Intelligent collaborative management edge computing internet-of-things equipment system and method

Abstract

The invention relates to the technical field of Internet of Things, in particular to an intelligent collaborative management edge computing Internet of Things equipment system and method.The method comprises the steps that local task execution strategies of all edge computing Internet of Things equipment are collected, and process expected attribute information is extracted from the local task execution strategies; according to the process expected attribute information and the historical work record of the edge computing internet-of-things equipment, identifying processes which cannot be processed locally and deadline information of the processes; performing process transfer feasibility verification on other edge computing internet-of-things equipment; according to the deadline information, carrying out local process transfer operation which cannot be processed; selecting a standby communication link according to a routing state in the Internet of Things; and adjusting the docking state of the standby communication link according to the processing live condition of the local unhandled process during the transfer period. By collecting task execution strategies for all edge computing Internet of Things devices and identifying and transferring processes which cannot be processed locally, collaborative management of different edge computing Internet of Things devices is realized, and normal operation of the Internet of Things in a full range is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things, and in particular to an edge computing Internet of Things device system and method for intelligent collaborative management. BACKGROUND

[0002] As a distributed network, the Internet of Things has a cloud, edge computing devices and user terminals inside; among them, the edge computing devices are directly connected with the user terminals and are used to process data from the user terminals. Generally speaking, the Internet of Things will set appropriate edge computing devices according to the layout of the user terminals to ensure that the data from the user terminals is processed in time and accurately. When the edge computing devices cannot effectively handle the data from the user terminals due to internal or external reasons, the edge computing devices will call for computing resources or memory resources from the cloud to complete their own data processing tasks. Considering that there are a large number of edge computing devices inside the Internet of Things, the cloud needs to cope with the resource calling demands of multiple edge computing devices at the same time, which not only increases its own workload but also affects the running stability of the entire Internet of Things. The edge computing devices inside the Internet of Things have corresponding running resources, and at present, the Internet of Things does not fully utilize the idle resources of the edge computing devices, cannot perform resource collaborative management between different edge computing devices, and cannot guarantee the normal operation of the Internet of Things in the whole range, thereby reducing the reliability and stability of the edge computing Internet of Things devices. SUMMARY

[0003] Considering that the edge computing Internet of Things devices inside the Internet of Things all meet their own resource needs through the cloud, different edge computing Internet of Things devices cannot transfer task processes, and cannot perform resource collaborative management between different edge computing Internet of Things devices, which affects the normal operation of the Internet of Things in the whole range and reduces the reliability and stability of the edge computing Internet of Things devices. In view of the above problems, the present application is proposed to provide an edge computing Internet of Things device system for intelligent collaborative management to overcome the above problems or at least partially solve the above problems, which comprises: An execution strategy acquisition module is configured to collect local task execution strategies of all edge computing Internet of Things devices; A process attribute determination module is configured to extract process expected attribute information from the local task execution strategies; A process identification module is configured to identify a local unhandleable process and its deadline information according to the process expected attribute information and historical work records of the edge computing Internet of Things devices; A transfer verification module is configured to initiate a process receiving inquiry to the Internet of Things, and to perform a process transfer feasibility verification on other edge computing Internet of Things devices responding to the inquiry; A transfer operation module is configured to perform a local unhandleable process transfer operation according to the deadline information; A link control module is configured to select a backup communication link according to a routing state within the Internet of Things, and adjust a docking state of the backup communication link according to a processing status of the local unprocessable process during the transfer.

[0004] Optionally, the execution strategy acquisition module is configured to collect respective local task execution strategies of all edge computing Internet of Things devices, including: According to an access node of all edge computing Internet of Things devices in the Internet of Things, cluster monitoring is implemented on all edge computing Internet of Things devices; wherein the cluster monitoring refers to time-sharing monitoring on part of the edge computing Internet of Things devices whose network distance to the access node meets a preset distance condition. According to the device identity, running records of all edge computing Internet of Things devices are extracted from the cluster monitoring log; content screening is performed on the running records to obtain a local task execution strategy of the edge computing Internet of Things device; wherein the local task execution strategy includes process segmentation information and process content information of the local task. The process attribute determination module is configured to extract process expected attribute information from the local task execution strategy, including: According to the process segmentation information and the process content information, expected attribute information of all processes under the local task execution strategy is determined; wherein the expected attribute information includes expected occupied resources and expected processing load of the process locally.

