Light node chain system, method and equipment based on edge computing and block chain and medium

Abstract

The invention discloses a light node chain system, method and device based on edge computing and a block chain and a medium, and belongs to the technical field of block chains, and the method comprises the steps: collecting edge hardware information, compiling an ARM architecture block chain executable file, cutting to obtain a lightweight mirror image, deploying edge block chain nodes, and generating a device unique identifier, creating an MQTT certificate and a hardware fingerprint as evidences, completing cloud side interaction, establishing a secure communication channel, processing data, deploying applications, pulling original business data to calculate an abstract, obtaining an application deployment list, deploying business applications, processing data, matching a consensus algorithm according to a scene, packaging, chaining a processing result, and archiving and storing; and finally, collecting node operation data, analyzing abnormity and performing remote operation and maintenance. According to the method, the problems of low cloud edge data collaboration efficiency, complex edge application deployment updating process, lack of hardware compatibility, excessive storage resource consumption, unbalanced algorithm computing power consumption and operation and maintenance management lagging in an edge computing scene are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of blockchains, in particular to a light node chain system, method, device and medium based on edge computing and blockchains. BACKGROUND

[0002] With the popularization of the Internet of Things and 5G technology, edge computing scenarios are increasingly complex, and the data generated by a large number of terminal devices needs to be processed in real time. The traditional cloud computing "centralized processing" mode faces problems such as bandwidth bottleneck, high delay, and waste of edge node computing power. At the same time, there is an urgent need for trusted storage and computing of edge-side data. The blockchain technology, with its distributed consensus and non-tamperable characteristics, has become an important technical direction for solving the trustworthiness of edge computing. However, the limited resources of edge nodes (such as low computing power, small storage, and weak network) lead to many technical challenges in the application of cloud-edge collaboration and blockchain technology.

[0003] The mainstream cloud-edge collaboration scheme is based on open source frameworks such as KubeEdge and EdgeX Foundry, which realize resource scheduling and application collaboration between the cloud and the edge. For example, some schemes realize cloud-edge data interaction through message queues and deploy edge applications using containerization technology, but there are the following problems:

[0004] Data collaboration relies on active issuance by the cloud, and the edge side lacks active acquisition capabilities, resulting in low data synchronization efficiency.

[0005] The application deployment update process is complex and requires manual intervention for image building and node configuration, making it difficult to adapt to the dynamic management of large-scale edge nodes. Edge node monitoring and operation rely on manual inspection and lack of automated alarm and remote debugging mechanisms.

[0006] Traditional blockchain technology is mainly deployed on cloud servers, and when extended to the edge side, it faces the following problems: the underlying architecture is not adapted to the mainstream ARM edge-side processors, resulting in the inability of blockchain nodes to run on smart terminals in the district. The full-data storage mode requires high storage capacity for edge nodes, which can easily cause storage overflow. The consensus algorithm consumes a lot of computing power, and edge nodes are difficult to support high-frequency consensus operations. SUMMARY

[0007] In view of the above problems, the present application is proposed.

[0008] Therefore, the technical problem solved by the present application is: if through the light node chain system based on edge computing and block chain, the cloud edge side lightweight technology architecture is realized. First, the lightweight block chain image is generated and deployed through the hardware adaptation module, the edge node hardware adaptation and cost reduction are realized; the cloud edge trusted connection is realized by using the double mode registration verification and interface interaction; then, the localization configuration is realized through data collaboration and application collaboration; then, the data trusted evidence is realized through the consensus processing of the data summary packaging module; finally, the storage resources are optimized through the hierarchical cutting storage of the block storage module; at the same time, the high-efficiency operation and maintenance are realized through the automatic monitoring, log management and upgrading of the operation and maintenance module.

[0009] To solve the above technical problems, the present application provides the following technical solutions: a light node chain system based on edge computing and block chain, comprising: a hardware adaptation module, configured to collect device hardware data in an edge node and compile a binary file, perform first cutting on the binary file and a basic system image to obtain a lightweight block chain image, deploy the lightweight block chain image to the edge node to obtain an edge block chain node; a data collaboration module, configured to establish a connection state between the edge node and a cloud end, and obtain a demand list according to a preset demand condition, and the edge node processes the demand list to obtain a data summary; an application collaboration module, configured to perform application localization configuration according to the data summary; a chain module, configured to process a consensus module in the edge block chain node according to the data summary to obtain block data; a block data storage module, configured to archive the block data to obtain archived data, upload the archived data to the cloud end, and store the archived data after second cutting; and an operation and maintenance module, configured to collect running data of the edge node according to the stored archived data, and perform operation and maintenance processing on an operating system according to the running data.

