CN-121984991-A - Method, device, equipment and system for accessing and scheduling equipment of Internet of things platform

CN121984991ACN 121984991 ACN121984991 ACN 121984991ACN-121984991-A

Abstract

The application discloses a device access and scheduling method, a device and a system of an internet of things platform, and relates to the technical field of big data internet of things, wherein the method comprises the steps of obtaining a device trust score of each access device through a credit node, obtaining access configuration corresponding to the device trust score, and completing access operation of all access devices based on the access configuration; determining a transmission configuration according to the data type of a data task transmitted by the access equipment through the credit node, and transmitting the data task to a processing node cluster of a processing layer based on the transmission configuration; and determining a selection coefficient of each processing node in the processing node cluster, and distributing the data task to the corresponding processing node based on the selection coefficient. By the mode, the closed loop with high concurrency, transmissibility, load balancing and self-healing of faults is integrally realized, and the stability and the resource utilization rate of the platform are obviously enhanced.

Inventors

YIN DESHUAI
YAN YONGCHAO
HUANG TAO
YIN FEI

Assignees

青岛海尔科技有限公司
海尔优家智能科技（北京）有限公司
青岛海尔智能家电科技有限公司

Dates

Publication Date: 20260505
Application Date: 20251229

Claims (10)

1. The device access and scheduling method of the internet of things platform is characterized by comprising the following steps: acquiring the equipment trust score of each access equipment through a credit node, and the access configuration corresponding to the equipment trust score, and completing the access operation of all the access equipment based on the access configuration; determining a transmission configuration according to the data type of a data task transmitted by the access equipment through the credit node, and transmitting the data task to a processing node cluster of a processing layer based on the transmission configuration; and determining a selection coefficient of each processing node in the processing node cluster, and distributing the data task to the corresponding processing node based on the selection coefficient so that each processing node executes the distributed data task.
2. The method of claim 1, wherein the obtaining, by the credit node, a device trust score for each access device and obtaining an access configuration corresponding to the device trust score, comprises: For each access device, historical behavior data of the access device is obtained through the credit node, and quantitative scoring is carried out on the historical behavior data based on a semantic tag library, so that a semantic tag library score is obtained; Acquiring communication performance parameters of the access equipment, and determining a communication capacity score of the access equipment based on the communication performance parameters; Determining a device trust score for the access device according to the communication capability score and the semantic tag library score; and acquiring a preset access configuration rule, and determining a corresponding access configuration based on the equipment trust score and the access configuration rule.
3. The method of claim 2, wherein quantitatively scoring the historical behavior data based on the semantic tag library to obtain a semantic tag library score, comprising: Determining a plurality of behavior evaluation parameters of the access equipment according to the historical behavior data, wherein the behavior evaluation parameters comprise data transmission accuracy, task completion time rate and rule compliance; based on the semantic tag library, the quantized score corresponding to each behavior evaluation parameter and the corresponding weight coefficient are obtained; and carrying out weighted summation based on the plurality of quantized scores and the weight coefficient corresponding to each quantized score to obtain a semantic tag library score.
4. The method of claim 2, wherein the access configuration comprises a target access channel and bandwidth parameters, wherein the determining the corresponding access configuration based on the device trust score and the access configuration rule comprises: Adjusting an access threshold value in the access configuration rule according to the equipment trust score, wherein the access threshold value is used for determining the trust type of the access equipment, and the access configuration rule is used for indicating an access channel and corresponding bandwidth parameters of the access equipment under different trust types; and determining a target access channel and corresponding bandwidth parameters of the access equipment based on the equipment trust score and the adjusted access configuration rule.
5. The method of claim 1, wherein the determining a selection coefficient for each processing node in the cluster of processing nodes and assigning the data task to the corresponding processing node based on the selection coefficient comprises: acquiring the current load rate of each processing node and the task priority of the data task; Calculating a selection coefficient of a corresponding processing node based on the task priority and each current load rate; and distributing the data task to a processing node corresponding to the selection coefficient with the highest value.
6. The method of claim 5, wherein after the transmitting the data task to the processing node cluster of the processing layer based on the transmission configuration, the method further comprises: acquiring health indexes and corresponding historical health data of each processing node in the processing node cluster; when the health index exceeds a corresponding index threshold, marking a processing node corresponding to the health index as a first abnormal processing node; Inputting each historical health data into a pre-trained time sequence fault pre-judging model to obtain the risk rate of faults of the corresponding processing nodes; Marking the processing node with the risk rate higher than the risk rate threshold as a second abnormal processing node; and performing migration operation on the data tasks of the first exception handling node and the second exception handling node.
7. The method of claim 6, wherein the method further comprises: acquiring the equipment access quantity and the data throughput of the processing node cluster, and executing elastic capacity expansion or capacity contraction on the processing node cluster through a Kubernetes containerized interface; Constructing a three-level disaster recovery architecture inside the processing node cluster, wherein the three-level disaster recovery architecture comprises a main processing node, a slave processing node and a standby processing node, wherein the main processing node and the corresponding slave processing node continuously synchronize data in real time, and the standby processing node continuously monitors the health states of the corresponding main processing node and slave processing node; when detecting that an abnormal main processing node exists, triggering a corresponding slave processing node to take over the data task of the abnormal main processing node, and upgrading the corresponding slave processing node into a new main processing node; upgrading the corresponding standby processing node to a new slave processing node, and supplementing the new standby processing node from the processing node cluster; and executing a cleaning operation on the abnormal main processing node.
8. The device access and scheduling device of the Internet of things platform is characterized by comprising an access module, a transmission module and a processing module, wherein: The access module is used for obtaining the equipment trust score of each access equipment through the credit node, and the access configuration corresponding to the equipment trust score, and completing the access operation of all the access equipment based on the access configuration; the transmission module is used for determining transmission configuration according to the data type of the data task transmitted by the access equipment through the credit node and transmitting the data task to a processing node cluster of a processing layer based on the transmission configuration; the processing module is configured to determine a selection coefficient of each processing node in the processing node cluster, and allocate the data task to a corresponding processing node based on the selection coefficient, so that each processing node executes the allocated data task.
9. An electronic device comprising a processor and a memory communicatively coupled to the processor; the memory stores computer-executable instructions; the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1 to 7.
10. The platform system of the Internet of things is characterized by comprising an access layer, a transmission layer and a processing layer, wherein: the access layer comprises a credit node, wherein the credit node is used for carrying out dynamic authentication and credit evaluation on the access equipment, generating equipment trust scores, and controlling the access equipment to complete access based on access configuration corresponding to the equipment trust scores; the transmission layer comprises the credit node and is used for receiving a data task from the access equipment, determining transmission configuration according to the data type of the data task, and then sending the data task to the processing layer according to the transmission configuration; The processing layer comprises a processing node cluster and is used for receiving data tasks from the transmission layer, calculating the selection coefficient of each processing node in the processing node cluster and distributing the data tasks to the corresponding processing nodes for processing according to the selection coefficient.