[0005] Optionally, the process identification module is configured to identify a local unprocessable process and its deadline information according to the process expected attribute information and historical working records of the edge computing Internet of Things device, including: The expected occupied resources of the process expected attribute information are compared with historical resource providing records of the edge computing Internet of Things device to determine whether a resource shortage event occurs in the edge computing Internet of Things device; The expected processing load of the process expected attribute information is compared with historical downtime occurrence records of the edge computing Internet of Things device to determine whether a failure event occurs in the edge computing Internet of Things device; When the resource shortage event or the failure event occurs, the corresponding process is determined as the local unprocessable process, and deadline information of the local unprocessable process during execution of the task in which the local unprocessable process is located is obtained; wherein the deadline information refers to the latest completion time information of the local unprocessable process.

[0006] Optionally, the transfer verification module is configured to initiate a process receiving inquiry to the Internet of Things, and perform process transfer feasibility verification on other edge computing Internet of Things devices responding to the inquiry, including: Based on the attribute tags of the processes that cannot be processed locally, a process reception query is initiated to the Internet of Things; wherein the attribute tags include the type tag and data volume tag of the processes that cannot be processed locally. Perform program configuration verification on the type label and computing power configuration verification on the data volume label on other edge computing IoT devices responding to the inquiry, thereby identifying a number of edge computing IoT devices that have passed the process transfer feasibility verification; The transfer operation module is used to perform a process transfer operation that cannot be processed locally based on the time limit information, including: Based on the aforementioned time limit information, a second query is performed on several other edge computing IoT devices that have passed the process transfer feasibility verification, thereby packaging and transferring the processes that cannot be processed locally to one of the edge computing IoT devices that have passed the process transfer feasibility verification.

[0007] Optionally, the link control module is used to select a backup communication link based on the routing status within the Internet of Things; and to adjust the connection status of the backup communication link based on the processing status of the locally unprocessable process during the transfer, including: Extract the routing occupancy time-domain distribution data within the Internet of Things (IoT) from the routing operation records of the IoT; select a backup communication link based on the routing occupancy time-domain distribution data; wherein the backup communication link refers to a communication link within the IoT whose maximum continuous idle time is greater than a preset time threshold; Based on the correct processing result of the locally unprocessable process during the transfer, a real-time situation is generated to determine whether the locally unprocessable process has completed processing; if so, the backup communication link is instructed to connect with the edge computing IoT device where the locally unprocessable process is currently located; if not, the backup communication link is not instructed to perform a connection operation.

[0008] As one aspect of the present invention, embodiments of the present invention also provide a method for intelligent collaborative management of edge computing IoT devices, including: Step S1: Collect the local task execution strategies of all edge computing IoT devices, and extract the expected process attribute information from the local task execution strategies; Step S2: Based on the expected attribute information of the process and the historical working records of the edge computing IoT device, identify the processes that cannot be processed locally and their time limits; Step S3: Initiate a process reception query to the Internet of Things (IoT), and perform process transfer feasibility verification on other edge computing IoT devices that respond to the query; perform process transfer operations that cannot be processed locally based on the time limit information. Step S4: Select a backup communication link based on the routing status within the Internet of Things; adjust the connection status of the backup communication link based on the processing status of the locally unprocessable process during the transfer.

[0009] Optionally, in step S1, the local task execution strategies of all edge computing IoT devices are collected, and process expectation attribute information is extracted from the local task execution strategies, including: Based on the access nodes of all edge computing IoT devices in the Internet of Things, clustered monitoring is implemented on all edge computing IoT devices; wherein the clustered monitoring refers to time-division monitoring of a portion of the edge computing IoT devices whose network distance from the access node meets the preset distance condition; Based on the device identity, the operation records of all edge computing IoT devices are extracted from the clustered monitoring logs; the operation records are filtered to obtain the local task execution strategy of the edge computing IoT devices; wherein the local task execution strategy includes process segmentation information and process content information of local tasks; Based on the process segmentation information and the process content information, the expected attribute information of each process under the local task execution strategy is determined; wherein, the expected attribute information includes the expected resource consumption and expected processing load of the process locally.

