Resource scheduling method and system for intelligent agent

Abstract

The invention provides a resource scheduling method and system for agents, and the method comprises the steps: creating a corresponding agent cluster in real time according to a plurality of agents, and correspondingly inputting a target task into the agent cluster; in the process that the agent cluster correspondingly executes the target task, whether a target agent which cannot execute the target task exists in the agent cluster or not is judged in real time; and if it is judged in real time that a target agent which cannot execute the target task exists in the agent cluster, creating a corresponding target edge cloud in real time according to the agent cluster based on a preset rule, and correspondingly completing the target task through the target edge cloud. According to the method and the device, the corresponding target task can be effectively processed through the edge cloud created in real time, and the working efficiency is correspondingly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agent control, and particularly relates to a resource scheduling method and system for agents. Background Art

[0002] With the progress of technology and the rapid development of productivity, people have made remarkable progress in the field of industrial manufacturing, and agents such as drones and industrial robots have been developed, which facilitate people's work.

[0003] Among them, various existing agents need to occupy certain resources during the actual work process. Specifically, for example, some agents will occupy storage resources, and some agents will occupy computing power resources. Moreover, in the scenario of multi-agent cluster collaborative task execution, different agents can carry different storage and computing power resources. Therefore, it is necessary to perform corresponding scheduling on the resources occupied by each agent.

[0004] Furthermore, in the actual process of scheduling agent resources in the prior art, most of them need to collect a large amount of historical data and train a resource scheduling model according to the historical data, and finally complete the resource allocation through the resource scheduling model. However, although this method can ultimately complete the resource allocation to a certain extent, it requires a lot of resources in the early stage to construct the resource scheduling model, thus having certain limitations in use, and at the same time, the allocation cost is relatively high, corresponding to a reduction in work efficiency. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a resource scheduling method and system for agents to solve the problems in the prior art that a large amount of resources are required in the early stage to construct a resource scheduling model, resulting in certain limitations in use and relatively high allocation costs.

[0006] The first aspect of the embodiment of the present invention proposes: A resource scheduling method for agents, wherein the method includes: According to a number of agents, create a corresponding agent cluster in real time, and input a target task into the agent cluster correspondingly; During the process of the agent cluster executing the target task correspondingly, determine in real time whether there is a target agent in the agent cluster that cannot execute the target task; If it is determined in real time that there is a target agent in the agent cluster that cannot execute the target task, create a corresponding target edge cloud in real time according to the agent cluster based on a preset rule, and complete the target task through the target edge cloud.

[0007] The beneficial effects of the present invention are as follows: By detecting a number of intelligent agents in real time, an intelligent agent cluster for processing data can be created in real time. Based on this, only by inputting the target task into the intelligent agent cluster, it can be determined in real time whether there are target intelligent agents that cannot execute the task. Based on this, a target edge cloud capable of processing the current target task can be created in real time based on the current target intelligent agent, so as to reasonably complete the resource scheduling among the intelligent agents, eliminate the limitations of use, and correspondingly greatly improve the work efficiency.

[0008] Further, the step of determining in real time whether there are target intelligent agents in the intelligent agent cluster that cannot execute the target task includes: When the target task is obtained in real time, a full scan of the target task is performed to detect in real time a number of processing items included in the target task; Sub-tasks respectively corresponding to each of the processing items are detected in real time, and each sub-task is unique; Based on each sub-task, it is determined in real time whether there is the target intelligent agent in the intelligent agent cluster, and the target intelligent agent is unique.

[0009] Further, the step of determining in real time whether there is the target intelligent agent in the intelligent agent cluster based on each sub-task includes: When each sub-task is obtained in real time, the task attributes respectively corresponding to each sub-task are detected in real time, and based on the task attributes, initial intelligent agents adapted to each sub-task are respectively matched in the intelligent agent cluster; The data processing amounts respectively corresponding to each initial intelligent agent are detected in real time, and the task amounts respectively corresponding to each sub-task are detected in real time; Based on the data processing amount and the task amount, it is determined in real time whether there is the target intelligent agent in the intelligent agent cluster, and both the data processing amount and the task amount are specific numerical values.