[0010] As a preferred scheme of the light node chain system based on edge computing and block chain, wherein: the first cutting on the binary file and the basic system image includes: after the first cutting on the binary file, the consensus module, the storage module and the network interaction module are retained; and after the first cutting on the basic system image, the necessary library file, the operating system kernel and the package management tool system core component are retained. The beneficial effects of the preferred technical scheme are that the image can adapt to the ARM architecture edge node, break the traditional block chain dependence on X86 architecture, reduce hardware cost, and the lightweight image makes the edge node start quickly, occupies less resources, and ensures stable and efficient operation of the edge block chain node.

[0011] As a preferred scheme of the edge computing and block chain based light node chain system, the step of obtaining the data digest comprises: establishing a demand list and transmitting the demand list to the edge node; the edge node pulls the demand data corresponding to the demand list from the basic data center and performs hash calculation on the demand data to generate the data digest.

[0012] As a preferred scheme of the edge computing and block chain based light node chain system, the step of performing application localization configuration according to the data digest comprises: packaging a business application corresponding to the demand list into an image package according to the data digest; uploading the image package to an image warehouse after auditing and performing system configuration to generate an application deployment list; and deploying the image package to the edge node after the edge node pulls the image package from the image warehouse. The beneficial effect of the preferred technical scheme is that the application is automatically configured by tool packaging, manual auditing, uploading to the warehouse, and generating and issuing a deployment list, which improves data synchronization efficiency, greatly shortens the time consumption of data pulling and storing evidence, releases message channel resources, simplifies the application deployment process, reduces manual intervention, reduces the risk of inconsistent configuration, ensures efficient and stable operation of the edge side business, and adapts to the needs of large-scale edge node scenarios.

[0013] As a preferred scheme of the edge computing and block chain based light node chain system, the step of obtaining the data digest comprises: establishing a demand list and transmitting the demand list to the edge node; the edge node pulls the demand data corresponding to the demand list from the basic data center and performs hash calculation on the demand data to generate the data digest.

[0014] As a preferred scheme of the edge computing and block chain based light node chain system, the step of performing application localization configuration according to the data digest comprises: packaging a business application corresponding to the demand list into an image package according to the data digest; uploading the image package to an image warehouse after auditing and performing system configuration to generate an application deployment list; and deploying the image package to the edge node after the edge node pulls the image package from the image warehouse. The beneficial effect of the preferred technical scheme is that the application is automatically configured by tool packaging, manual auditing, uploading to the warehouse, and generating and issuing a deployment list, which improves data synchronization efficiency, greatly shortens the time consumption of data pulling and storing evidence, releases message channel resources, simplifies the application deployment process, reduces manual intervention, reduces the risk of inconsistent configuration, ensures efficient and stable operation of the edge side business, and adapts to the needs of large-scale edge node scenarios.

[0015] As a preferred scheme of the edge computing and block chain based light node chain system, the running data of the edge node is collected according to the archived data, and the running data of the edge node is synchronously acquired according to the time stamp while the archived data is acquired.

[0016] The application provides an edge computing and block chain based light node chain method.

[0017] To solve the above technical problems, the application further provides the following technical scheme: an edge computing and block chain based light node chain method, comprising: collecting device hardware data in an edge node and compiling the device hardware data to obtain a binary file, performing first cutting on the binary file and a basic system image to obtain a light-weight block chain image, deploying the light-weight block chain image to the edge node to obtain an edge block chain node; establishing a connection state between the edge node and a cloud end, obtaining a demand list according to a preset demand condition, processing the demand list by the edge node to obtain a data digest; performing application localization configuration according to the data digest; processing a consensus module in the edge block chain node according to the data digest to obtain block data; archiving the block data to obtain archived data, uploading the archived data to the cloud end, performing second cutting on the archived data and storing the archived data; collecting running data of the edge node according to the stored archived data, and performing operation and maintenance processing on an operating system according to the running data.