[0010] Optionally, in step S2, based on the expected process attribute information and the historical working records of the edge computing IoT device, the process that cannot be processed locally and its time limit information are identified, including: By comparing the expected resource usage of the process's expected attribute information with the historical resource provision records of the edge computing IoT device, it is determined whether the edge computing IoT device has experienced a resource shortage event. By comparing the expected processing load of the process expected attribute information with the historical downtime records of the edge computing IoT device, it is determined whether the edge computing IoT device has experienced a failure event. When a resource shortage event or failure event occurs, the corresponding process is identified as a locally unprocessable process, and the time limit information of the locally unprocessable process during the execution of its task is obtained; wherein the time limit information refers to the latest completion time information of the locally unprocessable process.

[0011] Optionally, in step S3, a process reception query is initiated to the Internet of Things (IoT), and process transfer feasibility verification is performed on other edge computing IoT devices that respond to the query; based on the time limit information, a process transfer operation that cannot be processed locally is performed, including: Based on the attribute tags of the processes that cannot be processed locally, a process reception query is initiated to the Internet of Things; wherein the attribute tags include the type tag and data volume tag of the processes that cannot be processed locally. Perform program configuration verification on the type label and computing power configuration verification on the data volume label on other edge computing IoT devices responding to the inquiry, thereby identifying a number of edge computing IoT devices that have passed the process transfer feasibility verification; Based on the aforementioned time limit information, a second query is performed on several other edge computing IoT devices that have passed the process transfer feasibility verification, thereby packaging and transferring the processes that cannot be processed locally to one of the edge computing IoT devices that have passed the process transfer feasibility verification.

[0012] Optionally, in step S4, a backup communication link is selected based on the routing status within the Internet of Things; the connection status of the backup communication link is adjusted based on the processing status of the locally unprocessable process during the transfer, including: Extract the routing occupancy time-domain distribution data within the Internet of Things (IoT) from the routing operation records of the IoT; select a backup communication link based on the routing occupancy time-domain distribution data; wherein the backup communication link refers to a communication link within the IoT whose maximum continuous idle time is greater than a preset time threshold; Based on the correct processing result of the locally unprocessable process during the transfer, a real-time situation is generated to determine whether the locally unprocessable process has completed processing; if so, the backup communication link is instructed to connect with the edge computing IoT device where the locally unprocessable process is currently located; if not, the backup communication link is not instructed to perform a connection operation.

[0013] The beneficial effects of the above-mentioned technical solutions provided in the embodiments of the present invention include at least the following: This invention provides an intelligent collaborative management system and method for edge computing IoT devices. It collects the local task execution strategies of all edge computing IoT devices and extracts expected process attribute information from these strategies. Based on the expected process attribute information and the historical work records of the edge computing IoT devices, it identifies locally unprocessable processes and their time limits. It initiates a process reception query to the IoT and verifies the feasibility of process transfer for other responding edge computing IoT devices. Based on the time limit information, it performs a process transfer operation for locally unprocessable processes. It selects a backup communication link based on the routing status within the IoT. Based on the processing status of locally unprocessable processes during the transfer, it adjusts the connection status of the backup communication link. By collecting task execution strategies from all edge computing IoT devices and identifying and transferring locally unprocessable processes, collaborative management of different edge computing IoT devices is achieved, ensuring the normal operation of the entire IoT ecosystem.

[0014] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the structure of the intelligent collaborative management edge computing IoT device system provided in this embodiment of the invention; Figure 2 This is a flowchart illustrating the edge computing IoT device method for intelligent collaborative management provided in an embodiment of the present invention. Detailed Implementation

[0017] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0018] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," "outer," "far," "near," "front," and "rear," etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings and are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0019] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0020] Please see Figure 1 As shown, an embodiment of this application provides an intelligent collaborative management edge computing IoT device system. This intelligent collaborative management edge computing IoT device system includes: The execution strategy acquisition module is used to collect the local task execution strategies of all edge computing IoT devices. The process attribute determination module is used to extract expected process attribute information from the local task execution strategy; The process identification module is used to identify processes that cannot be processed locally and their time limits based on expected process attribute information and historical work records of edge computing IoT devices. The transfer verification module is used to initiate a process receiving query to the Internet of Things (IoT) and perform process transfer feasibility verification on other edge computing IoT devices that respond to the query. The transfer operation module is used to perform process transfer operations that cannot be processed locally based on the time limit information. The link control module is used to select backup communication links based on the routing status within the Internet of Things (IoT) and to adjust the connection status of backup communication links based on the processing status of processes that cannot be handled locally during the transfer process.

[0021] This intelligent collaborative management edge computing IoT device system collects task execution strategies from all edge computing IoT devices, identifies and transfers processes that cannot be processed locally, and achieves collaborative management of different edge computing IoT devices to ensure the normal operation of the entire IoT network.

