Distributed timed task processing system, method and equipment and storage medium

Abstract

The invention relates to a distributed timed task processing system, method and device and a storage medium. The system comprises a task template management module, a task management module, a task scheduling module and a task execution module. The task template management module is used for creating a task template and managing the task template; the task management template is used for managing tasks generated based on the task template; the task scheduling module is used for setting a task scheduling strategy; the task execution module is used for executing tasks; according to the invention, based on hierarchical three-level time wheel task storage management, the task scheduling accuracy, the execution efficiency, the management flexibility, the large-scale task processing capability and the like are remarkably improved.

Description

Technical Field

[0001] The invention relates to a distributed timed task processing system, method, device and storage medium, belonging to the technical field of task scheduling. Background Art

[0002] Existing task scheduling systems often have problems such as inaccurate scheduling, low execution efficiency, and lack of management flexibility when facing large-scale, diverse, and complex execution strategy tasks. Although some improved scheduling algorithms and task management strategies have been proposed, they are still unable to handle scheduled tasks in smart IoT scenarios.

[0003] The existing technology has the following core shortcomings, which not only affect the efficiency and reliability of scheduled task processing, but also limit its application in complex scenarios such as smart IoT:

[0004] First, the existing technology has obvious deficiencies in the accuracy of task scheduling. Due to the limitations of the scheduling algorithm or defects in the system design, tasks are often not accurately triggered at the scheduled time, which may cause delays or interruptions in key business processes.

[0005] Secondly, low execution efficiency is another significant problem. When faced with a large number or complex tasks, existing systems often show performance bottlenecks and cannot efficiently complete task processing. This not only affects the overall work efficiency, but may also lead to waste of resources and increased costs.

[0006] Furthermore, the lack of management flexibility is also an issue that cannot be ignored. Existing systems usually lack flexible task configuration and management capabilities and cannot easily cope with changing task requirements or execution strategies. This limits the adaptability and scalability of the system in a dynamic environment.

[0007] Finally, existing technologies also show insufficient processing capabilities for large tasks. When processing tasks involving large amounts of data or complex logic, the system often has difficulty ensuring execution stability and efficiency. Summary of the invention

[0008] In order to solve the above problems existing in the prior art, the present invention proposes a distributed scheduled task processing system, method, device and storage medium.

[0009] The technical solution of the present invention is as follows:

[0010] On the one hand, the present invention provides a distributed scheduled task processing system, including a task template management module, a task management module, a task scheduling module and a task execution module;

[0011] The task template management module is used to create task templates and manage task templates;

[0012] The task management template is used to manage tasks generated based on the task template;

[0013] The task scheduling module is used to set the scheduling strategy of the task;

[0014] The task execution module is used to execute tasks.

[0015] As a preferred embodiment of the present invention, the task template management module includes a basic component management unit, a task flow orchestration unit and a JSON conversion orchestration syntax unit;

[0016] The basic component management unit is used to create and manage basic components, which are basic units constituting tasks;

[0017] The task flow arrangement unit is used to arrange various basic components in a visual way to obtain a task flow and generate a task arrangement syntax;

[0018] The JSON conversion orchestration syntax unit is used to convert the task orchestration syntax into JSON format for storage.

[0019] As a preferred embodiment of the present invention, the task template management module includes a basic component management unit, a task flow orchestration unit and a JSON conversion orchestration syntax unit;

[0020] The basic component management unit is used to create and manage basic components, which are basic units constituting tasks;

[0021] The task flow arrangement unit is used to arrange various basic components in a visual way to obtain a task flow and generate a task arrangement syntax;

[0022] The JSON conversion orchestration syntax unit is used to convert the task orchestration syntax into JSON format for storage.

[0023] As a preferred embodiment of the present invention, the task management module includes a task editing unit, a task execution strategy configuration unit and a scheduling algorithm management unit;

[0024] The task editing unit is used to add, delete, modify and query tasks;

[0025] The task execution strategy configuration unit is used to configure the execution strategy according to the type and requirements of the task;

[0026] The scheduling algorithm management unit is used to select a priority algorithm for a task.

[0027] As a preferred embodiment of the present invention, the task scheduling module includes a task scheduling storage unit, a priority calculation unit, a load balancing strategy management unit and a scheduling allocation unit;

[0028] The task scheduling storage unit is constructed based on a time wheel algorithm for hierarchical storage and is used to store and schedule tasks;

[0029] The priority calculation unit is used to perform the priority of the task according to the selected priority algorithm;

[0030] The load balancing strategy management unit is used to manage the load balancing strategy of the task execution node;

[0031] The scheduling allocation unit is used to allocate execution nodes of tasks according to the load balancing strategy.