[0010] Further, the step of determining in real time whether there is the target intelligent agent in the intelligent agent cluster based on the data processing amount and the task amount includes: When the data processing amount corresponding to the initial intelligent agent and the task amount corresponding to the sub-task corresponding thereto are obtained in real time, it is determined in real time whether the data processing amount is greater than the task amount; If it is determined in real time that the data processing amount is less than the task amount, the initial intelligent agent corresponding to the current data processing amount being less than the task amount is set as the target intelligent agent, where one initial intelligent agent corresponds to only one sub-task.

[0011] Further, the step of creating the corresponding target edge cloud according to the preset rules based on the intelligent agent cluster includes: When the target intelligent agent is determined in real time, the communication range corresponding to the target intelligent agent is detected in real time, and the communication range includes a specific length; Based on the communication range, the target edge cloud is created in real time according to the target intelligent agent, and the target edge cloud is unique.

[0012] Further, the step of creating the target edge cloud in real time according to the target intelligent agent based on the communication range includes: When the communication range of the target intelligent agent is determined in real time, with the target intelligent agent as the center, a communication area corresponding to the target intelligent agent is created in real time in the intelligent agent cluster according to the communication range, and the communication area is circular; The communication area is scanned comprehensively to detect in real time a number of neighboring intelligent agents included in the communication area, and the target edge cloud is created in real time according to the target intelligent agent and the number of neighboring intelligent agents, and each neighboring intelligent agent is unique.

[0013] Further, the step of creating the target edge cloud in real time according to the target intelligent agent and the number of neighboring intelligent agents includes: When a number of neighboring intelligent agents are obtained in real time, a corresponding target communication network is created in real time according to the target intelligent agent and the number of neighboring intelligent agents; The target communication network and a preset edge algorithm are fused to generate a corresponding target edge network in real time, and the target edge network is uploaded to the cloud in real time to generate the target edge cloud in real time, and the target edge network is unique.

[0014] In the second aspect of the embodiments of the present invention, it is proposed that: A resource scheduling system for intelligent agents, wherein the system includes: An input module, configured to create a corresponding intelligent agent cluster according to a number of intelligent agents in real time, and input a target task into the intelligent agent cluster correspondingly; A judgment module, configured to judge in real time whether there is a target intelligent agent in the intelligent agent cluster that cannot execute the target task during the process of the intelligent agent cluster executing the target task; An execution module, configured to, if it is judged in real time that there is a target intelligent agent in the intelligent agent cluster that cannot execute the target task, create a corresponding target edge cloud according to the intelligent agent cluster based on preset rules, and complete the target task through the target edge cloud.

[0015] Further, the judgment module is specifically configured to: When the target task is obtained in real time, perform a full scan on the target task to detect in real time a number of processing items included in the target task; Detect in real time sub-tasks respectively corresponding to each of the processing items, and each sub-task is unique; According to each sub-task, determine in real time whether there is a target intelligent agent in the intelligent agent cluster, and the target intelligent agent is unique.

[0016] Further, the judgment module is specifically configured to: When each sub-task is obtained in real time, detect in real time task attributes respectively corresponding to each sub-task, and respectively match initial intelligent agents adapted to each sub-task in the intelligent agent cluster according to the task attributes; Detect in real time the data processing volume respectively corresponding to each initial intelligent agent, and detect in real time the task volume respectively corresponding to each sub-task; According to the data processing volume and the task volume, determine in real time whether there is a target intelligent agent in the intelligent agent cluster, and both the data processing volume and the task volume are specific numerical values.

[0017] Further, the judgment module is specifically configured to: When the data processing volume corresponding to the initial intelligent agent and the task volume corresponding to the sub-task corresponding to it are obtained in real time, determine in real time whether the data processing volume is greater than the task volume; If it is determined in real time that the data processing volume is less than the task volume, then set the initial intelligent agent corresponding to the current data processing volume being less than the task volume as the target intelligent agent, where one initial intelligent agent corresponds to only one sub-task.

[0018] Further, the execution module is specifically configured to: When the target intelligent agent is determined in real time, detect in real time the communication range corresponding to the target intelligent agent, and the communication range includes a specific length; Based on the communication range, create the target edge cloud in real time according to the target intelligent agent, and the target edge cloud is unique.

