End equipment efficient enabling method for edge-end scene

Abstract

The invention discloses an edge-end scene-oriented end equipment efficient enabling method, and relates to the technical field of software design and development, centralized management and control of heterogeneous equipment are realized through cloud, edge and end cooperative work, the method comprises the following steps: a cloud side constructs a unified metadata management system by using a Kubernetes technology, and provides equipment discovery, registration, management and monitoring functions; the side is responsible for access, standardized processing and analysis of equipment data, and synchronizes equipment state information to the cloud; the end side supports a plurality of Internet of Things protocols through the equipment service module and carries out data acquisition and preprocessing; according to the method, the advantages of cloud computing, edge computing and end equipment are effectively integrated, and the real-time performance and reliability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of software design and development, and in particular to a method for efficiently enabling terminal devices for edge scenarios. Background Art

[0002] In modern tactical edge combat environments, the diversity of heterogeneous terminal devices is becoming increasingly prominent, such as radars, infrared sensors, launchers and other sensors, each with its own unique hardware model and communication protocol. This complexity makes coordination and management between devices a key issue.

[0003] The traditional cloud computing model relies on centralized data processing and storage, which to a certain extent meets the needs of device management and data processing. However, with the increase in the number of devices and the rapid expansion of data volume, the cloud computing model faces problems such as insufficient network bandwidth, high latency, and high data transmission costs. These problems seriously affect the real-time performance and reliability of the system.

[0004] As an emerging computing model, edge computing aims to move data processing and storage from the cloud to edge nodes close to the data source, thereby reducing data transmission latency and bandwidth requirements and improving the system's real-time response capabilities and reliability. Edge computing can pre-process and analyze local data, provide fast feedback and decision support, and reduce dependence on cloud resources.

[0005] In the edge computing mode, how to efficiently conduct edge communication and device management is a key issue. Existing edge communication solutions often have problems such as inconsistent communication protocols, non-standard data formats, and complex device management. These problems lead to difficulties in system integration, high maintenance costs, and poor scalability. Summary of the invention

[0006] The purpose of the present invention is to design an efficient enabling technology for terminal devices based on edge scenarios in combination with cloud-edge collaborative technology.

[0007] The technical solution of the present invention is to provide an efficient enabling method for terminal devices in edge scenarios, the method comprising:

[0008] Build a device management model to achieve centralized management and control of heterogeneous devices. The built device management model includes cloud, edge, device, and multiple end devices, as follows:

[0009] The cloud side builds a unified metadata management system based on Kubernetes technology to define device resources and provide device discovery, registration, management, and monitoring functions. The cloud side monitors the addition, deletion, modification, and query information of device-related resources on the cloud side through the cloud controller, and sends this information from the cloud side. At the same time, the cloud controller is also responsible for receiving device-related events reported to the cloud side and performing corresponding processing;

[0010] The edge cloud based on Kubernetes is deployed on the edge side. The edge cloud is responsible for accessing, standardizing, processing, and analyzing device data. The edge cloud synchronizes the real-time status information of the end device to the cloud side through the edge controller. The edge controller can also receive update instructions issued by the cloud side and forward them downward.

[0011] The end side uses the device service module to achieve the conversion of different IoT protocols and standardization of data formats, and manages various end devices through the end controller. The management content includes establishing a mapping relationship between the end devices and the device resources defined on the cloud side.

[0012] Various end devices are connected to the end side through corresponding IoT protocols;

[0013] The process of cloud, edge, and end working together is as follows:

[0014] S1. Device registration and management: The end device registers with the edge node through the device service module. The edge node synchronizes the device information to the cloud side to complete the device registration and management.

[0015] S2. Data collection and processing: The end side collects data from the end device through the device service module, pre-processes the data through the device service module, and transmits the data to the edge side after processing. The edge side further processes and analyzes the data, and uploads the data to the cloud side for processing when necessary;

[0016] S3, Data storage and analysis: The cloud-side system receives the data uploaded by the edge nodes, extracts useful key information for storage and analysis, and generates control instructions to be issued based on the analysis results;

[0017] S4. Send control instructions: The cloud-side system will generate control instructions and send them to the end device. The end device will perform the corresponding operations and feedback the execution results.

[0018] S5, state synchronization and feedback: The edge node synchronizes the device status and control instructions between the cloud side and the end device through the edge controller to ensure the consistency and real-time performance of the system.

