Internet of Things gateway and gateway control method

Abstract

The invention relates to the technical field of Internet of Things gateways, in particular to an Internet of Things gateway and a gateway control method. The method comprises the following steps: acquiring initial state information of a gateway node of the Internet of Things to obtain gateway initial state data; connecting each gateway node with a block chain network according to the gateway initial state data, performing device identity verification on each gateway node and an access device through a block chain technology, and allocating initial tasks and resources of each gateway node by using a smart contract to generate initial resource allocation data; and performing local data processing on the gateway node through edge computing according to the initial resource allocation data to generate a local data processing result. By combining the block chain, the edge calculation and the smart contract, the expansibility, the reliability and the security of the system are improved, intelligent task scheduling and resource management are realized, and a complex scene of the Internet of Things is effectively dealt with.

Description

Technical Field

[0001] The present invention relates to the technical field of networking gateways, and in particular to an Internet of Things gateway and a gateway control method. Background Art

[0002] Many traditional gateways lack sufficient depth in security design. Most gateways rely only on simple authentication mechanisms and fail to make full use of advanced technologies such as blockchain for multiple verification of device identities and secure storage of data. This makes the IoT system extremely vulnerable to cyber attacks, posing huge security risks to the sensitive data of enterprises and user privacy. The resource management and task scheduling capabilities of IoT gateways on the current market are also relatively weak. Many IoT applications need to run in a dynamic environment, which requires the gateway to flexibly adjust resource and task allocation according to real-time status and needs. However, many existing gateway control methods are often static and lack intelligent decision-making capabilities. This single resource scheduling method not only reduces the efficiency of the system, but also makes it impossible for the system to respond quickly in emergencies, affecting the reliability of the service. The lack of an effective data sharing and collaboration mechanism is also a major shortcoming of existing IoT gateways. Many gateways only focus on local data processing and ignore cross-node collaboration and data sharing. As a result, although each node can operate independently, the overall system's intelligence and collaboration capabilities are limited. In many application scenarios, data sharing and collaboration are the key to achieving more efficient decision-making and operations. Lack of support in this regard will result in the failure to realize the potential of the overall system. In summary, the current IoT gateways and their control methods have significant defects in security, resource management, and coordination mechanisms. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide an Internet of Things gateway and a gateway control method to solve at least one of the above technical problems.

[0004] To achieve the above object, a control method for an Internet of Things gateway comprises the following steps: Step S1: Obtain the initial state information of the IoT gateway node to obtain the gateway initial state data; connect each gateway node to the blockchain network according to the gateway initial state data, perform device identity authentication on each gateway node and access device through blockchain technology, and use smart contracts to allocate initial tasks and resources to each gateway node to generate initial resource allocation data; Step S2: Perform local data processing on the gateway node through edge computing according to the initial resource allocation data to generate local data processing results; use the real-time performance monitoring API to monitor the system operation status of each gateway node in real time to obtain system operation status data; based on the local data processing results and system operation status data, dynamically adjust the task priority and resource allocation strategy to generate an optimized task allocation plan; Step S3: perform collaborative computing and distributed task processing on each gateway node according to the optimized task allocation scheme, and use blockchain to record the task execution history and resource usage of each gateway node to obtain task allocation execution result data; generate real-time computing results based on the real-time computing capability of the node according to the task allocation execution result data to obtain real-time computing result data; perform data sharing and task collaboration on each gateway node to obtain a data storage sharing strategy; Step S4: Encrypt and store the data through distributed storage technology according to the real-time calculation result data, and synchronize the data between nodes through the blockchain network to generate a distributed data storage optimization plan; dynamically adjust the data storage sharing strategy using smart contracts according to the distributed data storage optimization plan to obtain a data storage sharing plan; Step S5: Monitor and evaluate the task execution effect of each gateway node according to the data storage sharing scheme, and generate task execution monitoring results; verify the task execution status using the blockchain consensus mechanism according to the task execution monitoring results, and dynamically adjust resources and tasks according to the verification results to generate a system optimization control model; Step S6: Comprehensively schedule the task execution and resource allocation of the IoT gateway system according to the system optimization control model, and build a distributed gateway collaboration network model; coordinate tasks and dynamically optimize the control of each gateway node through the distributed gateway collaboration network model, and generate dynamic optimization control data to improve the scalability and reliability of the gateway system.

[0005] The present invention uses blockchain technology to authenticate the identity of IoT gateway nodes and access devices, ensure the legitimacy of the device identity, and improve the security of the system. The initial tasks and resources of each gateway node are allocated using smart contracts, making the task and resource allocation automatic and intelligent, reducing manual intervention and improving resource utilization efficiency. Edge computing technology is used to perform local data processing on gateway nodes, reducing the delay of data transmission, and improving real-time processing capabilities and system response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings: Figure 1A schematic diagram of the steps of the Internet of Things gateway and the gateway control method of the present invention; Figure 2 for Figure 1 Detailed step flow diagram of step S1; Figure 3 for Figure 1 Detailed step flow diagram of step S2; Figure 4 for Figure 1 Detailed step flow chart of step S3 in FIG. DETAILED DESCRIPTION