[0022] In another embodiment, the execution policy acquisition module is used to collect the local task execution policies of all edge computing IoT devices, including: Based on the access nodes of all edge computing IoT devices in the Internet of Things, clustered monitoring is implemented on all edge computing IoT devices; where clustered monitoring refers to time-division monitoring of some edge computing IoT devices whose network distance from the access node meets the preset distance condition; Based on the device identity, the operation records of all edge computing IoT devices are extracted from the clustered monitoring logs; the operation records are filtered to obtain the local task execution strategy of the edge computing IoT devices; the local task execution strategy includes process segmentation information and process content information of local tasks; The process attribute determination module is used to extract expected process attribute information from the local task execution strategy, including: Based on process segmentation information and process content information, determine the expected attribute information of each process under the local task execution strategy; among which, the expected attribute information includes the expected resource consumption and expected processing load of the process locally.

[0023] The Internet of Things (IoT) comprises multiple edge computing IoT devices. Each edge computing IoT device connects to the IoT and interfaces with a corresponding user terminal. During the interaction with the user terminal, the edge computing IoT device performs local task processing. This local task processing refers to the edge computing IoT device receiving data from the user terminal, generating computing tasks locally, and completing these tasks using its own resources. During this local task processing, the edge computing IoT device simultaneously generates a running log. Considering the large number of edge computing IoT devices within the IoT, independently monitoring each device would not only consume significant resources but also reduce the efficiency and real-time performance of the running log monitoring.

[0024] To quickly monitor the operational logs of all edge computing IoT devices within an IoT network, all edge computing IoT devices are divided into several clusters based on their access nodes in the IoT ecosystem. Each cluster contains several edge computing IoT devices, and the network distance between the access nodes of any two devices within the same cluster is less than a preset distance threshold. By clustering all edge computing IoT devices and implementing clustered monitoring (i.e., time-sharing monitoring of all edge computing IoT devices within each cluster), the workload of monitoring all edge computing IoT devices within the IoT ecosystem can be reduced, while ensuring monitoring efficiency and accuracy. For the clustered monitoring logs obtained from each cluster, information is extracted using the identity information of the edge computing IoT devices as a reference to obtain the operational logs of each edge computing IoT device. The operational logs are then filtered to obtain the process segmentation information and process content information of each edge computing IoT device's local task. The process segmentation information refers to all processes formed by the segmentation of the local task and their order; the process content information refers to the specific data calculation and processing content of each segmented process.

[0025] It is understandable that the aforementioned local task execution strategy comprehensively characterizes all processes during the local task execution of edge computing IoT devices. Different processes within the main task need to process different amounts and types of data, leading to varying processing results on the edge computing IoT device and their consequential impact. In practice, if the resources required or the load generated by one of the local task processes exceed the resource capacity or load tolerance of the corresponding edge computing IoT device, the edge computing IoT device will be unable to process the aforementioned process accurately and normally locally. Therefore, based on process segmentation information and process content information, the expected resource consumption and expected processing load of each process under the local task execution strategy are determined locally, providing a reliable basis for judging the compatibility of each process under the local task with the edge computing IoT device in terms of terms and load.

[0026] In another embodiment, the process identification module is used to identify processes that cannot be processed locally and their time limits based on expected process attribute information and historical work records of edge computing IoT devices, including: By comparing the expected resource consumption of the process's expected attribute information with the historical resource provision records of the edge computing IoT devices, it can be determined whether the edge computing IoT devices have experienced a resource shortage event. By comparing the expected processing load of the expected process attribute information with the historical downtime records of the edge computing IoT devices, it can be determined whether a failure event has occurred in the edge computing IoT devices. When a resource shortage event or failure event occurs, the corresponding process is identified as a locally unprocessable process, and the deadline information of the locally unprocessable process during the execution of its task is obtained; the deadline information refers to the latest completion time information of the locally unprocessable process.

