloud determines that the client does not meet the configuration condition, or determines that the client has a third task and the third task is removed from the cloud, the task synchronization instruction includes an instruction to delete the third task, wherein the third task is one or more of the tasks found in the cloud;

[0235] The deployment unit is specifically used for:

[0236] Deleting the third task;

[0237] The resource configuration information of the third task is deleted or updated.

[0238] In some embodiments, the apparatus further comprises a task initiation unit configured to:

[0239] Start the task by calling a task interface or executing a task calling function;

[0240] The task is triggered when the setting mechanism is executed, and the setting plan is configured in the code of the task.

[0241] In some embodiments, the apparatus further comprises a task processing unit configured to:

[0242] Performing calculations according to the task execution code in the terminal-side task resource;

[0243] Using the intelligent model in the terminal-side task resources to perform calculations;

[0244] According to the user data or the status data of the client, the corresponding algorithm code in the terminal-side task resource is called to perform calculations.

[0245] In some embodiments, the apparatus further comprises a decision unit configured to:

[0246] Make decisions based on task processing results;

[0247] Regularly reporting task processing results to the cloud so that the cloud can make decisions based on cloud user data;

[0248] The task processing result is reported to the cloud in real time, and a decision is made based on the received cloud data retrieved from the cloud that matches the task processing result.

[0249] Figure 5 A task processing device according to an embodiment of the present invention is schematically shown, which is applied to the cloud, and the device includes:

[0250] A receiving unit 501 is used to receive request information of at least one task from a client, wherein the request information includes task configuration information of the client sending the request information;

[0251] An acquisition unit 502 is used to acquire a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published;

[0252] A generating unit 503, configured to generate a task synchronization instruction according to the request information and the found task resource package;

[0253] The sending unit 504 is used to send the task synchronization instruction to the client, so that the client performs task deployment according to the task synchronization instruction to obtain corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing on the tasks started on the client.

[0254] In some embodiments, the apparatus further comprises a publishing unit, configured to:

[0255] Acquire task resources created for the task, wherein the task resources include task execution code, intelligent model, and algorithm code set for a set situation;

[0256] Processing the task resources, uploading the processing results to a content distribution network, and obtaining a link generated by the content distribution network;

[0257] The task resource package is obtained according to the link and the task configuration of the task, and the task resource package is stored in a cloud database.

[0258] In some embodiments, when the publishing unit is used to process the task resources, it is specifically used to:

[0259] Precompile part of the task execution code and / or part of the algorithm code to obtain a binary file.

[0260] In some embodiments, the generating unit is specifically used for:

[0261] When it is determined that the client meets the configuration conditions and that the first task does not exist on the client, the task synchronization instruction is set to include an instruction for adding a new first task and the address of a task resource package of the first task, wherein the first task is one or more of the tasks found in the cloud.

[0262] In some embodiments, the task configuration information includes a version number of the task, and the generating unit is specifically configured to:

[0263] When it is determined that the client meets the configuration conditions and that the client has a second task and its version number is lower than that of the cloud, the task synchronization instruction is set to include an instruction to update the second task, an instruction to delete the original second task, and the address of the task resource package of the second task, wherein the second task is one or more of the tasks found in the cloud.

[0264] In some embodiments, the task configuration information includes a version number of the task, and the generating unit is specifically configured to:

[0265] When it is determined that the client does not meet the configuration conditions, or when it is determined that the client has a third task and the third task is removed from the cloud, the task synchronization instruction is set to include an instruction to delete the third task, wherein the third task is one or more of the tasks found in the cloud.

[0266] Exemplary Media

[0267] After introducing the method and apparatus of the exemplary embodiment of the present invention, next, reference is made to Figure 6 A readable storage medium according to an exemplary embodiment of the present invention is described.

[0268] In this exemplary embodiment, the above method can be implemented by a program product, such as a portable compact disk read-only memory (CD-ROM) and including program code, and can be run on a device, such as a personal computer. However, the program product of the present invention is not limited to this. In this document, a readable storage medium can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus or a device.

[0269] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0270] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0271] The program code contained on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RE, etc., or any suitable combination of the foregoing.

[0272] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as C or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user computing device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0273] Exemplary Computing Devices

[0274] After introducing the method, apparatus and medium of the exemplary embodiments of the present invention, next, reference is made to Figure 7 A computing device according to an exemplary embodiment of the present invention is described.

[0275] Figure 7 The computing device 700 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0276] like Figure 7 As shown, the computing device 700 is in the form of a general computing device. The components of the computing device 700 may include but are not limited to: at least one processing unit 701, at least one storage unit 702, and a bus 703 connecting different system components (including the processing unit 701 and the storage unit 702).

[0277] The bus 703 includes a data bus, a control bus, and an address bus.