[0019] In any of the above technical solutions, further, the method also includes: building an edge communication framework to realize information interaction and data processing between end devices, and according to different protocols, the end devices are divided into terminal devices that are connected through the MQTT protocol and terminal devices that are connected through HTTP; for terminal devices that are connected through the MQTT protocol, develop corresponding adapters, and the adapter is responsible for converting the data of devices that support different protocols into the format supported by the MQTT protocol, and the data is transmitted through the MQTT Broker as an intermediate channel; for terminal devices that are connected through HTTP, the adapter is responsible for converting the data of devices that support different protocols into the format supported by HTTP.

[0020] In any of the above technical solutions, further, the cloud side adopts etcd as the database persistence solution; the edge side adopts SQLite as the database persistence solution; and the terminal side adopts MongoDB as the database persistence solution.

[0021] In any of the above technical solutions, further, the device resources defined on the cloud side include Device Model and Device:

[0022] Device Model: defines the standard properties of a device, including device metadata, requirements for various metadata, device specifications, and requirements for various device specifications. The Device Model defines the basic features and functional parameters of a device, providing a reference for device instantiation.

[0023] Device: defines a device instance. The definition includes the specific values ​​of each metadata of the device instance and the specific values ​​of each device specification. The device instance is a process of concretizing and instantiating the device model according to the specific conditions of the actual device.

[0024] In any of the above technical solutions, further, the edge controller operates autonomously when the edge side and the cloud side are offline, records changes in the status of the terminal device, and synchronizes the status information of the terminal device to the cloud side after confirming that the network connection with the cloud side is re-established.

[0025] In any of the above technical solutions, the device service module on the end side further supports multiple IoT protocols including Modbus, MQTT, BLE, BACnet and multiple data transmission protocols including HTTP, MQTT, CoAP. The device service module collects data from the end device and performs preliminary processing of data filtering, data aggregation and format conversion; the preprocessed data is transmitted to the edge node or cloud side through the network.

[0026] The beneficial effects of the present invention are:

[0027] The present invention introduces an edge communication framework to achieve unified management and empowerment of heterogeneous devices on the edge, simplify the device management process, and improve equipment utilization. Through unified management, device resources are dynamically allocated according to task requirements, resource allocation is optimized, and work efficiency is improved. By collecting and analyzing device data, intelligent decision-making can be supported to improve business efficiency and effectiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The advantages of the above and additional aspects of the present invention will become apparent and easily understood in the description of the embodiments in conjunction with the following drawings, in which:

[0029] Figure 1 is a schematic diagram of a device management model according to an efficient enabling method for edge devices in edge scenarios according to an embodiment of the present invention;

[0030] Figure 2 It is a schematic diagram of the edge-end communication framework of an efficient enabling method for edge-end devices for edge-end scenarios according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0032] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0033] This embodiment provides an efficient empowerment method for edge devices for edge scenarios. The method includes two parts: device management model construction and edge communication framework construction. It aims to achieve centralized management and control of various heterogeneous devices through a standardized device management framework and optimized edge communication technology.

[0034] like Figure 1 As shown in the figure, we first build a standardized device management model including cloud, edge, and end:

[0035] On the cloud side, a device management system is built based on Kubernetes technology. Kubernetes is an open source container orchestration platform that simplifies the deployment, expansion, and management of containerized applications. By packaging applications and their dependencies into lightweight containers, Kubernetes implements a flexible, efficient, and scalable deployment model, while supporting dynamic resource scheduling to adapt to rapid changes in the environment. On the cloud side, unified metadata management is implemented and standardized device models are formulated. The cloud side provides device discovery, registration, and monitoring functions, and the monitoring content includes the addition, deletion, modification, and query of device-related resources.

[0036] Specifically, device resources are defined through Kubernetes Custom Resource Definition (CRD), and a cloud controller (CloudController) is added to manage the corresponding device resources. The device resources include device models (Device Model) and devices (Device).

[0037] Device Model: An abstraction of a device template that defines the standard properties of a device (such as "temperature", "pressure", and "device status"), including device metadata, requirements for each metadata, device specifications, and requirements for each device specification. The device model defines the basic characteristics and functional parameters of the device and provides a reference for device instantiation.

[0038] Device: The definition of a device instance, including the specific values ​​of the device instance metadata and the specific values ​​of the device specifications. The device instance is the process of concretizing and instantiating the device model based on the specific conditions of the actual device.

[0039] Cloud Controller: The cloud controller monitors the addition, deletion, modification, and query information of device-related resources (such as device models and device instances) on the cloud side, and sends this information from the cloud side to the edge. It is also responsible for receiving device-related events reported from the edge to the cloud side and performing corresponding processing.