[0027] As described above, the resources and workloads required by each process under a local task on an edge computing IoT device vary. Some processes exceed the resource capacity and load tolerance of the current edge computing IoT device during local processing, causing them to fail to process normally locally and thus affecting the complete and correct processing of the local task. To accurately identify processes under a local task that cannot be processed locally, the expected resource usage of the process's expected attribute information is compared with the historical resource provision records of the edge computing IoT device. If the amount of resources that the edge computing IoT device could provide during the historical period was less than the expected resource usage, a resource shortage event is determined to have occurred; otherwise, no resource shortage event is determined. Furthermore, the expected processing load of the process's expected attribute information is compared with the historical downtime records of the edge computing IoT device. If the workload corresponding to a downtime of the edge computing IoT device during the historical period was less than the expected processing load, a failure event is determined to have occurred; otherwise, no failure event is determined. When a resource shortage event or failure event is determined, the corresponding process is identified as a process that cannot be processed locally.

[0028] Furthermore, the complete processing of local tasks relies on the completion of all processes. Each process (including those unable to process locally) has a set latest completion time to cooperate with the local task. Understandably, if a process unable to process locally fails to complete its task before its corresponding latest completion time, the normal and complete processing of the local task cannot be guaranteed. By obtaining the time limit information of processes unable to process locally during the execution of their respective tasks, a reliable basis is provided for subsequently selecting edge computing IoT devices capable of transferring and receiving these unprocessable local processes.

[0029] In another embodiment, the transfer verification module is used to initiate a process receiving query to the Internet of Things (IoT) and perform process transfer feasibility verification on other edge computing IoT devices that respond to the query, including: Based on the attribute tags of processes that cannot be processed locally, a process reception query is initiated to the Internet of Things; the attribute tags include the type tag and data volume tag of the processes that cannot be processed locally. For other edge computing IoT devices responding to inquiries, perform program configuration verification on type labels and computing power configuration verification on data volume labels to identify several edge computing IoT devices that have passed the process transfer feasibility verification. The transfer operation module is used to perform process transfer operations that cannot be processed locally based on the time limit information, including: Based on the time limit information, a second query is performed on several other edge computing IoT devices that have passed the process transfer feasibility verification, so as to package and transfer the processes that cannot be processed locally to one of the edge computing IoT devices that have passed the process transfer feasibility verification.

[0030] To select matching edge computing IoT devices that cannot handle processes locally within the Internet of Things (IoT), a process acceptance query is broadcast to the IoT network based on the type and data volume tags of the unprocessed process. When other edge computing IoT devices connected to the IoT network receive the query, they determine whether to respond based on their own operational status; for example, if the overall workload of other edge computing IoT devices is less than a preset load threshold, they will respond to the query. Then, the program configuration verification for the type tag and the computing power configuration verification for the data volume tag are performed on the other edge computing IoT devices that respond to the query. That is, whether the program provided by the other edge computing IoT device matches the type of the unprocessed process locally, and whether the computing power provided matches the data volume of the unprocessed process locally. If both the program configuration verification and the computing power configuration verification pass, the corresponding edge computing IoT device is determined to have passed the process transfer feasibility verification.

[0031] Furthermore, based on the aforementioned timeframe information, a second query is performed on several other edge computing IoT devices that have passed the process transfer feasibility verification. This process packages and transfers processes that cannot be processed locally to one of the edge computing IoT devices that has passed the process transfer feasibility verification. This "one edge computing IoT device that has passed the process transfer feasibility verification" refers to the edge computing IoT device that can process the aforementioned processes that cannot be processed locally the fastest using its own resources. Through this process, the transfer of processes that cannot be processed locally is accurately achieved, ensuring correct and efficient process handling.

[0032] In another embodiment, the link control module is used to select a backup communication link based on the routing status within the Internet of Things (IoT); and to adjust the connection status of the backup communication link based on the processing status of processes that cannot be processed locally during the transfer process, including: Extract the time-domain distribution data of routing occupancy within the IoT from the routing operation records of the IoT; select backup communication links based on the time-domain distribution data of routing occupancy; where backup communication links refer to communication links within the IoT whose maximum continuous idle time exceeds a preset time threshold; Based on the correct processing results of the locally unprocessable process during the transfer, a real-time situation is generated to determine whether the locally unprocessable process has completed processing. If so, the backup communication link is instructed to connect with the edge computing IoT device where the locally unprocessable process is currently located. If not, the backup communication link is not instructed to perform the connection operation.