[0007] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0008] To achieve this, please refer to Figures 1 to 4 The present invention provides a control method for an Internet of Things gateway, the method comprising the following steps: Step S1: Obtain the initial state information of the IoT gateway node to obtain the gateway initial state data; connect each gateway node to the blockchain network according to the gateway initial state data, perform device identity authentication on each gateway node and access device through blockchain technology, and use smart contracts to allocate initial tasks and resources to each gateway node to generate initial resource allocation data; Step S2: Perform local data processing on the gateway node through edge computing according to the initial resource allocation data to generate local data processing results; use the real-time performance monitoring API to monitor the system operation status of each gateway node in real time to obtain system operation status data; based on the local data processing results and system operation status data, dynamically adjust the task priority and resource allocation strategy to generate an optimized task allocation plan; Step S3: perform collaborative computing and distributed task processing on each gateway node according to the optimized task allocation scheme, and use blockchain to record the task execution history and resource usage of each gateway node to obtain task allocation execution result data; generate real-time computing results based on the real-time computing capability of the node according to the task allocation execution result data to obtain real-time computing result data; perform data sharing and task collaboration on each gateway node to obtain a data storage sharing strategy; Step S4: Encrypt and store the data using distributed storage technology based on the real-time calculation result data, and synchronize the data between nodes through the blockchain network to generate a distributed data storage optimization plan; dynamically adjust the data storage sharing strategy using smart contracts based on the distributed data storage optimization plan to obtain a data storage sharing plan; Step S5: Monitor and evaluate the task execution effect of each gateway node according to the data storage sharing scheme, and generate task execution monitoring results; verify the task execution status using the blockchain consensus mechanism according to the task execution monitoring results, and dynamically adjust resources and tasks according to the verification results to generate a system optimization control model; Step S6: Comprehensively schedule the task execution and resource allocation of the IoT gateway system according to the system optimization control model, and build a distributed gateway collaboration network model; coordinate tasks and dynamically optimize the control of each gateway node through the distributed gateway collaboration network model, and generate dynamic optimization control data to improve the scalability and reliability of the gateway system.

[0009] In the embodiment of the present invention, reference Figure 1 The above is a schematic flow chart of a control method of an Internet of Things gateway of the present invention. In this example, the Internet of Things gateway and the gateway control method include the following steps: Step S1: Obtain the initial state information of the IoT gateway node to obtain the gateway initial state data; connect each gateway node to the blockchain network according to the gateway initial state data, perform device identity authentication on each gateway node and access device through blockchain technology, and use smart contracts to allocate initial tasks and resources to each gateway node to generate initial resource allocation data; The embodiment of the present invention is completed by an Internet of Things device management platform and a variety of monitoring tools. The hardware status information of the node may include the usage of CPU, memory, and storage resources; the network connection status includes parameters such as bandwidth, network delay, and data transmission rate; the security status is obtained by monitoring the intrusion detection, identity authentication, and data transmission security of each node; the device access information records the number, type, and status of the Internet of Things devices currently connected to each gateway node. Based on the acquired gateway initial state information, the gateway initial state data is generated. The initial state data comprehensively reflects the resource availability and current operating status of each gateway node. After the gateway initial state data is generated, the blockchain technology is used to implement device identity authentication for each gateway node and the Internet of Things devices connected to it to ensure the legitimacy and security of each node and device in the network. Here, through the blockchain technology, the device identity authentication is based on the trusted identity information stored on the chain, and the identity of each node is verified through the distributed ledger to prevent forgery or tampering. After completing the identity authentication, the initial tasks and resources of the gateway node are allocated using smart contracts. The smart contract will automatically allocate appropriate tasks and resources to each node according to the resource situation, task requirements, and initial state information of each gateway node, and generate initial resource allocation data. This allocation process ensures the transparency and rationality of task and resource allocation, laying the foundation for the collaborative computing, task allocation and dynamic optimization control of gateway nodes in the subsequent steps, and ensuring the security, reliability and rational allocation of resources of the system.

[0010] Step S2: Perform local data processing on the gateway node through edge computing according to the initial resource allocation data to generate local data processing results; use the real-time performance monitoring API to monitor the system operation status of each gateway node in real time to obtain system operation status data; based on the local data processing results and system operation status data, dynamically adjust the task priority and resource allocation strategy to generate an optimized task allocation plan; The embodiment of the present invention uses edge computing technology to perform local data processing on each IoT gateway node based on the initial resource allocation data. The implementation of edge computing distributes the data processing tasks to each gateway node so that the data can be processed close to the source, reducing the delay of data transmission and the burden of the central server. After each gateway node receives the initial resource allocation data, it will pre-process, calculate and analyze the received local data according to the assigned tasks and resources to generate corresponding local data processing results. During the data processing process, the system operation status of the gateway node is monitored using a real-time performance monitoring API. These APIs record the key performance indicators of each node (such as CPU usage, memory usage, network bandwidth, and data processing time, etc.) and generate system operation status data. These data reflect the performance of each gateway node in real time and help evaluate its load and resource consumption. Based on the local data processing results and the system operation status data, the task priority and resource allocation strategy are dynamically adjusted. In order to improve the system efficiency, a greedy algorithm is used to analyze these data. Through the greedy algorithm, the priority of the task is adjusted in real time according to the current resource usage and task completion of the gateway node, and the resources are dynamically optimized and allocated. This ensures that high-priority tasks are processed first and resources are more reasonably allocated to each node to avoid resource waste or overload. Based on these adjustments, an optimized task allocation plan is generated. This plan is used to guide task coordination and distributed processing between gateway nodes in subsequent steps, improving the overall system performance and task execution efficiency.