[0040] The cloud side uses etcd as the database persistence solution. etcd is a highly available, distributed key-value storage database that is suitable for storing and managing key information such as cluster configuration data, status information, and service discovery. etcd provides strong consistency and reliability, and has good horizontal scalability, which can cope with the growth and complexity of cluster size.

[0041] On the edge side, the edge cloud built on Kubernetes is deployed as part of the Kubernetes ecosystem to solve the deployment and management problems of distributed systems on edge nodes. The edge cloud system manages and controls edge devices through the edge controller (EdgeController). The edge controller (EdgeController) is used to manage the status and properties of end devices and synchronize the status information of devices between edge nodes and the cloud side to achieve persistence and consistency of device status. The specific functions of the edge controller (EdgeController) are as follows:

[0042] Device status synchronization: Ensure that the device status is synchronized between the edge node and the cloud when the device status is updated between the two. Both the cloud-side application and the edge application can obtain the latest status information of the device. For example, when the device status changes, the edge node will send the change information to the edge controller (EdgeController), and the edge controller (EdgeController) will synchronize this information to the cloud side, so that the cloud side can understand the device status changes in a timely manner.

[0043] Remote management: The cloud side remotely manages the end device through the edge controller (EdgeController). The management content includes modifying the device configuration, issuing commands, updating firmware, etc.; these management operations will be synchronized to the end-side device, thereby affecting the behavior of the device; for example, when the device firmware needs to be updated, the cloud side can send an update instruction to the edge controller (EdgeController), and the edge controller (EdgeController) forwards the instruction to the device. After the device completes the firmware update, it reports the update result to the edge controller (EdgeController), which is finally synchronized to the cloud side.

[0044] Disconnection processing: In edge computing scenarios, devices may often be offline or in a weak network state, and the connection with the cloud side is unstable. The edge controller (EdgeController) can operate autonomously in an offline state. When the device reconnects to the cloud side, the device status information is synchronized to the cloud side to prevent data loss or inconsistency; for example, when the device status changes while offline, the edge controller (EdgeController) will record these changes, and when the device is back online, the change information will be synchronized to the cloud side.

[0045] Application logic: The synchronization and management of device status can provide convenience for applications, such as real-time monitoring of device status, making decisions based on device status, etc.; for example, based on changes in device status, corresponding business logic can be triggered to achieve automated management and control.

[0046] SQLite is used as the database persistence solution on the edge. SQLite is a self-contained, zero-configuration SQL database engine. It is very lightweight and suitable for embedded devices and edge computing environments. In edge computing scenarios, resources are limited, and choosing a lightweight database can reduce resource consumption and is more suitable for running on edge devices.

[0047] On the end side, the end-side devices are managed through the deployed end controller (EndpointController), and the device information is persisted to the edge through the edge controller (EdgeController). At the same time, the device information is persisted (saved) to the cloud side through the cloud controller (CloudController), so that the device information on the end side corresponds to the device model (Device Model) and the device (Device) definition and is mapped one by one to keep data synchronized.

[0048] The device service module is installed on the end device, which is responsible for the collection, preprocessing and standardization of device data. The device service module supports the conversion of multiple IoT protocols (such as Modbus, MQTT, BLE, BACnet) to ensure that the data of different types of devices can be processed compatibly; the device service module collects data from the device and performs preliminary processing, such as data filtering, data aggregation and format conversion, to ensure data quality and consistency; the preprocessed data is transmitted to the edge node or cloud side through the network. The device service module supports multiple data transmission protocols (such as HTTP, MQTT, CoAP) to ensure the stability and reliability of data transmission.

[0049] The registration and management of end devices are carried out through the device service module. The device service module is used to register with the edge node, and the edge node then synchronizes the device information to the cloud side to complete the registration and management of the device. The end side collects the data of the end device through the device service module, and pre-processes the data through the device service module. After processing, the data is transmitted to the edge side. The device service in the device service module is used to convert the protocols of different IoT devices and standardize the data formats. The standardized device data is transmitted to the core service in the device service module for further processing and analysis. The data is analyzed, filtered and converted in real time, and operations can also be performed according to predefined rules and policies, such as issuing alarms, triggering events, etc. The device The support services in the service module provide edge data processing analysis and intelligent decision-making services, such as logging, scheduling and data cleaning functions. The export service can also process data under offline conditions, and provides APIs to build applications based on edge data, realizing the collection, processing and application of edge device data; then the cloud-side system receives the data uploaded by the edge nodes, extracts useful key information for storage and analysis, and generates control instructions to be issued based on the analysis results; the cloud-side system sends the generated control instructions to the end device, and the end device performs the corresponding operations and feeds back the execution results; the edge nodes synchronize the device status and control instructions between the cloud and the end device through the edge controller to ensure the consistency and real-time performance of the system.