Description

Method, device, equipment and system for accessing and scheduling equipment of Internet of things platform Technical Field The application relates to the technical field of big data Internet of things, in particular to a method, a device, equipment and a system for accessing and scheduling equipment of an Internet of things platform. Background With the rapid popularization of internet of things (IoT) technology, the device access scale in the fields of industrial manufacturing, intelligent transportation, smart home, smart agriculture, etc. has shown an exponential growth. Taking the industrial internet of things as an example, a large-scale factory may deploy hundreds of thousands of sensors, actuators and intelligent terminal devices, which interact with a platform through various communication protocols (such as MQTT, coAP, loRaWAN, etc.), and transmit monitoring data, control instructions and status information in real time. The internet of things platform is used as a core hub, and complex tasks such as equipment access authentication, data transmission, service logic processing, resource scheduling and the like are required to be processed simultaneously. However, high concurrent access of mass devices, differentiated transmission requirements of heterogeneous data, network interference in a dynamic environment and sudden traffic load fluctuation have extremely high requirements on the stability of a platform. However, the existing scheme is rigidified in four layers of equipment access, transmission, processing and resource scheduling, namely, the centralized access layer is easy to be subjected to single-point failure, the transmission layer protocol and topology fixed key data packet loss is high, the processing nodes of the processing layer are not busy and idle, and the fault can only be remedied afterwards. Therefore, a device access and scheduling method covering a stable and reliable internet of things platform is needed. Disclosure of Invention The application provides a device access and scheduling method, device and system of an Internet of things platform, which are used for solving the problems that in the conventional scheme, four layers of device access, transmission, processing and resource scheduling are all rigidified, an access layer is centralized and is easy to be subjected to single-point failure, a transmission layer protocol and topology fixed key data packet loss is high, and processing nodes of a processing layer are not uniform in busy and idle and faults can only be remedied afterwards. Therefore, a stable and reliable method for accessing and scheduling devices of the internet of things platform is needed. In a first aspect, the present application provides a method for accessing and scheduling devices of an internet of things platform, including: acquiring the equipment trust score of each access equipment through a credit node, and the access configuration corresponding to the equipment trust score, and completing the access operation of all the access equipment based on the access configuration; determining a transmission configuration according to the data type of a data task transmitted by the access equipment through the credit node, and transmitting the data task to a processing node cluster of a processing layer based on the transmission configuration; and determining a selection coefficient of each processing node in the processing node cluster, and distributing the data task to the corresponding processing node based on the selection coefficient so that each processing node executes the distributed data task. In a possible implementation manner, the obtaining, by a credit node, a device trust score of each access device, and obtaining an access configuration corresponding to the device trust score, includes: For each access device, historical behavior data of the access device is obtained through the credit node, and quantitative scoring is carried out on the historical behavior data based on a semantic tag library, so that a semantic tag library score is obtained; Acquiring communication performance parameters of the access equipment, and determining a communication capacity score of the access equipment based on the communication performance parameters; Determining a device trust score for the access device according to the communication capability score and the semantic tag library score; and acquiring a preset access configuration rule, and determining a corresponding access configuration based on the equipment trust score and the access configuration rule. In a possible implementation manner, the quantitatively scoring the historical behavior data based on the semantic tag library to obtain a semantic tag library score includes: Determining a plurality of behavior evaluation parameters of the access equipment according to the historical behavior data, wherein the behavior evaluation parameters comprise data transmission accuracy, task completion time rate a