[0033] To ensure the rapid and secure return of processing results for processes that cannot be processed locally after migration to their original edge computing IoT devices, several backup communication links with good and stable communication performance need to be selected within the IoT. Specifically, routing occupancy time-domain distribution data within the IoT is extracted from the IoT's routing operation records. Communication links with a maximum continuous idle time exceeding a preset threshold are selected as backup links. Real-time data is then generated based on the correct processing results of processes that cannot be processed locally during the migration period to determine whether the processes have completed processing. The connection status between the backup communication links and the edge computing IoT devices currently hosting the processes that cannot be processed locally is adjusted accordingly. This ensures rapid feedback of process processing results to the original edge computing IoT devices, guarantees the overall completion progress of tasks belonging to processes that cannot be processed locally, enables collaborative management of different edge computing IoT devices, and ensures the normal operation of the entire IoT ecosystem.

[0034] Please see Figure 2 As shown, an embodiment of this application provides a method for intelligent collaborative management of edge computing IoT devices. This method includes: Step S1: Collect the local task execution strategies of all edge computing IoT devices and extract the expected process attribute information from the local task execution strategies; Step S2: Based on the expected attribute information of the process and the historical working records of the edge computing IoT device, identify the processes that cannot be processed locally and their time limits; Step S3: Initiate a process reception query to the Internet of Things (IoT), and perform process transfer feasibility verification on other edge computing IoT devices that respond to the query; based on the time limit information, perform process transfer operations that cannot be processed locally. Step S4: Select a backup communication link based on the routing status within the IoT; adjust the connection status of the backup communication link based on the actual processing status of processes that cannot be processed locally during the transfer.

[0035] This intelligent collaborative management method for edge computing IoT devices achieves collaborative management of different edge computing IoT devices by collecting task execution strategies for all edge computing IoT devices, identifying and transferring processes that cannot be processed locally, thus ensuring the normal operation of the entire IoT ecosystem.

[0036] In another embodiment, in step S1, the local task execution strategies of all edge computing IoT devices are collected, and process expectation attribute information is extracted from the local task execution strategies, including: Based on the access nodes of all edge computing IoT devices in the Internet of Things, clustered monitoring is implemented on all edge computing IoT devices; where clustered monitoring refers to time-division monitoring of some edge computing IoT devices whose network distance from the access node meets the preset distance condition; Based on the device identity, the operation records of all edge computing IoT devices are extracted from the clustered monitoring logs; the operation records are filtered to obtain the local task execution strategy of the edge computing IoT devices; the local task execution strategy includes process segmentation information and process content information of local tasks; Based on process segmentation information and process content information, determine the expected attribute information of each process under the local task execution strategy; among which, the expected attribute information includes the expected resource consumption and expected processing load of the process locally.

[0037] In another embodiment, in step S2, based on the expected attribute information of the process and the historical working records of the edge computing IoT device, the process that cannot be processed locally and its time limit information are identified, including: By comparing the expected resource consumption of the process's expected attribute information with the historical resource provision records of the edge computing IoT devices, it can be determined whether the edge computing IoT devices have experienced a resource shortage event. By comparing the expected processing load of the expected process attribute information with the historical downtime records of the edge computing IoT devices, it can be determined whether a failure event has occurred in the edge computing IoT devices. When a resource shortage event or failure event occurs, the corresponding process is identified as a locally unprocessable process, and the deadline information of the locally unprocessable process during the execution of its task is obtained; the deadline information refers to the latest completion time information of the locally unprocessable process.

[0038] In another embodiment, in step S3, a process reception query is initiated to the Internet of Things (IoT), and process transfer feasibility verification is performed on other edge computing IoT devices that respond to the query; based on the time limit information, a process transfer operation that cannot be processed locally is performed, including: Based on the attribute tags of processes that cannot be processed locally, a process reception query is initiated to the Internet of Things; the attribute tags include the type tag and data volume tag of the processes that cannot be processed locally. For other edge computing IoT devices responding to inquiries, perform program configuration verification on type labels and computing power configuration verification on data volume labels to identify several edge computing IoT devices that have passed the process transfer feasibility verification. Based on the time limit information, a second query is performed on several other edge computing IoT devices that have passed the process transfer feasibility verification, so as to package and transfer the processes that cannot be processed locally to one of the edge computing IoT devices that have passed the process transfer feasibility verification.

[0039] In another embodiment, in step S4, a backup communication link is selected based on the routing status within the Internet of Things; the connection status of the backup communication link is adjusted based on the processing status of processes that cannot be processed locally during the transfer, including: Extract the time-domain distribution data of routing occupancy within the IoT from the routing operation records of the IoT; select backup communication links based on the time-domain distribution data of routing occupancy; where backup communication links refer to communication links within the IoT whose maximum continuous idle time exceeds a preset time threshold; Based on the correct processing results of the locally unprocessable process during the transfer, a real-time situation is generated to determine whether the locally unprocessable process has completed processing. If so, the backup communication link is instructed to connect with the edge computing IoT device where the locally unprocessable process is currently located. If not, the backup communication link is not instructed to perform the connection operation.