[0050] The end side uses MongoDB as the database persistence solution. MongoDB is a database based on distributed file storage, which is highly scalable and flexible. It can store a large amount of end-side device data and event data, and can well meet the needs of the end side. In addition, MongoDB also has rich query languages ​​and index support, and can provide efficient data query and analysis functions.

[0051] The collaboration of cloud, edge, and end aims to integrate the advantages of cloud computing, edge computing, and end devices, and achieve efficient data processing, device management, and business applications through collaborative work. The process of cloud, edge, and end collaboration is as follows:

[0052] S1. Device registration and management. The end device registers with the edge node through the device service module. The edge node synchronizes the device information to the cloud side to complete the device registration and management.

[0053] Specifically, the name and device ID of the end device are packaged into the same piece of data for registration at the edge node.

[0054] S2, data collection and processing, the end device collects data, and after pre-processing by the device service module, the data is transmitted to the edge node. The edge node further processes and analyzes the data and uploads the data to the cloud side when necessary.

[0055] S3, data storage and analysis, the cloud-side system receives data uploaded by edge nodes, stores and conducts in-depth analysis to generate business insights and intelligent decisions.

[0056] Specifically, the method for generating business insights and intelligent decision-making includes: after the cloud-side system receives the data uploaded by the edge side, it extracts useful key information for storage and analysis, and sends commands to the edge-side nodes based on the analysis results.

[0057] S4: Control instructions are sent down. The cloud-side system generates control instructions based on intelligent decisions and sends them down to edge nodes or end devices. The end devices perform corresponding operations and feedback the execution results.

[0058] S5, state synchronization and feedback, the edge node synchronizes the device status and control instructions between the cloud side and the end device through the edge controller (EdgeController) to ensure the consistency and real-time performance of the system.

[0059] Through the collaborative work of cloud, edge, and end, efficient management of devices and real-time data processing are achieved, resource utilization is optimized, and system reliability and response speed are improved. This collaborative approach is suitable for large-scale distributed IoT application scenarios and can meet the efficient management and intelligent needs of modern smart devices and applications.

[0060] Challenges caused by differences in end-device communication protocols, such as Figure 2 As shown, the present invention also builds a standardized edge communication framework, which shields the underlying communication details, converts the format, adapts the protocol, and maps the data sent by the device, and performs data processing and analysis in the edge environment.

[0061] According to different protocols, end devices can be divided into terminal devices that are connected through the MQTT protocol and terminal devices that are connected through HTTP; for terminal devices that are connected through the MQTT protocol, corresponding adapters are developed. The adapter is responsible for converting the data of devices that support different protocols into the format supported by the MQTT protocol, and the data is transmitted through the MQTT Broker as the intermediate channel; for terminal devices that are connected through HTTP, the adapter is responsible for converting the data of devices that support different protocols into the format supported by HTTP.

[0062] The edge communication framework provides the following services:

[0063] Device service: The southbound data flow sent from the cloud-side application to the device layer mainly handles the protocol conversion and data format standardization of different IoT devices. The northbound data flow in the opposite direction realizes the forwarding of device information and the transmission of instructions for command control services. The device service supports multiple IoT protocols (such as modbus, MQTT, BLE, BACnet) and provides a development framework for unsupported protocols. Data standardization processing simplifies application development and avoids worrying about data format differences between different devices.

[0064] Core services: Standardized device data is transmitted to core services for further processing and analysis; core services include rule engines and data analysis engines, which can analyze, filter and convert data in real time; actions can be performed according to predefined rules and policies, such as issuing alarms, triggering events, etc.

[0065] Support services: Provide edge data processing analysis and intelligent decision-making services, such as logging, scheduling, and data cleaning functions; the rule engine microservice monitors edge device data, the scheduling microservice regularly cleans device data, the alarm microservice generates and sends alarms, and the log microservice receives log write requests.

[0066] Export service: It can process data even offline and provide APIs to build edge data-based applications. The interfaces include RESTful APIs and message queues, which support integration with existing applications and achieve real-time data transmission and processing. In some scenarios, it communicates with cloud platforms or other third-party systems to export device information for storage and analysis. It provides client registration services, timely notification of device data transmission, format processing, and supports json or XML formats.

[0067] Through the above service links, the collection, processing and application of edge device data are realized, which facilitates the construction and deployment of edge computing applications and improves the flexibility and efficiency of the system.

[0068] The steps in the present invention can be adjusted in order, combined or deleted according to actual needs.