[0011] Step S3: perform collaborative computing and distributed task processing on each gateway node according to the optimized task allocation scheme, and use blockchain to record the task execution history and resource usage of each gateway node to obtain task allocation execution result data; generate real-time computing results based on the real-time computing capability of the node according to the task allocation execution result data to obtain real-time computing result data; perform data sharing and task collaboration on each gateway node to obtain a data storage sharing strategy; The embodiment of the present invention performs collaborative computing and distributed task processing on each IoT gateway node based on an optimized task allocation scheme. Each gateway node performs tasks according to the assigned task priority and resources according to the optimized task allocation scheme. The collaborative computing process realizes parallel processing of tasks and improves the efficiency of task execution through coordination between nodes. While the task is being executed, the task execution history and resource usage of each gateway node are recorded in real time using blockchain technology. Specifically, the blockchain records the task processing log, resource usage data, task completion time and other information of each node, and these data are stored in the blockchain network in an unalterable manner. This ensures the transparency and traceability of task execution of each node, while enhancing the security and credibility of the system. Based on the recorded task execution history, task allocation execution result data is generated. These result data reflect the completion status and resource usage of task execution of each node, including task completion time, resource consumption and task success rate. Based on the task allocation execution result data, real-time calculation based on the real-time computing power of the node is performed. Each gateway node generates real-time calculation result data based on its current computing power and task execution status. These data can reflect the load status and resource utilization efficiency of the node when executing the task, and provide a reference basis for subsequent optimization. In addition, data sharing and task collaboration are carried out between the gateway nodes. Based on the task allocation execution results and the computing power of the nodes, a data storage sharing strategy is generated. This strategy ensures that each node can efficiently share necessary data during the task execution process, reduce data transmission delays, and fully utilize resources, ultimately improving the overall performance of the system.

[0012] Step S4: Encrypt and store the data through distributed storage technology according to the real-time calculation result data, and synchronize the data between nodes through the blockchain network to generate a distributed data storage optimization plan; dynamically adjust the data storage sharing strategy using smart contracts according to the distributed data storage optimization plan to obtain a data storage sharing plan; According to the real-time calculation result data, the embodiment of the present invention encrypts and stores all relevant data through distributed storage technology. Before the data of each IoT gateway node is stored, it will be processed by an encryption algorithm to ensure the security and privacy protection of the data. The specific method of encrypted storage can select a symmetric or asymmetric encryption method to ensure the security of data during storage and transmission according to system requirements. The gateway nodes synchronize data through the blockchain network. The blockchain network provides a distributed ledger, so that the data synchronization between nodes has a high degree of transparency and non-tamperability. The data synchronization process ensures that each node has the latest task execution data, resource usage data and other related information, thereby enhancing the effectiveness of collaborative work between nodes. In the process of data synchronization, a distributed data storage optimization scheme is generated based on the performance of data transmission and storage. Through the storage performance monitoring module, the storage performance of each node is analyzed in real time, and an optimized storage scheme is generated by combining information such as data synchronization delay and data integrity verification results. The scheme ensures the efficiency and stability of distributed storage by reasonably allocating storage resources and optimizing the data synchronization mechanism. According to the generated distributed data storage optimization scheme, the data storage sharing strategy is dynamically adjusted using smart contracts. Smart contracts automatically adjust data sharing strategies based on the current storage status and the collaborative work between nodes to ensure that the system can flexibly respond to data storage needs and improve storage efficiency in a changing environment.

[0013] Step S5: Monitor and evaluate the task execution effect of each gateway node according to the data storage sharing scheme, and generate task execution monitoring results; verify the task execution status using the blockchain consensus mechanism according to the task execution monitoring results, and dynamically adjust resources and tasks according to the verification results to generate a system optimization control model; According to the data storage sharing scheme, the embodiment of the present invention monitors and evaluates the task execution effect of each gateway node in real time. Through the monitoring tool embedded in the system, the task execution status, resource usage and collaborative work effect of each gateway node in the entire Internet of Things network are collected to generate task execution monitoring result data. These monitoring results include indicators such as the timeliness of task completion, the efficiency of resource usage and the degree of collaboration between tasks. The task execution of each gateway node is verified by using the blockchain consensus mechanism. The verification process ensures the authenticity and integrity of the task execution and resource usage data reported by each node through the distributed consensus algorithm of the blockchain. All nodes participate in the verification together, and only the data confirmed by the consensus mechanism is recognized as credible data. This process ensures the security, transparency and consistency of task execution and data storage. After the verification is completed, the system will automatically adjust the resources and tasks dynamically according to the verification results. Through the smart contract, the system analyzes the execution of tasks and the efficiency of resource usage, and adjusts the task priority, resource allocation strategy and task allocation rules of each gateway node. This dynamic adjustment can optimize the efficiency of system resource usage, avoid performance bottlenecks caused by task overload or insufficient resources of some nodes, thereby improving the execution efficiency and task processing capability of the entire gateway system. This step generates a system optimization control model, which is used for subsequent resource scheduling and task allocation to ensure that the gateway system maintains efficient operation in task execution and resource management and can adapt to the dynamically changing network environment.