[0032] As a preferred embodiment of the present invention, the time wheel algorithm of the hierarchical storage is specifically:

[0033] The time wheel algorithm is divided into three levels, namely hour wheel, minute wheel and second wheel. Each level of the time wheel is equipped with a number of ticks for storing data.

[0034] A task information table and a time wheel data table are respectively constructed in the database, wherein the task information table is used to store task information, including task ID, task execution time, and task detailed information, and the time wheel data table is used to store data of each tick of the time wheel, including tick number, task ID list, and tick status;

[0035] The hour wheel includes 24 ticks, each tick stores a list of tasks with an execution time of one hour. The hour wheel rotates once every hour, reads tasks with an execution time of one hour that need to be executed 24 hours later from the database and allocates them to each tick, then stores the IDs of all tasks in the task list in the current tick into the task ID list, and deletes expired tick data at the same time;

[0036] The sub-wheel includes 60 ticks, each tick stores a task ID list with an execution time of one minute. The sub-wheel rotates once per minute, obtains the task ID list from the tick of the hour wheel, assigns the task ID list to the tick of the sub-wheel, and deletes the expired tick data in the sub-wheel. The tick data of the sub-wheel is stored in Redis;

[0037] The second wheel includes 60 ticks, each tick stores detailed information of the task to be executed in the current second. The minute wheel rotates once per second, and a task ID list is obtained from the tick of the minute wheel. A list of detailed information of the task is obtained through the task ID list, and the list of detailed information of the task is assigned to the tick of the second wheel. The list of detailed information of the task stored in the tick to which the second wheel currently rotates is pushed to the scheduling allocation unit, and expired tick data in the second wheel is deleted. The tick data of the second wheel is stored in Redis.

[0038] As a preferred embodiment of the present invention, the task execution module includes a task scheduling syntax parsing unit, a task thread pool management unit, a task resource occupancy calculation unit and a task retry unit;

[0039] The task scheduling syntax parsing unit is used to parse the task scheduling syntax and convert it into corresponding execution instructions;

[0040] The task thread pool management unit is used for allocating, recycling and monitoring task threads;

[0041] The task resource occupancy calculation unit is used to calculate the resource occupancy of each task;

[0042] The task retry unit is used to retry or notify the failed task according to a preset retry strategy.

[0043] On the other hand, the present invention also provides a distributed scheduled task processing method, comprising the following steps:

[0044] The basic components required are created through the basic component management unit, and the created basic components are orchestrated through the task process orchestration unit to obtain the task process and generate the task orchestration syntax. The task orchestration syntax is then converted into JSON format for saving through the JSON conversion orchestration syntax unit. Each JSON format file is a task template;

[0045] Set the task template attributes according to the requirements to generate the corresponding task instance, and parse the task call plan to determine the task execution time;

[0046] The task scheduling storage unit stores the tasks in the time wheel according to the execution time of the tasks;

[0047] In the task execution phase, the task execution strategy configuration unit, scheduling algorithm management unit and load balancing strategy management unit respectively determine the task execution strategy, scheduling algorithm and load balancing strategy, and then the task scheduling syntax parsing unit and task thread pool management unit determine the execution order and dependency of the tasks and select the thread pool;

[0048] During the task execution process, the task resource occupancy is calculated in real time by the task resource occupancy calculation unit and sent to the load balancing strategy management unit. The load balancing strategy management unit adjusts the load balancing strategy in real time according to the received information.

[0049] On the other hand, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present invention when executing the program.

[0050] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the present invention.

[0051] The present invention has the following beneficial effects:

[0052] 1. The present invention has achieved significant improvements in task scheduling accuracy, execution efficiency, management flexibility, and large-scale task processing capabilities based on hierarchical three-level time wheel task storage management. These advantages make the present invention have broad application prospects and important practical value in smart IoT scenarios, and provide strong support for the in-depth development of smart IoT technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a system module diagram of the present invention;

[0054] Figure 2 A schematic diagram of the time wheel algorithm for layered storage of the present invention;

[0055] Figure 3 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0058] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0059] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0060] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0061] Embodiment 1:

[0062] See also Figure 1 , a distributed scheduled task processing system, including a task template management module, a task management module, a task scheduling module and a task execution module;

[0063] The task template management module is used to create task templates and manage task templates;

[0064] The task management template is used to manage tasks generated based on the task template;

[0065] The task scheduling module is used to set the scheduling strategy of the task;

[0066] The task execution module is used to execute tasks.