[0019] Further, the execution module is specifically configured to: When the communication range of the target intelligent agent is determined in real time, with the target intelligent agent as the center, create in real time a communication area corresponding to the target intelligent agent in the intelligent agent cluster according to the communication range, and the communication area is circular; Perform a full scan of the communication area to detect in real time a number of neighboring agents contained in the communication area, and create the target edge cloud in real time according to the target agent and the number of neighboring agents. Each neighboring agent is unique.

[0020] Further, the execution module is specifically configured to: When a number of neighboring agents are obtained in real time, create a corresponding target communication network in real time according to the target agent and the number of neighboring agents; Perform a fusion process on the target communication network and a preset edge algorithm to generate a corresponding target edge network in real time, and upload the target edge network to the cloud in real time to generate the target edge cloud in real time. The target edge network is unique.

[0021] The third aspect of the embodiments of the present invention proposes: A computer includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the resource scheduling method for agents as described above.

[0022] The fourth aspect of the embodiments of the present invention proposes: A readable storage medium stores a computer program thereon. When the program is executed by a processor, it implements the resource scheduling method for agents as described above.

[0023] The additional aspects and advantages of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention. Description of the Drawings

[0024] Figure 1 It is a flowchart of the resource scheduling method for agents provided by the first embodiment of the present invention; Figure 2 It is a structural block diagram of the resource scheduling system for agents provided by the third embodiment of the present invention.

[0025] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. Specific Embodiments

[0026] To facilitate the understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0027] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected to" another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs. The terms used herein in the specification of this invention are for the purpose of describing specific embodiments only and are not intended to limit the invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0029] Please refer to Figure 1 , which shows a resource scheduling method for an agent provided by the first embodiment of the present invention. The resource scheduling method for an agent provided in this embodiment can timely process the target tasks that the agent cannot complete through the edge cloud created in real time, correspondingly greatly improving the work efficiency.

[0030] Specifically, this embodiment provides: A resource scheduling method for an agent, specifically including the following steps: Step S10, creating a corresponding agent cluster according to a number of agents in real time, and inputting the target task into the agent cluster correspondingly; Step S20, during the process of the agent cluster correspondingly executing the target task, judging in real time whether there is a target agent in the agent cluster that cannot execute the target task; Step S30, if it is judged in real time that there is a target agent in the agent cluster that cannot execute the target task, then creating a corresponding target edge cloud according to the agent cluster based on a preset rule, and completing the target task through the target edge cloud.

[0031] Specifically, in this embodiment, it should be noted first that in order to successfully execute each target task, it is necessary to obtain the required task information and agent information in real time. At this time, it is necessary to parse and process the working states of several existing agents. Specifically, it should be noted that the resource scheduling method provided by the present invention is mainly implemented for the existing agent cluster, that is, for real-time scheduling of resources in the existing agent cluster. Among them, it should be pointed out that the resources specifically include computing power resources and storage resources, etc. Based on this, in the actual application process, in order to improve work efficiency, the present invention will integrate several agents detected in real time, that is, create a corresponding agent cluster in real time according to the current several agents. Based on this, it is possible to send corresponding tasks to the current agent cluster. Specifically, in the process of the agent cluster executing tasks, it is inevitable that a certain agent cannot complete the task. Based on this, the present invention will mark the tasks that the current agent cannot complete and set them as the required target tasks for subsequent processing.

[0032] Furthermore, after the target tasks required are determined in real time through the above steps, the server set in the background can immediately create a corresponding target edge cloud based on the current agent cluster according to the pre-set rules. Among them, it should be pointed out that the existing edge cloud is a data processing system, but its characteristic is that it can be set on edge devices, and the edge devices can complete a large amount of data processing with less resources. Based on this, the target edge cloud created in real time by the present invention can effectively meet the processing requirements of the above target tasks and can be successfully executed, so that the above agent cluster can continuously and effectively be in a stable working state, correspondingly greatly improving work efficiency and at the same time improving the user experience.

[0033] Second Embodiment Furthermore, the step of real-time judging whether there is a target agent in the agent cluster that cannot execute the target task includes: When the target task is obtained in real time, perform a full scan on the target task to detect several processing items included in the target task in real time; Detect in real time the subtasks corresponding to each of the processing items, and each subtask is unique; According to each subtask, judge in real time whether there is the target agent in the agent cluster, and the target agent is unique.