[0014] Step S6: Comprehensively schedule the task execution and resource allocation of the IoT gateway system according to the system optimization control model, and build a distributed gateway collaboration network model; coordinate tasks and dynamically optimize the control of each gateway node through the distributed gateway collaboration network model, and generate dynamic optimization control data to improve the scalability and reliability of the gateway system.

[0015] The embodiment of the present invention performs comprehensive scheduling on the task execution and resource allocation of the Internet of Things gateway system based on the system optimization control model. The model formulates a global scheduling strategy based on the task execution capability, resource usage status, and coordination efficiency between nodes of each gateway node. This comprehensive scheduling strategy is distributed through the blockchain network to ensure that the tasks and resource allocation adjustments of all gateway nodes are synchronously executed in a distributed environment and generate optimized task scheduling data. The system uses the optimized task scheduling data to construct a distributed gateway collaboration network model. The model not only takes into account the resource sharing and task collaboration between gateway nodes, but also uses smart contracts to automatically manage the task allocation and adjustment of each node, ensuring that each node can dynamically adjust the task priority and resource allocation according to actual needs. The distributed collaboration network realizes decentralized management and efficient collaboration through blockchain technology, avoiding single point failure and network bottleneck problems. With the support of the distributed gateway collaboration network model, the system can coordinate the task execution of each gateway node, detect and adjust abnormal situations in task execution through real-time monitoring and smart contracts, and ensure the reliability of task execution. At the same time, the system dynamically optimizes the resource allocation and task scheduling of each node based on real-time monitoring data, and improves the overall processing capacity and scalability of the network. The system will generate dynamic optimization control data based on the distributed gateway collaborative network model. These data can optimize and control the gateway system in real time to ensure that the system can adapt to the dynamically changing network environment. For example, when the network load increases, the system will automatically adjust the task allocation and resource usage of each node according to the current resources and task execution status to ensure that the system can maintain a stable and efficient operation state under high load environment.

[0016] The present invention realizes efficient collaboration and decentralized management among gateway nodes through blockchain technology and distributed gateway collaborative network model. The decentralized characteristics of blockchain ensure the scalability of the system, without relying on a single node or central server, and can adapt to the access requirements of large-scale Internet of Things devices. Through the blockchain consensus mechanism and smart contracts, the task execution and resource allocation process of the gateway system can be verified, ensuring the accuracy of data and the safety of operation. Blockchain technology also improves the system's anti-attack and consistency of data synchronization, thereby improving the reliability of the entire Internet of Things system. Through real-time performance monitoring API and edge computing technology, the method can dynamically monitor the operating status of each gateway node and adjust the task priority and resource allocation strategy according to the actual situation of the node. In this way, the optimization of task scheduling is realized, the computing efficiency of the system is improved, and the waste of resources is reduced. Through distributed storage technology and data encryption processing, the method ensures the security of data storage and sharing in the gateway system. Using the blockchain network for data synchronization can ensure that the data is consistent among multiple nodes, avoid data loss or tampering, and improve the security and privacy protection of data. By using smart contracts to automatically manage the task allocation, resource adjustment and data storage of each gateway node, the system can dynamically adjust the task and resource configuration of each node in real time, reducing the need for manual intervention and realizing intelligent task scheduling and resource management. Through task execution history records, task monitoring, and real-time computing optimization based on node computing power, the system can timely perform performance analysis and adjust scheduling strategies, improving the overall system's operating efficiency and task processing capabilities. In summary, the IoT gateway and control method effectively improve the scalability, reliability and security of the IoT system, and optimize resource scheduling and task execution through smart contracts and blockchain technology. It can cope with complex IoT scenarios and ensure the stability and efficiency of the system in large-scale networks.

[0017] Preferably, step S1 comprises the following steps: Step S11: Acquire the initial state information of the IoT gateway node to obtain the gateway initial state data; Step S12: Connect each IoT gateway node to the blockchain network according to the gateway initial status data to obtain node connection status data; Step S13: Perform device identity authentication on each gateway node and the IoT device connected thereto using blockchain technology according to the node connection status data to obtain device identity authentication data; Step S14: Based on the device identity authentication data, the initial tasks and resources of each gateway node are dynamically allocated using smart contracts to generate initial resource allocation data.

[0018] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1Detailed step flow diagram of step S1 in the embodiment of the present invention, step S1 includes the following steps: Step S11: Acquire the initial state information of the IoT gateway node to obtain the gateway initial state data; When the embodiment of the present invention deploys the Internet of Things system, each Internet of Things gateway node will collect the initial state information of the gateway node through the built-in sensor, software monitoring module or network interface. The initial state information usually includes hardware status (such as the processor utilization of the gateway, memory and storage resource availability, power status, etc.), network status (such as the network connection status between the gateway and other devices, signal strength, transmission rate, delay, etc.) and software status (including the currently running operating system version, software environment, network protocol stack, application status, etc.). The initial state information collected by each Internet of Things gateway node will be transmitted to the system central control unit or the corresponding blockchain node through the network interface. These initial state data will be integrated and stored as reference benchmark data before the gateway node is connected to the blockchain network. The system generates the gateway initial state data based on the collected state information of each gateway node. The data contains a complete description of each gateway node, including its currently available hardware and software resources, network connection status, etc. The initial state data can also be stored in a standardized format (such as JSON, XML, etc.) for subsequent processing.