[0067] As a preferred implementation of this embodiment, the task template management module includes a basic component management unit, a task flow orchestration unit, and a JSON conversion orchestration syntax unit;

[0068] The basic component management unit is used to create and manage basic components, which are basic units that constitute tasks. By effectively managing these components, the system can more flexibly combine and configure various tasks.

[0069] The task flow orchestration unit is used to orchestrate various basic components in a visual way to obtain task flows and generate task orchestration syntax. Users can use this function to drag and drop to orchestrate task flows in an intuitive way without having to have an in-depth understanding of complex programming syntax. This greatly reduces the difficulty of task configuration and improves work efficiency.

[0070] The JSON conversion orchestration syntax unit is used to convert the task orchestration syntax into JSON format for storage, so as to facilitate system parsing and execution.

[0071] As a preferred implementation of this embodiment, the task management module includes a task editing unit, a task execution strategy configuration unit and a scheduling algorithm management unit;

[0072] The task editing unit is used to add, delete, modify and query tasks to meet the ever-changing task requirements;

[0073] The task execution strategy configuration unit is used to configure the execution strategy according to the type and requirements of the task, such as scheduled execution, conditional triggering, etc.;

[0074] The scheduling algorithm management unit is used to select the priority algorithm of the task. The system provides priority algorithms such as First Come First Served (FCFS), Short Job Priority (SJF), High Response Ratio Priority, as well as load balancing algorithms such as Round Robin, Weighted Round Robin, Least Connections, Shortest Response Time, etc. for users to choose from to ensure that the task can be executed in the best way.

[0075] As a preferred implementation of this embodiment, the task scheduling module includes a task scheduling storage unit, a priority calculation unit, a load balancing strategy management unit and a scheduling allocation unit;

[0076] The task scheduling storage unit is constructed based on a time wheel algorithm of hierarchical storage and is used to store and schedule tasks. This design can ensure accurate triggering and efficient execution of tasks.

[0077] The priority calculation unit is used to prioritize tasks according to the selected priority algorithm to ensure that key tasks can be processed promptly and effectively;

[0078] The load balancing strategy management unit is used to manage the load balancing strategy of the task execution nodes to avoid the situation where some nodes are overloaded while other nodes are idle. The specific functions of the load balancing strategy include the following key links:

[0079] 1) Collect task execution node information: The task resource occupancy calculation function is used to obtain the load status of the real-time monitoring task node, including CPU usage, memory usage, disk I / O, network traffic, etc., in order to perform accurate load assessment.

[0080] 2) Select a scheduling algorithm: Select the most appropriate scheduling algorithm based on business requirements and server performance, such as Round Robin, Weighted Round Robin, Least Connections, Shortest Response Time, etc.

[0081] 3) Calculate node weight: According to the scheduling algorithm, the weight is calculated by the performance and current load of the task node.

[0082] The scheduling allocation unit is used to allocate execution nodes of tasks according to the load balancing strategy.

[0083] As a preferred implementation of this embodiment, see Figure 2 The time wheel algorithm of the hierarchical storage is specifically as follows:

[0084] The time wheel algorithm is divided into three levels, namely hour wheel, minute wheel and second wheel. Each level of the time wheel is equipped with a number of ticks for storing data.

[0085] A task information table and a time wheel data table are respectively constructed in the database, wherein the task information table is used to store task information, including task ID, task execution time, and task detailed information, and the time wheel data table is used to store data of each tick of the time wheel, including tick number, task ID list, and tick status;

[0086] The hour wheel includes 24 ticks, each tick stores a list of tasks with an execution time of one hour. The hour wheel rotates once every hour, reads tasks with an execution time of one hour that need to be executed 24 hours later from the database and allocates them to each tick, then stores the IDs of all tasks in the task list in the current tick into the task ID list, and deletes expired tick data at the same time;

[0087] The sub-wheel includes 60 ticks, each tick stores a task ID list with an execution time of one minute. The sub-wheel rotates once per minute, obtains the task ID list from the tick of the hour wheel, assigns the task ID list to the tick of the sub-wheel, and deletes the expired tick data in the sub-wheel. The tick data of the sub-wheel is stored in Redis for fast reading and updating;

[0088] The second wheel includes 60 ticks, each tick stores detailed information of the task to be executed in the current second, the minute wheel rotates once per second, a task ID list is obtained from the tick of the minute wheel, a list of detailed information of the task is obtained through the task ID list, the list of detailed information of the task is assigned to the tick of the second wheel, and the detailed information list of the task stored in the tick to which the second wheel currently rotates is pushed to the scheduling allocation unit, and expired tick data in the second wheel is deleted at the same time. The tick data of the second wheel is stored in Redis for fast reading and updating;

[0089] This three-level time wheel design of tiered storage adopts the following strategies to balance storage space and read performance.