[0034] Furthermore, the step of judging in real time whether there is the target agent in the agent cluster according to each subtask includes: When each of the subtasks is obtained in real time, the task attributes respectively corresponding to each of the subtasks are detected in real time, and initial agents adapted to each of the subtasks are respectively matched in the agent cluster according to the task attributes; The data processing amounts respectively corresponding to each of the initial agents are detected in real time, and the task amounts respectively corresponding to each of the subtasks are detected in real time; According to the data processing amount and the task amount, it is determined in real time whether there is a target agent in the agent cluster, and both the data processing amount and the task amount are specific values.

[0035] Further, the step of determining in real time whether there is a target agent in the agent cluster according to the data processing amount and the task amount includes: When the data processing amount corresponding to the initial agent and the task amount corresponding to the subtask corresponding to it are obtained in real time, it is determined in real time whether the data processing amount is greater than the task amount; If it is determined in real time that the data processing amount is less than the task amount, the initial agent corresponding to the current data processing amount being less than the task amount is set as the target agent, where one initial agent only corresponds to one subtask.

[0036] Further, the step of creating a corresponding target edge cloud in real time according to the agent cluster based on a preset rule includes: When the target agent is determined in real time, the communication range corresponding to the target agent is detected in real time, and the communication range includes a specific length; Based on the communication range, the target edge cloud is created in real time according to the target agent, and the target edge cloud is unique.

[0037] Further, the step of creating the target edge cloud in real time according to the target agent based on the communication range includes: When the communication range of the target agent is determined in real time, with the target agent as the center, a communication area corresponding to the target agent is created in real time in the agent cluster according to the communication range, and the communication area is circular; The communication area is scanned comprehensively to detect in real time a number of neighboring agents included in the communication area, and the target edge cloud is created in real time according to the target agent and the number of neighboring agents, and each neighboring agent is unique.

[0038] Further, the step of creating the target edge cloud in real time according to the target agent and a number of neighboring agents includes: When a number of the neighboring agents are obtained in real time, a corresponding target communication network is created in real time according to the target agent and the number of the neighboring agents; The target communication network and a preset edge algorithm are subjected to fusion processing to generate a corresponding target edge network in real time, and the target edge network is uploaded to the cloud in real time to generate the target edge cloud in real time. The target edge network is unique.

[0039] In addition, in this embodiment, it should also be noted that after the required target task is obtained in real time through the above steps, it is necessary to immediately perform parsing processing on the current target task, that is, it is necessary to determine in real time whether there is a problem that the target task cannot be processed inside the intelligent agent cluster. Based on this, the present invention will first perform a full scan of the current target task. It should be pointed out that since existing target tasks are all composed of a series of events, that is, a target task usually contains several processing items. Based on this, the present invention will detect in real time the subtasks corresponding to each current processing item again, and each subtask is unique. Based on this, in order to objectively and accurately determine whether each current subtask can be executed, the present invention will detect in real time the task attributes corresponding to each current subtask. Specifically, for the sake of easy understanding, for example, the task attribute can be a data caching task, a data encryption task, a data transmission task, etc., so that the initial intelligent agents adapted to each current subtask can be directly matched inside the intelligent agent cluster according to the current task attribute. At the same time, the data processing amounts that each current initial intelligent agent can respectively complete, and the task amounts respectively included in each current subtask can be synchronously detected. On this basis, it can be determined in real time whether there is a situation where the data processing amount of the initial intelligent agent in the current intelligent agent cluster is less than the task amount of the current subtask. Specifically, if not, it can directly indicate that each current subtask can be completed. Correspondingly, if so, it can be directly determined that there is a phenomenon that the intelligent agent cannot complete the subtask. Based on this, it is necessary to mark in real time the initial intelligent agent that cannot complete the corresponding subtask, and set the initial intelligent agent at the marked position as the above-mentioned target agent for subsequent processing.