[0019] Step S12: Connect each IoT gateway node to the blockchain network according to the gateway initial status data to obtain node connection status data; In the embodiment of the present invention, the initial state data of the gateway has been acquired and generated in the IoT gateway node, and the data includes detailed information such as the hardware resources, network connection status, and software running status of the gateway node. At this time, the system will establish a connection strategy with the blockchain network for each gateway node based on these initial state data. The system selects an appropriate network channel based on the network status information (such as network bandwidth, delay, connection quality, etc.) and hardware status information of the gateway, and attempts to connect with the blockchain network node. The connection method can be achieved through a wired connection, a wireless connection, or a virtual private network (VPN) connection method. Each gateway node will establish a connection with multiple blockchain nodes to ensure the distributed transmission and reliability of data. After the connection is successfully established, the system will detect the connection status of each IoT gateway node in real time and generate node connection status data. This data includes the connection success (failure) status, connection stability, and node identity. If the connection fails, the system can try to connect again according to the network status of the gateway, or select a backup node connection path to ensure that the gateway node can reliably access the blockchain network. The node connection status data will be stored in the distributed ledger of the blockchain network to ensure that the connection information of each gateway node is securely and transparently recorded. The immutability of blockchain ensures the integrity and credibility of these connected data.

[0020] Step S13: Perform device identity authentication on each gateway node and the IoT device connected thereto using blockchain technology according to the node connection status data to obtain device identity authentication data; The embodiment of the present invention has generated node connection status data, which includes connection information between the IoT gateway node and the blockchain network, such as connection success status, node identification, connection quality, etc. This data provides a basis for device identity authentication. After accessing the blockchain network, each IoT gateway node initiates an identity authentication request for itself and the IoT device it is connected to. The identity authentication request is distributed through the blockchain network to ensure the execution of distributed authentication. The content of the verification includes the unique identifier (Node ID) of the gateway node, the MAC address or IMEI number of the device, and the public key of the device and other security information. The distributed ledger of the blockchain stores the identity information of all registered gateway nodes and IoT devices. The identity authentication request of the gateway node will be verified by multiple blockchain nodes. The verification process includes verifying the node identification, verifying the device information and tamper-proof verification. After the verification is completed, the blockchain node will generate device identity authentication data, including the verification pass status, verification timestamp and digital signature. The verification result is fed back to the IoT gateway node through the blockchain network and stored in the distributed ledger of the blockchain. The gateway node will perform subsequent operations such as resource allocation and task processing based on the device identity authentication data. If the verification fails, the system will notify the relevant gateway node to re-register or troubleshoot.

[0021] Step S14: Based on the device identity authentication data, the initial tasks and resources of each gateway node are dynamically allocated using smart contracts to generate initial resource allocation data.

[0022] The embodiment of the present invention has generated device identity authentication data, including identity information, verification status, and related security credentials (such as digital signatures and verification timestamps) of each gateway node and its access device. These data provide a basis for the dynamic allocation of resources and tasks. Prior to this, it is necessary to define the task and resource allocation rules in the smart contract. These rules include task priority, resource allocation criteria, and device roles. Write smart contract code, including resource allocation logic, task allocation rules, and execution conditions. Smart contracts can be written in Solidity or other smart contract languages ​​and deployed on the blockchain network. Deploy the written smart contract on the blockchain network. Smart contracts will be stored in the distributed ledger of the blockchain, and the consensus mechanism of the blockchain nodes will ensure that they are tamper-proof and transparent. Smart contracts perform tasks and resource allocation operations based on device identity authentication data. The contract will automatically check the authentication status of each device and allocate resources and tasks according to the defined rules. The smart contract calculates the amount of resources required for each gateway node and access device according to the predefined resource allocation rules, and generates corresponding resource allocation data. These data include computing resources, storage resources, network bandwidth, etc. allocated to each node. The smart contract allocates initial tasks to each gateway node based on task priority and resource availability. Task allocation data includes task type, execution order, task dependencies, etc. The initial resource allocation data is recorded in the distributed ledger of the blockchain so that all network nodes can access and verify it. These records include the timestamp and digital signature of the allocation results to ensure the integrity and immutability of the data. The resource allocation data and task allocation results are fed back to each gateway node through the blockchain network. The nodes will perform resource allocation and task preparation based on this data.