[0018] The application provides a computer device, comprising a memory and a processor, and the memory stores a computer program.

[0019] The application provides a computer readable storage medium, which stores a computer program.

[0020] The beneficial effects of this invention are as follows: In cloud-edge data collaboration, by distributing data lists and actively pulling data from the edge, edge nodes can obtain business data on demand, avoiding invalid data transmission, reducing message channel occupation to ensure real-time command transmission, and shortening data synchronization latency to meet the timeliness requirements of real-time business on the edge side; In edge application management, by uploading images to the image repository according to the application marketplace, edge nodes can pull images from the image repository, realizing fully automated operation of edge applications, reducing manual intervention, avoiding configuration inconsistencies, and supporting uninterrupted business during application upgrades, ensuring service continuity on the edge side; In blockchain edge adaptation and storage, by cross-platform compilation and adaptation to the ARM architecture, the limitations of traditional blockchain hardware architecture are broken, allowing it to run stably on various edge terminals; By adopting a storage mode of cloud archiving and edge trimming, the storage pressure on edge nodes is reduced, data loss due to storage overflow is avoided, and data traceability is ensured; In operation and security, an automated operation and maintenance system collects node status in real time and automatically alarms, supports remote log management and system upgrades, and improves operation and maintenance efficiency; By using dual authentication and encrypted communication, unauthorized access is prevented, system security risks are reduced, and the operational security of edge nodes is ensured. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 The following is an overall flowchart of a lightweight node chain system based on edge computing and blockchain, provided as an embodiment of the present invention. Detailed Implementation

[0023] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0024] Example 1, referring to Figure 1 This is the first embodiment of the present invention, which provides a light node chain system based on edge computing and blockchain, including:

[0025] S100: Hardware adaptation module, used to collect device hardware data in edge nodes and compile it to obtain binary files. By performing a first trimming on the binary files and the basic system image, a lightweight blockchain image is obtained. The lightweight blockchain image is then deployed to the edge nodes to obtain edge blockchain nodes.

[0026] S200: Data collaboration module, which establishes a connection between edge nodes and the cloud. The cloud obtains a list of requirements based on preset requirements, and the edge nodes process the list of requirements to obtain a data summary.

[0027] S300: Application collaboration module, which performs localized application configuration based on data summaries.

[0028] S400: On-chain module, which processes the consensus module in the edge blockchain node based on the data digest to obtain block data.

[0029] S500: Block data storage module, which archives block data, obtains archived data, uploads the archived data to the cloud, and stores the archived data after a second trimming.

[0030] S600: Operation and maintenance module, which collects the operating data of edge nodes based on the stored archived data, and performs operation and maintenance processing on the operating system based on the operating data.

[0031] It should be noted that in existing edge computing and blockchain integration technologies, cloud-edge collaboration relies on proactive cloud deployment and manual operation, which is difficult to adapt to the resource-constrained characteristics of edge nodes. In scenarios with massive concurrent terminal devices, the deployment time of message channel applications is often too long. Secondly, when extending blockchain technology to the edge, insufficient consideration is given to hardware characteristics and operational constraints. The limitations of ARM architecture, low computing power, and small storage commonly used by edge nodes are ignored, leading to node deployment failures, storage overflows, consensus bottlenecks, and poor applicability of optimization results in actual edge scenarios. In addition, operation and maintenance management and data trustworthiness directly affect system stability, but edge nodes often suffer from low efficiency of manual inspection, data synchronization delays, and unauthorized access and tampering. Traditional methods lack automated monitoring and dual authentication mechanisms, making it difficult to ensure the real-time trustworthiness of edge data and the secure operation of the system.

[0032] Therefore, to address the issues of low cloud-edge data collaboration efficiency, complex and unautomated edge application deployment and update processes, lack of hardware compatibility, excessive storage resource consumption, unbalanced algorithm computing power consumption, and lagging operation and maintenance management in the aforementioned edge computing scenarios, a lightweight node chain system can be constructed through the steps of S100-S600. First, edge device hardware data is collected, an executable file supporting the ARM architecture is compiled, and a lightweight blockchain image is generated and deployed as an edge blockchain node. Second, a unique identifier is generated for each edge node, and a connection is established after verification with the cloud. Next, the cloud generates a requirement list based on the connection status, and the edge node obtains business data and data summaries, completing localized configuration through application collaboration. Then, the data summaries are processed by the scenario consensus module and stored on the blockchain as block data. Next, the block data is filtered, archived, and uploaded to the cloud, and after a second trimming, the hash header and tail are retained for storage. Finally, operational data is collected, automatic alarms are triggered when thresholds are exceeded, and remote operation and maintenance are supported.