[0069] The units in the device of the present invention can be combined, divided and deleted according to actual needs.

[0070] Although the present invention is disclosed in detail with reference to the accompanying drawings, it should be understood that these descriptions are merely exemplary and are not intended to limit the application of the present invention. The scope of protection of the present invention is defined by the appended claims and may include various modifications, alterations and equivalents made to the invention without departing from the scope and spirit of the present invention.

Claims

1. A method for efficiently enabling end devices for edge scenarios, characterized in that: The method comprises: Build a device management model to achieve centralized management and control of heterogeneous devices. The built device management model includes cloud, edge, device, and multiple end devices, as follows: The cloud side builds a unified metadata management system based on Kubernetes technology to define device resources and provide device discovery, registration, management, and monitoring functions. The cloud side monitors the addition, deletion, modification, and query information of device-related resources on the cloud side through the cloud controller, and sends this information from the cloud side. At the same time, the cloud controller is also responsible for receiving device-related events reported to the cloud side and performing corresponding processing; The edge cloud based on Kubernetes is deployed on the edge side. The edge cloud is responsible for accessing, standardizing, processing, and analyzing device data. The edge cloud synchronizes the real-time status information of the end device to the cloud side through the edge controller. The edge controller can also receive update instructions issued by the cloud side and forward them downward. The end side uses the device service module to achieve the conversion of different IoT protocols and standardization of data formats, and manages various end devices through the end controller. The management content includes establishing a mapping relationship between the end devices and the device resources defined on the cloud side. Various end devices are connected to the end side through corresponding IoT protocols; The process of cloud, edge, and end working together is as follows: S1. Device registration and management: The end device registers with the edge node through the device service module. The edge node synchronizes the device information to the cloud side to complete the device registration and management. S2. Data collection and processing: The end side collects data from the end device through the device service module, pre-processes the data through the device service module, and transmits the data to the edge side after processing. The edge side further processes and analyzes the data, and uploads the data to the cloud side for processing when necessary; S3, Data storage and analysis: The cloud-side system receives the data uploaded by the edge nodes, extracts useful key information for storage and analysis, and generates control instructions to be issued based on the analysis results; S4. Send control instructions: The cloud-side system will generate control instructions and send them to the end device. The end device will perform the corresponding operations and feedback the execution results. S5, state synchronization and feedback: The edge node synchronizes the device status and control instructions between the cloud side and the end device through the edge controller to ensure the consistency and real-time performance of the system.

2. The method for efficiently enabling end devices for edge scenarios according to claim 1 is characterized in that: The method also includes: building an edge communication framework to realize information interaction and data processing between end devices. According to different protocols, the end devices are divided into terminal devices that are connected through the MQTT protocol and terminal devices that are connected through HTTP; for terminal devices that are connected through the MQTT protocol, developing corresponding adapters, the adapter is responsible for converting the data of devices that support different protocols into the format supported by the MQTT protocol, and the data is transmitted through the MQTT Broker as an intermediate channel; for terminal devices that are connected through HTTP, the adapter is responsible for converting the data of devices that support different protocols into the format supported by HTTP.

3. The method for efficiently enabling end devices for edge scenarios according to claim 1, characterized in that: The cloud side uses etcd as the database persistence solution; the edge side uses SQLite as the database persistence solution; and the terminal side uses MongoDB as the database persistence solution.

4. The method for efficiently enabling end devices for edge scenarios according to claim 1, characterized in that: The device resources defined on the cloud side include Device Model and Device: Device Model: defines the standard properties of a device, including device metadata, requirements for various metadata, device specifications, and requirements for various device specifications. The Device Model defines the basic features and functional parameters of a device, providing a reference for device instantiation. Device: defines a device instance. The definition includes the specific values ​​of each metadata of the device instance and the specific values ​​of each device specification. The device instance is a process of concretizing and instantiating the device model according to the specific conditions of the actual device.

5. The method for efficiently enabling end devices for edge scenarios according to claim 1, characterized in that: The edge controller operates autonomously when the edge side and the cloud side are offline, records changes in the terminal device status, and synchronizes the terminal device status information to the cloud side after confirming that the network connection with the cloud side is re-established.

6. The method for efficiently enabling end devices for edge scenarios according to claim 1, characterized in that: The device service module on the end side supports multiple IoT protocols including Modbus, MQTT, BLE, and BACnet, and multiple data transmission protocols including HTTP, MQTT, and CoAP. The device service module collects data from the end device and performs preliminary processing such as data filtering, data aggregation, and format conversion; The preprocessed data is transmitted to the edge node or cloud side through the network.

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