[0023] The present invention performs device identity authentication through blockchain technology to ensure that the identities of the Internet of Things gateway nodes and their access devices are authentic and secure. The immutability and decentralization characteristics of the blockchain effectively prevent the risks of device identity forgery and illegal access. During the identity authentication process, the identity information of all nodes is recorded in the blockchain, ensuring the transparency and security of the system. The tasks and resources of each gateway node are automatically and dynamically allocated through smart contracts, reducing manual intervention and improving the efficiency and accuracy of resource allocation. Smart contracts can quickly allocate computing resources, storage resources, bandwidth, etc. according to the real-time identity authentication data and node status of the device, ensuring efficient use of resources. The dynamic allocation mechanism enables the system to make adjustments according to actual needs and network status, avoiding waste of resources and imbalanced task allocation. Through the dynamic connection between nodes and the blockchain network, the system can flexibly adapt to the increase or decrease of gateway nodes and has high scalability. New nodes can join the network through identity authentication, which not only ensures the security of the system, but also realizes the elastic expansion of the system. Dynamic task and resource allocation based on real-time data enables the system to quickly respond to changes in Internet of Things devices, realize rapid deployment and execution of new tasks, and improve the adaptability of the entire system. The system realizes distributed collaborative computing among gateway nodes through blockchain and smart contracts. In the process of task allocation and resource allocation, not only the status of a single node is considered, but also the resource status of the entire network is combined to optimize the allocation and execution of tasks. This collaborative processing method can balance the load between nodes, avoid the problem of overload or insufficient resource utilization of individual nodes, and thus improve the processing efficiency and stability of the overall system. All node connection status data, device identity authentication data, resource and task allocation data are recorded through blockchain, realizing transparent data management. Any participant can view the operating status and allocation of the system through blockchain, ensuring the openness and traceability of operations. This method not only improves the trust of the system, but also provides a reliable data foundation for subsequent system monitoring, evaluation and optimization.

[0024] Preferably, step S11 includes the following steps: Step S111: monitor the hardware resource status in real time through the system resource monitoring tool and obtain the hardware information of each IoT gateway node to generate node hardware status data; The embodiment of the present invention uses hardware resource monitoring software deployed on the Internet of Things gateway node to monitor the status of key hardware resources including CPU, memory, storage, and power supply. The monitoring tool can collect data such as hardware usage, temperature, and power consumption in a regular sampling manner. The hardware resource monitoring software is responsible for reading real-time data from the hardware and sending it to the monitoring server or management platform by installing a lightweight agent program on each gateway node. The system monitors and records hardware parameters such as CPU usage, memory usage, disk IO, storage remaining capacity, and temperature of the gateway node at preset time intervals. When the hardware resource status is abnormal (such as CPU overload or insufficient storage space, etc.), the system will trigger an alarm mechanism, generate early warning data of the abnormal status, and report it to the control center in real time. By summarizing and analyzing the hardware monitoring data of each node, the system generates node hardware status data. These status data can reflect the hardware performance and health status of each gateway node at present. All acquired hardware status data will be regularly uploaded to the central control server or distributed data storage platform to facilitate subsequent system status analysis and resource optimization. These data are stored in an encrypted manner to ensure that they are not tampered with or leaked during transmission and storage.

[0025] Step S112: Using a traffic monitoring tool to record the network traffic, network performance and network connection status of each gateway node in real time, obtain the bandwidth usage, network delay and data transmission rate of each gateway node, and generate node network status data; The embodiment of the present invention uses an open source or commercial traffic monitoring tool to be deployed on each gateway node. The tool can capture and record network traffic, data packets and network connection status in real time. The traffic monitoring tool is tightly integrated with the network interface of each gateway node and can monitor all data traffic and network performance indicators entering and leaving the gateway node. The traffic monitoring tool continuously monitors the network traffic of the gateway node, records the data transmission volume per second, and classifies the inbound and outbound traffic (such as uplink / downlink traffic, application layer data flow, etc.). For abnormal traffic peaks or sudden traffic fluctuations, the system can issue an alarm through an alarm mechanism to prompt potential network bottlenecks or abnormal traffic attacks. The bandwidth usage of each gateway node is recorded in real time, including information such as the current bandwidth utilization rate and idle bandwidth. The system can also dynamically adjust task allocation and data transmission priority according to bandwidth usage to ensure that the gateway node maintains a stable connection under high load. The monitoring tool regularly tests network delay and measures the network response speed between nodes by sending ICMP packets to ensure that the delay is within an acceptable range. The system can also record the data transmission rate of each gateway node, monitor the difference between the actual transmission rate and the theoretical maximum bandwidth, and ensure that the network performance meets the expected requirements. When the delay is too high or the transmission rate is significantly reduced, the system can prompt network congestion or link abnormality. The traffic monitoring tool records the network connection status of each gateway node in real time. For gateway nodes that frequently disconnect and reconnect, the system can generate network connection abnormality logs to support further network troubleshooting. The system aggregates the above-mentioned monitored data to generate complete node network status data, including key information such as bandwidth utilization, network delay, data transmission rate and connection status. These data are transmitted to the central control server or blockchain system as a basis for subsequent optimization task allocation and resource management. All network status data is encrypted and transmitted to the distributed storage platform to ensure that the data is protected from tampering or attack during transmission and storage.

[0026] Step S113: Obtain the security status of each gateway node through a security monitoring tool to generate node security status data; The embodiment of the present invention monitors the security status of the node in real time and generates node security status data through the security monitoring tool deployed on each IoT gateway node. The security monitoring tool performs continuous intrusion detection (IDS) and firewall protection on each gateway node, identifies and records suspicious traffic, malicious attack behaviors, and unauthorized access attempts. Regularly scan the operating system and application software of the gateway node for vulnerabilities, identify possible security vulnerabilities and risks in the system, and record the vulnerability type and repair status. Authentication is performed on the IoT devices connected to the gateway to monitor whether there is unauthorized device access or device identity forgery, and the verification results are recorded. The security logs of each node are collected and analyzed in real time, sensitive behaviors such as login failures and privilege escalation operations are monitored, and relevant data are recorded. Through the above operations, the node security status data generated includes intrusion detection results, vulnerability scanning reports, identity authentication records, and security logs to ensure the security of each gateway node.