[0040] Further, after the required target agent is determined in real time through the above steps, in order to successfully complete the subtask, the present invention will, based on the current target agent, create a corresponding target edge cloud in real time. Specifically, the present invention will first detect the communication range that the current target agent can reach. Based on this, with the current target agent as the center, and correspondingly detect the length of the current communication range. At the same time, with the length of the current communication range as the radius, a required communication area will be correspondingly divided in the above agent cluster. It can be understood that this communication area is circular. Based on this, for the convenience of subsequent implementation, the present invention will perform a corresponding full scan within the range of the current communication area, and can scan out in real time the neighboring agents that are adapted to the current target agent in the current communication area, that is, the agents close to the current target agent. Based on this, the present invention will immediately create a corresponding target communication network according to the current target agent and several neighboring agents. It should be noted that, in order to enable this target communication network to be adapted to existing edge devices, the present invention will again fuse the existing edge algorithm into the current target communication network to form a corresponding target edge network. On this basis, the target edge network will finally be uploaded to the cloud correspondingly, so as to form a corresponding target edge cloud, so that the target edge cloud can execute the corresponding task, improving work efficiency.

[0041] Please refer to Figure 2 , the third embodiment of the present invention provides: A resource scheduling system for agents, wherein the system includes: An input module, configured to create a corresponding agent cluster according to several agents in real time, and input a target task into the agent cluster correspondingly; A judgment module, configured to, during the process of the agent cluster correspondingly executing the target task, judge in real time whether there is a target agent in the agent cluster that cannot execute the target task; An execution module, configured to, if it is judged in real time that there is a target agent in the agent cluster that cannot execute the target task, create a corresponding target edge cloud according to the agent cluster based on a preset rule, and complete the target task through the target edge cloud.

[0042] Further, the judgment module is specifically configured to: When the target task is obtained in real time, perform a full scan on the target task to detect in real time several processing items included in the target task; Detect in real time the subtasks corresponding to each of the processing items respectively, and each subtask is unique; Determine in real time whether there is a target agent in the agent cluster according to each of the sub-tasks, and the target agent is unique.

[0043] Further, the determination module is specifically configured to: When each sub-task is obtained in real time, detect in real time the task attributes corresponding to each sub-task respectively, and match in the agent cluster the initial agents adapted to each sub-task respectively according to the task attributes; Detect in real time the data processing amount corresponding to each initial agent respectively, and detect in real time the task amount corresponding to each sub-task respectively; Determine in real time whether there is a target agent in the agent cluster according to the data processing amount and the task amount, and both the data processing amount and the task amount are specific numerical values.

[0044] Further, the determination module is specifically configured to: When the data processing amount corresponding to the initial agent and the task amount corresponding to the sub-task corresponding thereto are obtained in real time, determine in real time whether the data processing amount is greater than the task amount; If it is determined in real time that the data processing amount is less than the task amount, then set the initial agent corresponding to the current data processing amount being less than the task amount as the target agent, where one initial agent corresponds to only one sub-task.

[0045] Further, the execution module is specifically configured to: When the target agent is determined in real time, detect in real time the communication range corresponding to the target agent, and the communication range includes a specific length; Create the target edge cloud in real time based on the communication range according to the target agent, and the target edge cloud is unique.

[0046] Further, the execution module is specifically configured to: When the communication range of the target agent is determined in real time, with the target agent as the center, create in real time in the agent cluster a communication area corresponding to the target agent according to the communication range, and the communication area is circular; Perform a full scan of the communication area to detect in real time a number of neighboring agents included in the communication area, and create the target edge cloud in real time according to the target agent and the number of neighboring agents, and each neighboring agent is unique.

[0047] Further, the execution module is specifically configured to: When a number of the neighboring agents are obtained in real time, a corresponding target communication network is created in real time according to the target agent and the number of the neighboring agents; The target communication network and a preset edge algorithm are fused to generate a corresponding target edge network in real time, and the target edge network is uploaded to the cloud in real time to generate the target edge cloud in real time. The target edge network is unique.

[0048] A fourth embodiment of the present invention provides a computer, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the resource scheduling method for agents as described above is implemented.

[0049] A fifth embodiment of the present invention provides a readable storage medium, on which a computer program is stored. When the program is executed by a processor, the resource scheduling method for agents as described above is implemented.

[0050] In summary, the resource scheduling method and system for agents provided in the above embodiments of the present invention can timely process the target tasks that cannot be completed by agents through the edge cloud constructed in real time, correspondingly greatly improving the work efficiency.

[0051] It should be noted that the above-mentioned each module can be a functional module or a program module, and can be implemented by software or by hardware. For the modules implemented by hardware, the above-mentioned each module can be located in the same processor; or the above-mentioned each module can also be located in different processors in any combined form.