[0090] Selection of storage media: The system selects different storage media based on the access frequency and performance requirements of the data. For example, the data of the hour wheel is stored in the database, which is suitable for long-term storage and query; while the data of the minute wheel and second wheel is stored in Redis, which is suitable for fast reading and updating. This selection of storage media helps to balance storage expenses and reading performance.

[0091] Dynamic task transfer: The system has designed a dynamic task transfer mechanism between different levels of time wheels. When a task is transferred from the hour wheel to the minute wheel and then to the second wheel, the system will dynamically adjust the position of the task in the time wheel according to the execution time of the task. This dynamic transfer reduces unnecessary storage space usage and ensures that tasks can be scheduled and executed in a timely manner.

[0092] Expired task management: The system will regularly check and delete or mark expired ticks to free up storage space and avoid wasting storage resources. This expired task management strategy helps maintain efficient use of storage space.

[0093] Data structure optimization: By using data structures such as linked lists to store tasks in each tick, the system can efficiently manage the task list, especially when the number of tasks is large. This data structure can reduce memory consumption and improve the performance of task scheduling.

[0094] As a preferred implementation of this embodiment, the task execution module includes a task scheduling syntax parsing unit, a task thread pool management unit, a task resource occupancy calculation unit and a task retry unit;

[0095] The task scheduling syntax parsing unit is used to parse the task scheduling syntax and convert it into corresponding execution instructions;

[0096] The task thread pool management unit is used for allocating, recycling and monitoring task threads;

[0097] The task resource occupancy calculation unit is used to calculate the resource occupancy of each task;

[0098] The task retry unit is used to retry the failed task according to a preset retry strategy or notify the user to manually process it, which greatly improves the task execution success rate and system reliability.

[0099] Embodiment 2:

[0100] See also Figure 3 , a distributed scheduled task processing method, used in the system described in embodiment 1, comprises the following steps:

[0101] The basic components required are created through the basic component management unit, and the created basic components are orchestrated through the task process orchestration unit to obtain the task process and generate the task orchestration syntax. The task orchestration syntax is then converted into JSON format for saving through the JSON conversion orchestration syntax unit. Each JSON format file is a task template;

[0102] Set the task template attributes according to the requirements to generate the corresponding task instance, and parse the task call plan to determine the task execution time;

[0103] The task scheduling storage unit stores the tasks in the time wheel according to the execution time of the tasks;

[0104] In the task execution phase, the task execution strategy configuration unit, scheduling algorithm management unit and load balancing strategy management unit respectively determine the task execution strategy, scheduling algorithm and load balancing strategy, and then the task scheduling syntax parsing unit and task thread pool management unit determine the execution order and dependency of the tasks and select the thread pool;

[0105] During the task execution process, the task resource occupancy is calculated in real time by the task resource occupancy calculation unit and sent to the load balancing strategy management unit. The load balancing strategy management unit adjusts the load balancing strategy in real time according to the received information.

[0106] Embodiment three:

[0107] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present invention when executing the program.

[0108] Embodiment 4:

[0109] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in any embodiment of the present invention is implemented.

[0110] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and 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 and c can be represented by: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0111] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0112] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0113] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), disk or optical disk, and other media that can store program codes.

[0114] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A distributed timed task processing system, characterized in that: It includes task template management module, task management module, task scheduling module and task execution module; The task template management module is used to create task templates and manage task templates; The task management template is used to manage tasks generated based on the task template; The task scheduling module is used to set the scheduling strategy of the task; The task execution module is used to execute tasks.

2. A distributed timed task processing system according to claim 1, characterized in that: The task template management module includes a basic component management unit, a task flow arrangement unit and a JSON conversion arrangement syntax unit; The basic component management unit is used to create and manage basic components, which are basic units constituting tasks; The task flow arrangement unit is used to arrange various basic components in a visual way to obtain a task flow and generate a task arrangement syntax; The JSON conversion orchestration syntax unit is used to convert the task orchestration syntax into JSON format for storage.