[0027] Step S114: using the IoT device management platform to collect device access information, detect and record information of IoT devices currently connected to each gateway node, and generate device access status data; The embodiment of the present invention collects the device information of each IoT gateway node in real time through the IoT device management platform, and generates device access status data. The IoT device management platform regularly scans the devices connected to each gateway node, automatically identifies the unique identifier of the device (such as MAC address, device ID, etc.), and records the type, brand and model of the device. The system continuously monitors the access status of the device, including the device connection time, the IP address of the current access gateway and the connection frequency of the device, and records the access and disconnection information. The platform also obtains the configuration data of each device, such as the device's firmware version, communication protocol and security settings, to ensure that the connected devices meet the system's specifications and security requirements. The device registration information, configuration status and real-time access status are integrated to generate device access status data for subsequent analysis and task allocation to ensure the effectiveness and security of IoT device access.

[0028] Step S115: Integrate the node hardware status data, node network status data, node security status data and device access status data to generate gateway initial status data.

[0029] The embodiment of the present invention aggregates and processes the data generated by multiple monitoring modules through a data integration tool. The system obtains the hardware status data, network status data, security status data and device access status data of the node respectively. Preprocessing is performed on various types of data, including removing outliers, unifying data formats and time synchronization, to ensure that data from different sources can consistently reflect the status of the node. Through the integration algorithm, the hardware, network, security and device access information are comprehensively analyzed to form a unified gateway initial status view and generate a report on the overall operation of the gateway. The analyzed data results are stored to generate gateway initial status data, which provides basic information for subsequent task allocation and system optimization, and can fully understand the status of each gateway node.

[0030] The present invention uses a system resource monitoring tool to obtain the hardware resource status, network traffic and security status of the Internet of Things gateway node in real time, so that the operating status of the gateway node can be fully perceived. This real-time monitoring improves the system's responsiveness to the node status, and can promptly discover potential problems and take measures. The network traffic and connection status of the gateway node are recorded by the traffic monitoring tool to ensure that the system can monitor network bandwidth usage, delay and data transmission rate. This function realizes the optimized management of network performance, improves the utilization efficiency of network resources, and ensures the normal connection and communication of Internet of Things devices. The security monitoring tool can monitor the security status of the gateway node in real time, ensure that the Internet of Things gateway can prevent potential attacks, and improve the overall security protection capability of the system. The device access information is collected in real time through the Internet of Things device management platform, so that the system can grasp the device status of each gateway node access, and ensure the access security and controllability of the device. By integrating different monitoring data, the initial state data of the gateway is generated. These data lay the foundation for subsequent task allocation and resource optimization, making the management of the gateway system more accurate and efficient, and improving the scalability and operation efficiency of the entire Internet of Things system. The all-round monitoring and data integration of the Internet of Things gateway nodes are effectively realized, and the stability, reliability and security of the gateway system are improved.

[0031] Preferably, step S2 comprises the following steps: Step S21: using IoT devices to collect raw data and pre-process the data to generate standardized data; Step S22: using the initial resource allocation data to locally process the standardized data according to the computing capacity of the node, and using a local storage device to temporarily store the local processing result to generate a local data processing result; Step S23: using the real-time performance monitoring API to collect real-time system operation status data of each gateway node to generate system operation status data; Step S24: Analyze the current load status of the node in real time according to the system operation status data, identify the overloaded nodes, and obtain the node load data; Step S25: Analyze the local data processing results and system operation status data using a greedy algorithm to obtain node resource usage data; Step S26: Dynamically adjust task priorities and resource allocation strategies based on node load data and node resource usage data to generate an optimized task allocation plan.

[0032] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S2 in the embodiment of the present invention, step S2 includes the following steps: Step S21: using IoT devices to collect raw data and pre-process the data to generate standardized data; The embodiment of the present invention collects raw data related to the environment, equipment operating status, etc. through various sensors and terminal devices. The data may include temperature, humidity, equipment working status, energy consumption, etc. Since the data formats and types of different devices may be inconsistent, the raw data needs to be preprocessed. Remove noise data and outliers to ensure reliable data quality. For example, filter out abnormal data points caused by sensor failures. Unify the format and standardize the data generated by different devices. For example, convert data with different data protocols and formats into a unified format for subsequent calculation and analysis. Normalize numerical data so that data in different ranges can be processed and analyzed at the same scale. Finally, standardized data that meets the processing requirements of the Internet of Things gateway is generated, providing a reliable data basis for subsequent local data processing and resource allocation. This process significantly improves data processing efficiency and ensures the stability and accuracy of the system.