[0033] Example 2, refer to Figure 1 This is the second embodiment of the present invention, which provides a light node chain system based on edge computing and blockchain.

[0034] In this embodiment of the invention, the hardware adaptation module in step S100 is used to collect device hardware data in the edge node and compile it to obtain a binary file. By performing a first trimming on the binary file and the basic system image, a lightweight blockchain image is obtained. The lightweight blockchain image is then deployed to the edge node to obtain an edge blockchain node.

[0035] Regarding processor architecture adaptation, cross-platform compilation technology is employed. The blockchain source code is compiled on the CentOS 7 ARM architecture system to generate an executable file that supports the ARMv8 instruction set, while retaining x86 architecture compilation capabilities. The GCC cross-compilation toolchain is used to convert the core blockchain module into an ARM architecture binary file.

[0036] Specifically, in step A3, the Ubuntu 18.04 ARM architecture system is trimmed, removing the GNOME desktop environment and redundant development tool components, retaining only the necessary OpenSSL and libcurl library files, and compressing the base image from 400MB to approximately 200MB. Simultaneously, the blockchain functional modules are trimmed as needed, retaining only the PBFT / RAFT consensus modules and removing the high-computing-power-consuming POW modules.

[0037] It should be noted that the core modules of a blockchain include a consensus module, a storage module, and a network module.

[0038] In one possible implementation, the GCC cross-compilation toolchain can also be replaced by the Clang / LLVM toolchain, which supports open-source compiler frameworks for multiple architectures, has fast compilation capabilities, generates concise binary files, and can be configured to directly compile source code for the corresponding target architecture. Since the edge nodes in this invention are mostly ARM architecture and there are hybrid architecture scenarios, this toolchain can adapt to the compilation requirements of ARM architecture while also supporting x86 architecture, meeting the functional requirements of cross-platform compilation for edge nodes.

[0039] In another possible implementation, the GCC cross-compilation toolchain can be replaced by a combined MUSL and GCC toolchain. This toolchain combines the GCC compiler with the lightweight C standard library MUSL. MUSL has simple dependencies, reducing redundant dependencies in the compiled output. Given the low computing power and limited storage characteristics of edge nodes in this invention, this toolchain can adapt to the lightweight compilation requirements of edge nodes and fit their resource-constrained functional scenarios.

[0040] In this embodiment of the invention, in step S200, the data collaboration module establishes a connection between the edge node and the cloud. The cloud obtains a demand list based on preset demand conditions, and the edge node processes the demand list to obtain a data summary.

[0041] It should be noted that in the S200, the edge node establishes a connection with the cloud through a dual-mode secure network access mechanism and remote operation and maintenance. The unique identifier includes the MAC address and firmware ID.

[0042] The dual-mode secure network access includes manual registration and automatic registration. Both modes use TLS 1.3 encrypted communication to ensure secure certificate transmission.

[0043] Specifically, MQTT certificates and hardware fingerprints are created to obtain device authentication credentials; the MQTT certificate is generated during manual registration, while the hardware fingerprint is verified during automatic registration, and both are device authentication credentials.

[0044] The specific steps for manual registration are as follows: the administrator enters the unique identifier of the edge node on the cloud management platform, generates the MQTT certificate and account password, packages it into the edge core service installation package, and installs it on the device offline via a USB flash drive or other media. After the device starts up, it automatically uses the certificate to connect to the cloud EMQX.

[0045] The specific steps of automatic registration are as follows: the device loads the operating system image integrating the edge core service, and after starting, it actively sends a registration request to the cloud identity authentication service. After the cloud verifies the device's unique identifier, it automatically generates a certificate and account password and returns them to the device to complete the access.

[0046] It should be noted that when registering manually, the unique identifier is specifically the MAC address and firmware ID; when registering automatically, the unique identifier is specifically the hardware fingerprint.