[0040] The intelligent collaborative management edge computing IoT device method of the present invention corresponds to and has the same operation and effect as the aforementioned intelligent collaborative management edge computing IoT device system, and will not be described again here.

[0041] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. This disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims. Thus, if these modifications and variations of the invention fall within the scope of the claims of the invention and their equivalents, the invention is also intended to include these modifications and variations.

Claims

1. An intelligent collaborative management edge computing Internet of Things device system, characterized in that, The system comprises: an execution strategy acquisition module configured to collect local task execution strategies of all edge computing IoT devices; a process attribute determination module configured to extract process expected attribute information from the local task execution strategies; a process identification module configured to identify local unhandled processes and their deadline information according to the process expected attribute information and historical work records of the edge computing IoT devices; a transfer verification module configured to send an inquiry to an IoT initiating process and perform process transfer feasibility verification on other edge computing IoT devices responding to the inquiry; a transfer operation module configured to perform local unhandled process transfer operations according to the deadline information; a link control module configured to select a backup communication link according to routing states within the IoT and adjust the docking state of the backup communication link according to the processing status of the local unhandled process during the transfer.

2. The intelligent collaborative management edge computing IoT device system of claim 1, wherein: the execution strategy acquisition module is configured to collect local task execution strategies of all edge computing IoT devices, including: performing clusterized monitoring on all edge computing IoT devices at an access node of the IoT, wherein the clusterized monitoring refers to performing time-sharing monitoring on part of the edge computing IoT devices whose network distance from the access node meets a preset distance condition; extracting running records of all edge computing IoT devices from the clusterized monitoring logs according to device identities; and performing content screening on the running records to obtain local task execution strategies of the edge computing IoT devices, wherein the local task execution strategies include process segmentation information and process content information of local tasks. the process attribute determination module is configured to extract process expected attribute information from the local task execution strategies, including: determining expected attribute information of all processes under the local task execution strategies according to the process segmentation information and the process content information, wherein the expected attribute information includes expected resource occupation and expected processing load of the processes at the local.

3. The intelligent collaborative management edge computing IoT device system of claim 1, wherein: the process identification module is configured to identify local unhandled processes and their deadline information according to the process expected attribute information and historical work records of the edge computing IoT devices, including: comparing expected resource occupation of the process expected attribute information with historical resource provision records of the edge computing IoT devices to determine whether a resource shortage event occurs in the edge computing IoT devices; comparing expected processing load of the process expected attribute information with historical downtime occurrence records of the edge computing IoT devices to determine whether a failure event occurs in the edge computing IoT devices; when a resource shortage event or a failure event occurs, determining a corresponding process as a local unhandled process and obtaining deadline information of the local unhandled process during execution of a task in which the local unhandled process is located, wherein the deadline information refers to the latest completion time information of the local unhandled process. 4.The intelligent collaborative management edge computing IoT device system of claim 1, wherein: the transfer verification module is configured to receive a query from the IoT initiating process, and perform a process transfer feasibility verification on other edge computing IoT devices responding to the query, including: receiving a query from the IoT initiating process according to an attribute tag of the local unhandled process, wherein the attribute tag includes a type tag and a data volume tag of the local unhandled process; performing a program configuration verification on the type tag and a computing power configuration verification on the data volume tag on other edge computing IoT devices responding to the query, to determine a plurality of edge computing IoT devices passing the process transfer feasibility verification; and the transfer operation module is configured to perform a local unhandled process transfer operation according to the deadline information, including: performing a secondary query on the plurality of other edge computing IoT devices passing the process transfer feasibility verification according to the deadline information, to pack and transfer the local unhandled process to one of the edge computing IoT devices passing the process transfer feasibility verification. 5.The intelligent collaborative management edge computing IoT device system of claim 1, wherein: the link control module is configured to select a backup communication link according to a routing state inside the IoT, and adjust a docking state of the backup communication link according to a processing live of the local unhandled process during the transfer, including: extracting routing occupation time domain distribution data inside the IoT from a routing operation record of the IoT; selecting a backup communication link according to the routing occupation time domain distribution data, wherein the backup communication link refers to a communication link with a maximum continuous idle time longer than a preset time threshold; and generating a live of a correct processing result of the local unhandled process during the transfer, to determine whether the local unhandled process is completed; if yes, instructing the backup communication link to dock with the edge computing IoT device currently hosting the local unhandled process; and if not, not instructing the backup communication link to perform a docking operation. including: step S1: collecting local task execution strategies of all edge computing IoT devices, and extracting process expected attribute information from the local task execution strategies; step S2: identifying a local unhandled process and deadline information thereof according to the process expected attribute information and a historical work record of the edge computing IoT device; step S3: receiving a query from the IoT initiating process, and performing a process transfer feasibility verification on other edge computing IoT devices responding to the query; and performing a local unhandled process transfer operation according to the deadline information; and step S4: selecting a backup communication link according to a routing state inside the IoT, and adjusting a docking state of the backup communication link according to a processing live of the local unhandled process during the transfer. 7.The intelligent collaborative management edge computing IoT device method of claim 6, wherein: ​ ​ ​ ​ ​ ​ ​ ​ 6. The method for intelligent collaborative management of edge computing Internet of Things equipment, characterized in that, ​ ​ ​ ​ ​ ​ In step S1, the local task execution strategy of each edge computing IoT device is collected, and the process expected attribute information is extracted from the local task execution strategy, including: According to the access nodes of all edge computing IoT devices in the Internet of Things, cluster monitoring is implemented on all edge computing IoT devices; wherein the cluster monitoring refers to time-sharing monitoring on part of the edge computing IoT devices whose network distance to the access node meets the preset distance condition; According to the device identity, the running record of each edge computing IoT device is extracted from the cluster monitoring log; the running record is content-filtered to obtain the local task execution strategy of the edge computing IoT device; wherein the local task execution strategy includes process segmentation information and process content information of the local task; According to the process segmentation information and the process content information, the expected attribute information of each process under the local task execution strategy is determined; wherein the expected attribute information includes the expected resource occupation and the expected processing load of the process locally.