[0278] The storage unit 702 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 7021 and / or a cache memory 7022 , and may further include a readable medium in the form of a non-volatile memory, such as a read-only memory (ROM) 7023 .

[0279] The storage unit 702 may also include a program / utility 7025 having a set (at least one) of program modules 7024, such program modules 7024 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0280] Computing device 700 may also communicate with one or more external devices 704 (eg, keyboards, pointing devices, etc.).

[0281] Such communication may be performed via input / output (I / O) interface 705. In addition, computing device 700 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via network adapter 706. Figure 7 As shown, network adapter 706 communicates with other modules of computing device 700 via bus 703. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with computing device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0282] It should be noted that although several units / modules or sub-units / modules of the interface traffic management device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules for embodiment.

[0283] In addition, although the operations of the method of the present invention are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0284] Although the spirit and principle of the present invention have been described with reference to several specific embodiments, it should be understood that the present invention is not limited to the disclosed specific embodiments, and the division of various aspects does not mean that the features in these aspects cannot be combined to benefit, and such division is only for the convenience of expression. The present invention is intended to cover various modifications and equivalent arrangements included in the spirit and scope of the attached claims.

Claims

1. A task processing method, characterized in that: The method comprises: Sending request information of at least one task to the cloud, so that the cloud obtains a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published by the cloud, and the request information includes task configuration information of the client sending the request information; receiving a task synchronization instruction from the cloud, wherein the task synchronization instruction is generated by the cloud according to the request information and the found task resource package; The task resource package indicated by the task synchronization instruction is acquired and deployed to obtain corresponding terminal-side task resources, where the terminal-side task resources are used to perform task processing after the task is started.

2. The method according to claim 1, characterized in that The request information for sending at least one task to the cloud includes at least one of the following: sending the request information periodically; The request information is sent when the client, the setting application or the setting operation is started.

3. The method according to claim 1, characterized in that When the cloud determines that the client satisfies the configuration condition and determines that the client does not have the first task, the task synchronization instruction includes an instruction to add a first task and an address of a task resource package of the first task, wherein the first task is one or more of the tasks found by the cloud; The step of obtaining and deploying the task resource package indicated by the task synchronization instruction includes: Download the task resource package of the first task according to the address in the task synchronization instruction; Add resource configuration information for the first task.

4. The method according to claim 1, characterized in that: The task configuration information includes the version number of the task. When the cloud determines that the client meets the configuration condition and determines that the client has a second task with a lower version number than the cloud, the task synchronization instruction includes an instruction to update the second task, an instruction to delete the original second task, and the address of the task resource package of the second task, wherein the second task is one or more of the tasks found by the cloud; The step of obtaining and deploying the task resource package indicated by the task synchronization instruction includes: Download the task resource package of the second task according to the address in the task synchronization instruction, and delete the original second task; Update resource configuration information of the second task.

5. The method according to claim 1, characterized in that When the cloud determines that the client does not meet the configuration condition, or determines that the client has a third task and the third task is removed from the cloud, the task synchronization instruction includes an instruction to delete the third task, wherein the third task is one or more of the tasks found in the cloud; The step of obtaining and deploying the task resource package indicated by the task synchronization instruction includes: Deleting the third task; The resource configuration information of the third task is deleted or updated.

6. A task processing method, characterized in that: The method comprises: Receiving request information of at least one task from a client, wherein the request information includes task configuration information of the client sending the request information; Acquire a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published; Generate a task synchronization instruction according to the request information and the found task resource package; The task synchronization instruction is sent to the client, so that the client performs task deployment according to the task synchronization instruction to obtain corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing on the tasks started on the client.

7. A task processing device, characterized in that: The device comprises: A sending unit, configured to send request information of at least one task to a cloud, so that the cloud obtains a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published by the cloud, and the request information includes task configuration information of a client sending the request information; A synchronization unit, configured to receive a task synchronization instruction from the cloud, wherein the task synchronization instruction is generated by the cloud according to the request information and the found task resource package; The deployment unit is used to obtain the task resource package indicated by the task synchronization instruction and deploy it to obtain the corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing after the task is started.

8. A task processing device, characterized in that: The device comprises: A receiving unit, configured to receive request information of at least one task from a client, wherein the request information includes task configuration information of the client sending the request information; An acquisition unit, configured to acquire a task resource package corresponding to the task according to the request information, wherein the task resource package is pre-published; A generating unit, configured to generate a task synchronization instruction according to the request information and the found task resource package; The sending unit is used to send the task synchronization instruction to the client, so that the client performs task deployment according to the task synchronization instruction to obtain corresponding terminal-side task resources, and the terminal-side task resources are used to perform task processing on the tasks started on the client.

9. A computing device, characterized in that The computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the operations performed by any one of claims 1 to 5 or the method of claim 6 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, and the program is executed by a processor to implement the operations performed by any one of claims 1 to 5 or the method of claim 6.

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