[0047] This involves establishing a connection between edge nodes and the cloud, with the cloud obtaining a list of requirements based on preset conditions, and the edge nodes processing the list to obtain a data summary.

[0048] Specifically, the business requirements list is transmitted to the edge nodes, and the edge blockchain nodes pull the business data from the basic data center, perform hash calculations, and generate data summaries.

[0049] In one possible implementation, the creation of MQTT certificates and hardware fingerprints to obtain device authentication credentials can also be replaced by X.509 digital certificates and PSKs. The X.509 digital certificate serves as the device identity credential and supports on-chain verification, while the PSK is a pre-configured symmetric key suitable for low-computing-power edge nodes. According to the dual-mode network access method of this invention, during manual registration, the PSK and certificate are pre-packaged; during automatic registration, the certificate and temporary PSK are dynamically distributed from the cloud, both enabling identity verification and adapting to the security authentication requirements of edge nodes.

[0050] In another possible implementation, the creation of MQTT certificates and hardware fingerprints to obtain device authentication credentials can be replaced by blockchain identity identifiers and JWT tokens. The blockchain stores the unique identifier of the device, forming an immutable identity, while the JWT token serves as a short-term access credential containing device permission information. During manual registration, the identifier is written to the blockchain, and during automatic registration, a JWT is generated based on the identifier. The combination of the two supports trusted authentication for dual-mode network access, fitting lightweight interaction scenarios between the edge and the cloud.

[0051] In this embodiment of the invention, in step S300, the application collaboration module performs application localization configuration based on the data digest.

[0052] Specifically, based on the data summary, the business application is packaged into an image using a tool. After manual review, the image is uploaded to the image repository and configured by the system to generate an application deployment list. The application deployment list is then distributed to the edge nodes through the communication module. The edge nodes pull the image from the image repository and perform local configuration.

[0053] Specifically, the communication module ensures that cloud commands take effect on the blockchain through the cloud collaboration API interface, and the blockchain stores the collected edge node data to the cloud database through the RESTful interface provided by the Front component.

[0054] In one implementation, edge blockchain nodes can also pull business data from the underlying data center via a Kafka message queue push mechanism. As a high-throughput messaging system, Kafka allows the underlying data center to push data to designated message topics based on a list of business needs. Edge nodes can subscribe to these topics to receive data and then perform hash calculations locally to generate digests. This approach reduces the resource consumption of edge nodes actively pulling data, adapts to the real-time transmission requirements of business data in data collaboration services, and supports the acquisition of locally configured data infrastructure.

[0055] In another possible implementation, edge blockchain nodes can also pull business data from the basic data center through the built-in data synchronization service of the edge computing platform. Relying on the inter-module communication mechanism of Azure IoT Edge, the basic data center synchronizes business data to the corresponding edge module through the cloud module, and the edge node directly obtains data from the local module and generates a summary.

[0056] In this embodiment of the invention, in step S400, the on-chain module processes the consensus module in the edge blockchain node according to the data digest to obtain block data.

[0057] It should be noted that, based on the obtained data summary, transactions are deployed through smart contracts to store the data summary on the blockchain, while the original data is stored in a local database on the edge side.

[0058] It should be noted that when uploading the data digest to the blockchain, it is necessary to determine whether the data digest is valid. In a multi-zone network scenario, if the PBFT algorithm in the consensus module is identical to the data digest and reaches a first threshold, the data digest is packaged into block data. In a single-zone orphan chain scenario, if the RAFT algorithm in the consensus module is identical to the data digest and reaches a second threshold, the data digest is packaged into block data. Otherwise, the data digest is deemed invalid and deleted.

[0059] It should be noted that smart contract deployment transactions involve uploading the data digest notarization code to the edge blockchain, completing initialization, and recording it as an on-chain transaction, supporting the automatic uploading of edge data to the blockchain. The contract is trimmed, and the transaction uses the RAFT / PBFT low-computing-power consensus module, initiated by the cloud or edge node, activated after parameter verification, and then called by subsequent edge nodes.

[0060] In this embodiment of the invention, in step S500, the block data storage module archives the block data to obtain archived data, uploads the archived data to the cloud, and stores the archived data after a second trimming.

[0061] Specifically, edge blockchain nodes periodically or according to block height trigger data archiving. The data archiving component packages and uploads historical block data to the cloud BaaS platform for storage. After the upload is completed, the data trimming component deletes the main data of the archived blocks on the edge side, retaining only the block hash header and tail for subsequent data verification.