3. A distributed scheduled task processing system according to claim 1, characterized in that: The task management module includes a task editing unit, a task execution strategy configuration unit and a scheduling algorithm management unit; The task editing unit is used to add, delete, modify and query tasks; The task execution strategy configuration unit is used to configure the execution strategy according to the type and requirements of the task; The scheduling algorithm management unit is used to select a priority algorithm for a task.

4. A distributed timed task processing system according to claim 1, characterized in that: The task scheduling module includes a task scheduling storage unit, a priority calculation unit, a load balancing strategy management unit and a scheduling allocation unit; The task scheduling storage unit is constructed based on a time wheel algorithm for hierarchical storage and is used to store and schedule tasks; The priority calculation unit is used to perform the priority of the task according to the selected priority algorithm; The load balancing strategy management unit is used to manage the load balancing strategy of the task execution node; The scheduling allocation unit is used to allocate execution nodes of tasks according to the load balancing strategy.

5. A distributed timed task processing system according to claim 4, characterized in that: The time wheel algorithm for layered storage is specifically as follows: The time wheel algorithm is divided into three levels, namely hour wheel, minute wheel and second wheel. Each level of the time wheel is equipped with a number of ticks for storing data. A task information table and a time wheel data table are respectively constructed in the database, wherein the task information table is used to store task information, including task ID, task execution time, and task detailed information, and the time wheel data table is used to store data of each tick of the time wheel, including tick number, task ID list, and tick status; The hour wheel includes 24 ticks, each tick stores a list of tasks with an execution time of one hour. The hour wheel rotates once every hour, reads tasks with an execution time of one hour that need to be executed 24 hours later from the database and allocates them to each tick, then stores the IDs of all tasks in the task list in the current tick into the task ID list, and deletes expired tick data at the same time; The sub-wheel includes 60 ticks, each tick stores a task ID list with an execution time of one minute. The sub-wheel rotates once per minute, obtains the task ID list from the tick of the hour wheel, assigns the task ID list to the tick of the sub-wheel, and deletes the expired tick data in the sub-wheel. The tick data of the sub-wheel is stored in Redis; The second wheel includes 60 ticks, each tick stores detailed information of the task to be executed in the current second. The minute wheel rotates once per second, and a task ID list is obtained from the tick of the minute wheel. A list of detailed information of the task is obtained through the task ID list, and the list of detailed information of the task is assigned to the tick of the second wheel. The list of detailed information of the task stored in the tick to which the second wheel currently rotates is pushed to the scheduling allocation unit, and expired tick data in the second wheel is deleted. The tick data of the second wheel is stored in Redis.

6. A distributed scheduled task processing system according to claim 1, characterized in that: The task execution module includes a task scheduling syntax parsing unit, a task thread pool management unit, a task resource occupancy calculation unit and a task retry unit; The task scheduling syntax parsing unit is used to parse the task scheduling syntax and convert it into corresponding execution instructions; The task thread pool management unit is used for allocating, recycling and monitoring task threads; The task resource occupancy calculation unit is used to calculate the resource occupancy of each task; The task retry unit is used to retry or notify the failed task according to a preset retry strategy.

7. A distributed timed task processing method, characterized in that: The system for use in claims 1-6 comprises the following steps: The basic components required are created through the basic component management unit, and the created basic components are orchestrated through the task process orchestration unit to obtain the task process and generate the task orchestration syntax. The task orchestration syntax is then converted into JSON format for saving through the JSON conversion orchestration syntax unit. Each JSON format file is a task template; Set the task template attributes according to the requirements to generate the corresponding task instance, and parse the task call plan to determine the task execution time; The task scheduling storage unit stores the tasks in the time wheel according to the execution time of the tasks; In the task execution phase, the task execution strategy configuration unit, scheduling algorithm management unit and load balancing strategy management unit respectively determine the task execution strategy, scheduling algorithm and load balancing strategy, and then the task scheduling syntax parsing unit and task thread pool management unit determine the execution order and dependency of the tasks and select the thread pool; During the task execution process, the task resource occupancy is calculated in real time by the task resource occupancy calculation unit and sent to the load balancing strategy management unit. The load balancing strategy management unit adjusts the load balancing strategy in real time according to the received information.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to claim 7 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to claim 7 is implemented.

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