[0052] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0053] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0054] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, the multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0055] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0056] The above-described embodiments merely represent several implementation manners of the present invention, and their descriptions are relatively specific and detailed, but should not be construed as limiting the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. A resource scheduling method for an agent, characterized in that, The method includes: According to a number of agents, corresponding agent clusters are created in real time, and the target task is correspondingly input into the agent clusters; During the process of the agent clusters correspondingly executing the target task, it is judged in real time whether there are target agents in the agent clusters that cannot execute the target task; If it is judged in real time that there are target agents in the agent clusters that cannot execute the target task, a corresponding target edge cloud is created in real time based on the preset rules according to the agent clusters, and the target task is completed correspondingly through the target edge cloud.

2. The resource scheduling method for an agent according to claim 1, characterized in that: The step of judging in real time whether there are target agents in the agent clusters that cannot execute the target task includes: When the target task is obtained in real time, a full scan is performed on the target task to detect in real time a number of processing items included in the target task; Sub-tasks respectively corresponding to each of the processing items are detected in real time, and each sub-task is unique; According to each sub-task, it is judged in real time whether there is a target agent in the agent clusters, and the target agent is unique.

3. The resource scheduling method for an agent according to claim 2, characterized in that: The step of judging in real time whether there is a target agent in the agent clusters according to each sub-task includes: When each sub-task is obtained in real time, the task attributes respectively corresponding to each sub-task are detected in real time, and initial agents adapted to each sub-task are respectively matched in the agent clusters according to the task attributes; The data processing amounts respectively corresponding to each of the initial agents are detected in real time, and the task amounts respectively corresponding to each sub-task are detected in real time; According to the data processing amount and the task amount, it is judged in real time whether there is a target agent in the agent clusters, and both the data processing amount and the task amount are specific values.

4. The resource scheduling method for an agent according to claim 3, wherein: The step of judging in real time whether there is a target agent in the agent clusters according to the data processing amount and the task amount includes: When the data processing amount corresponding to the initial agent and the task amount corresponding to the sub-task corresponding to it are obtained in real time, it is judged in real time whether the data processing amount is greater than the task amount; If it is judged in real time that the data processing amount is less than the task amount, the initial agent corresponding to the current data processing amount being less than the task amount is correspondingly set as the target agent, where one initial agent only corresponds to one sub-task.

5. The resource scheduling method for an agent according to claim 4, wherein: The step of creating a corresponding target edge cloud in real time based on the preset rules according to the agent clusters includes: When the target agent is determined in real time, the communication range corresponding to the target agent is detected in real time, and the communication range includes a specific length; Based on the communication range, the target edge cloud is created in real time according to the target agent, and the target edge cloud is unique.

6. The resource scheduling method for an agent according to claim 5, wherein: The step of creating the target edge cloud in real time based on the communication range according to the target agent includes: When the communication range of the target agent is determined in real time, a communication area corresponding to the target agent is created in real time in the agent cluster centered on the target agent according to the communication range, and the communication area is circular; Perform a full scan of the communication area to detect in real time a number of neighboring agents included in the communication area, and create the target edge cloud in real time according to the target agent and the number of neighboring agents, and each neighboring agent is unique.

7. The resource scheduling method for an agent according to claim 6, wherein: The step of creating the target edge cloud in real time according to the target agent and the number of neighboring agents includes: When a number of neighboring agents are obtained in real time, create a corresponding target communication network in real time according to the target agent and the number of neighboring agents; Perform a fusion process on the target communication network and a preset edge algorithm to generate a corresponding target edge network in real time, and upload the target edge network to the cloud in real time to generate the target edge cloud in real time, and the target edge network is unique.

8. A resource scheduling system for an agent, characterized in that, The system includes: An input module, configured to create a corresponding agent cluster in real time according to a number of agents, and input a target task into the agent cluster correspondingly; A judgment module, configured to judge in real time whether there is a target agent in the agent cluster that cannot execute the target task during the process of the agent cluster executing the target task; An execution module, configured to, if it is judged in real time that there is a target agent in the agent cluster that cannot execute the target task, create a corresponding target edge cloud in real time according to the agent cluster based on a preset rule, and complete the target task through the target edge cloud.

9. A computer, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the resource scheduling method for agents according to any one of claims 1 to 7.

10. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the resource scheduling method for agents according to any one of claims 1 to 7.

Images