[0062] It should be noted that the second pruning involves deleting the archived block body data on the edge side through a data pruning component, retaining only the block hash header and tail.

[0063] In one implementation, edge-side block data can be packaged and uploaded to the cloud-based BaaS platform via IPFS distributed storage. Edge nodes encrypt historical block data and store it in IPFS, generating unique content identifiers. Only the unique content identifiers are uploaded to the cloud. The cloud can access the complete data through the unique content identifiers, and the unique content identifiers are retained for verification during edge-side pruning.

[0064] In another possible implementation, edge-side block data can be packaged and uploaded to the cloud-based BaaS platform via an edge-cloud incremental synchronization mechanism. Edge nodes use the rsync algorithm to calculate the differences between historical blocks and locally stored data, uploading only the incremental data to the cloud, where it is merged into a complete archive. During edge-side pruning, the block body excluding the incremental data is deleted, while the incremental hash is retained for verification.

[0065] In this embodiment of the invention, in step S600, the operation and maintenance module collects the running data of the edge nodes based on the stored archived data, and performs operation and maintenance processing on the operating system based on the running data.

[0066] The operation and maintenance process includes equipment monitoring, log management, and upgrade modules.

[0067] The device monitoring system collects operational data from the edge nodes at regular intervals. When the operational data exceeds a set threshold, an alarm is issued via SMS and email.

[0068] Log management supports remote querying of kernel logs, system logs, and application logs, and provides log keyword search and export functions. Log export adopts block transmission and supports asynchronous download of log files up to 1GB.

[0069] The upgrade module supports online upgrades of the operating system, kernel, and edge core services. Upgrade packages are selected from the device upgrade package repository and downloaded using a breakpoint resume method. The device status is saved during the upgrade process, and services are automatically restored after the upgrade is completed, ensuring that the upgrade does not interrupt services.

[0070] In summary, this invention addresses cloud-edge data collaboration by enabling edge nodes to acquire business data on demand through data list distribution and proactive edge retrieval. This avoids invalid data transmission, reduces message channel occupancy to ensure real-time command transmission, and shortens data synchronization latency, meeting the timeliness requirements of real-time edge services. For edge application management, images are uploaded from the application marketplace to the image repository, and edge nodes retrieve images from the repository, achieving fully automated operation of edge applications. This reduces manual intervention, avoids configuration inconsistencies, and supports uninterrupted service during application upgrades, ensuring service continuity on the edge side. Regarding blockchain edge adaptation and storage, cross-platform compilation adapts to the ARM architecture, breaking the limitations of traditional blockchain hardware architecture and enabling stable operation on various edge terminals. The use of cloud archiving and edge-trimmed storage reduces storage pressure on edge nodes, prevents data loss due to storage overflow, and ensures data traceability. In terms of operation and security, an automated operation and maintenance system collects node status in real time and automatically alerts, supporting remote log management and system upgrades, improving operational efficiency. Dual authentication and encrypted communication prevent unauthorized access, reduce system security risks, and ensure the safe operation of edge nodes.

[0071] Example 3 is the third embodiment of the present invention, which provides a lightweight node chain method based on edge computing and blockchain, including:

[0072] This is used to collect device hardware data in edge nodes and compile it to obtain an executable file. A lightweight blockchain image is obtained by first trimming the executable file. The lightweight blockchain image is then deployed to the edge nodes to obtain edge blockchain nodes.

[0073] Used to generate a unique identifier through edge blockchain nodes, and to verify with the cloud through the unique identifier to establish a connection status;

[0074] It is used to obtain a list of requirements based on the connection status and business scenario requirements in the cloud, obtain business data and data summary through data collaboration service, and realize local configuration based on data summary through application collaboration service;

[0075] It is used to obtain the block packaging confirmation result by processing the data digest through the consensus module, and to store the data digest on the chain to obtain the block data;

[0076] It is used to filter and upload block data to the cloud and archive it, obtain archived data, and store the archived data after a second trimming.

[0077] It is used to collect operational data of edge nodes based on stored archived data, and to perform operation and maintenance processing on the operating system based on the operational data.