8. The intelligent collaborative management edge computing IoT device method of claim 6, wherein: In step S2, according to the process expected attribute information and the historical working record of the edge computing IoT device, the local unhandled process and its deadline information are identified, including: Comparing the expected resource occupation of the process expected attribute information with the historical resource provision record of the edge computing IoT device, it is judged whether a resource shortage event occurs in the edge computing IoT device; Comparing the expected processing load of the process expected attribute information with the historical downtime occurrence record of the edge computing IoT device, it is judged whether a failure event occurs in the edge computing IoT device; When a resource shortage event or a failure event occurs, the corresponding process is determined as a local unhandled process, and the deadline information of the local unhandled process during the execution of the task is obtained; wherein the deadline information refers to the latest completion time information of the local unhandled process.

9. The intelligent collaborative management edge computing IoT device method of claim 6, wherein: In step S3, a process receiving inquiry is initiated to the Internet of Things, and process transfer feasibility verification is implemented on other edge computing IoT devices responding to the inquiry; according to the deadline information, a local unhandled process transfer operation is performed, including: According to the attribute tag of the local unhandled process, a process receiving inquiry is initiated to the Internet of Things; wherein the attribute tag includes a type tag and a data volume tag of the local unhandled process; The program configuration verification on the type tag and the computing power configuration verification on the data volume tag are performed on other edge computing IoT devices responding to the inquiry, so as to determine a plurality of edge computing IoT devices that pass the process transfer feasibility verification; According to the deadline information, a secondary inquiry is made on a plurality of other edge computing IoT devices that pass the process transfer feasibility verification, so as to pack and transfer the unhandled process to one of the edge computing IoT devices that pass the process transfer feasibility verification. 10.The intelligent collaborative management edge computing IoT device method of claim 6, wherein: in step S4, a backup communication link is selected according to a routing state inside the IoT; according to a processing live of the local unhandled process during the transfer, an interfacing state of the backup communication link is adjusted, including: extracting routing occupation time domain distribution data inside the IoT from a routing operation record of the IoT; selecting a backup communication link according to the routing occupation time domain distribution data, wherein the backup communication link refers to a communication link with a maximum continuous idle time greater than a preset time threshold; generating a live according to a correct processing result of the local unhandled process during the transfer, judging whether the local unhandled process is completed; if yes, instructing the backup communication link to interface with an edge computing IoT device currently located by the local unhandled process; if not, not instructing the backup communication link to perform an interfacing operation.

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