[0078] Example 4, the fourth embodiment of the present invention, differs from the previous three embodiments in that: if the function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0079] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0080] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0081] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination of all three. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0082] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A lightweight node chain system based on edge computing and blockchain, characterized in that: include, The hardware adaptation module is used to collect device hardware data in the edge node and compile it to obtain a binary file. By performing a first trimming on the binary file and the basic system image, a lightweight blockchain image is obtained. The lightweight blockchain image is then deployed to the edge node to obtain an edge blockchain node. The data collaboration module establishes a connection between edge nodes and the cloud. The cloud obtains a list of requirements based on preset requirements, and the edge nodes process the list of requirements to obtain a data summary. The application collaboration module performs localized application configuration based on the data digest. The on-chain module processes the consensus module in the edge blockchain node according to the data digest to obtain block data; The block data storage module archives the block data, obtains archived data, uploads the archived data to the cloud, and stores the archived data after a second trimming. The operation and maintenance module collects the operating data of the edge nodes based on the stored archived data, and performs operation and maintenance processing on the operating system based on the operating data.

2. The lightweight node chain system based on edge computing and blockchain as described in claim 1, characterized in that: The first trimming step of the binary file and the base system image includes: After the first trimming process trims the binary file, the consensus module, storage module, and network interaction module are retained. After the first trimming process trims the base system image, it retains the necessary library files, operating system kernel, package management tools, and core system components.

3. The lightweight node chain system based on edge computing and blockchain as described in claim 2, characterized in that: The steps to obtain a data summary include: Create a requirements list and transmit the requirements list to the edge nodes; The edge node pulls the demand data corresponding to the demand list from the basic data center, performs hash calculation on the demand data, and generates a data digest.

4. The lightweight node chain system based on edge computing and blockchain as described in claim 3, characterized in that: The steps for localizing application configuration based on the data digest include: Based on the data summary, the business applications corresponding to the requirement list are packaged into image packages; After the image package is reviewed, it is uploaded to the image repository, and the system is configured to generate an application deployment list; The edge node pulls the image package from the image repository and then deploys it to the edge node.

5. The lightweight node chain system based on edge computing and blockchain as described in claim 4, characterized in that, The steps to obtain block data include: The consensus module determines whether the data digest is valid. When in a multi-unit network scenario, if the PBFT algorithm in the consensus module is identical to the data digest to the first threshold, the data digest is packaged into block data. When in a single-server orphan chain scenario, if the RAFT algorithm in the consensus module is identical to the data digest and reaches the second threshold, the data digest is packaged into block data. Otherwise, the data digest is deemed invalid, and the corresponding data digest is deleted.

6. The lightweight node chain system based on edge computing and blockchain as described in claim 5, characterized in that, The step of performing a second trimming and storing the archived data includes: The edge nodes perform archiving at a set period or according to the block height of the block data, obtain archived data, and upload it to the cloud. The second trimming method deletes the block body data of the archived data, retains the hash header and hash tail, and then stores it in the cloud.

7. The lightweight node chain system based on edge computing and blockchain as described in claim 5, characterized in that, The operational data of the edge nodes is collected based on the stored archived data, including: While acquiring the archived data, the running data of the edge nodes are also acquired synchronously based on the timestamp; The operational data of the edge nodes includes the device hardware data, the light node chain system data, and the business application data.

8. A lightweight node chain method based on edge computing and blockchain, employing the lightweight node chain system based on edge computing and blockchain as described in any one of claims 1 to 7, characterized in that, include: The data is used to collect device hardware data in the edge node and compile it to obtain a binary file. By performing a first trimming on the binary file and the base system image, a lightweight blockchain image is obtained. The lightweight blockchain image is then deployed to the edge node to obtain an edge blockchain node. The edge node establishes a connection with the cloud. The cloud obtains a list of requirements based on preset requirements. The edge node processes the list of requirements to obtain a data summary. Perform application localization configuration based on the data digest; The consensus module in the edge blockchain node processes the data digest to obtain block data. The block data is archived to obtain archived data, and the archived data is uploaded to the cloud. The archived data is then stored after a second trimming. The operating data of the edge nodes is collected based on the stored archived data, and the operating system is operated and maintained based on the operating data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the light node chain system based on edge computing and blockchain as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the light node chain system based on edge computing and blockchain as described in any one of claims 1 to 7.

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