[0033] Step S22: using the initial resource allocation data to locally process the standardized data according to the computing capacity of the node, and using a local storage device to temporarily store the local processing result to generate a local data processing result; The embodiment of the present invention uses the initial resource allocation data to perform local processing on the pre-processed standardized data based on the computing power of the IoT gateway node. According to the computing power of the node and the initial resource allocation data, an appropriate amount of tasks are assigned to each gateway node. Ensure that the computing load of the node is within its capability. Analyze and calculate the standardized data at the gateway node. The processed data is temporarily stored in the local storage device of the node, awaiting further processing or uploading to the central node. These local data processing results can be used for dynamic optimization and resource adjustment of subsequent systems. This implementation method improves the real-time and efficiency of the system in processing data by making full use of edge computing, while reducing network bandwidth occupancy and pressure on the central server.

[0034] Step S23: using the real-time performance monitoring API to collect real-time system operation status data of each gateway node to generate system operation status data; The embodiment of the present invention integrates a real-time performance monitoring API on each IoT gateway node, and the API is responsible for automatically collecting key performance indicators during system operation. The API monitors the hardware resource status of the node in real time, such as CPU temperature, operating frequency, disk I / O, etc., to ensure stable node operation; monitors the network connection status in real time, obtains indicators such as bandwidth utilization, network delay, packet loss rate, etc. to evaluate network load; monitors the tasks being executed on the node, obtains the execution time of each task, resource occupancy, and task processing progress and other information. The collected system operation status data is summarized and processed to generate system operation status data that can be used to analyze the current operation status of the node, which is used for load analysis and optimization in subsequent steps.

[0035] Step S24: Analyze the current load status of the node in real time according to the system operation status data, identify the overloaded nodes, and obtain the node load data; The embodiment of the present invention analyzes the resource usage of each gateway node through the system operation status data, especially the consumption of key resources such as CPU, memory, bandwidth and storage. These data are used to evaluate the current load status of each node. When the resource usage of certain nodes exceeds the preset threshold (such as high CPU occupancy, insufficient memory, etc.), the system marks it as an overloaded node. The system determines which nodes' computing or network resources face bottlenecks by dynamically monitoring the task execution and hardware performance of the nodes, thereby generating node load data. After the load data is generated, the system will immediately analyze it to ensure that rapid adjustment measures are taken on nodes with excessive load, such as reallocating tasks or adjusting resource usage, to avoid performance degradation or failure caused by node overload.

[0036] Step S25: Analyze the local data processing results and system operation status data using a greedy algorithm to obtain node resource usage data; The embodiment of the present invention collects local data processing results and system operation status data, including key information such as the real-time computing power of the node, network delay, bandwidth usage, etc. These data will be used as input for optimization calculations. The system uses a greedy algorithm to process the collected data. The greedy algorithm will gradually select the current local optimal resource allocation scheme to ensure that the computing resources and task load of the node are matched as efficiently as possible. The algorithm avoids resource waste and improves task processing efficiency by preferentially allocating resources to tasks with higher resource requirements or higher priorities. By analyzing the computing resource occupancy of the node, the system dynamically generates node resource usage data, which is used to judge in real time the matching degree of the node's resource consumption, processing power and current tasks.

[0037] Step S26: Dynamically adjust task priorities and resource allocation strategies based on node load data and node resource usage data to generate an optimized task allocation plan.

[0038] The embodiment of the present invention analyzes the current task execution status and resource utilization efficiency of each node based on node load data and node resource usage data. According to the load status of the node, the system adjusts the task priority in real time. For nodes with heavy loads, the system will reduce the priority of the node processing tasks, and assign some tasks to nodes with lighter loads to avoid performance degradation due to overload operation. For nodes with sufficient resources and light loads, high-priority tasks are given priority to improve the overall processing efficiency of the system. The system dynamically adjusts the resource allocation strategy according to the current state of the node. For example, increase computing resources or bandwidth allocated to nodes processing important tasks, or reduce resources allocated to low-priority tasks to ensure the optimal utilization of the entire gateway system resources. Through the above analysis, an optimized task allocation scheme is generated, so that the Internet of Things gateway can improve the stability and scalability of the system while ensuring efficient operation.

[0039] The present invention generates standardized data by using IoT devices to collect raw data and perform preprocessing, thereby ensuring the data quality and consistency of subsequent processing and laying a foundation for efficient data analysis. Dynamically adjust resource allocation according to the computing power of the node, so that standardized data can be efficiently processed locally, reduce the delay of data transmission, improve the response speed, and reduce the network load. Through the real-time performance monitoring API, the system can continuously monitor the operating status of each node. This real-time feedback mechanism enables the system to quickly identify the load status of the node and respond to potential performance bottlenecks in a timely manner. Through real-time analysis of the node load status, the system can identify nodes with heavy loads, thereby performing effective resource management. This intelligent load monitoring and analysis significantly improves the stability and reliability of the system. The greedy algorithm is used to analyze the local data processing results and system status, and the resource usage of each node is effectively identified. This process optimizes resource allocation, so that the system can achieve optimal performance under different load conditions. Based on the analysis of load data and resource usage data, the system can dynamically adjust task priorities and resource allocation strategies to generate optimized task allocation plans. This flexible resource management strategy enhances the scalability of the system and ensures efficient and stable operation. It significantly improves the performance, stability and resource utilization efficiency of the IoT gateway system, and provides strong support for efficient data processing in diverse application scenarios.

[0040] Preferably, step S3 comprises the following steps: Step S31: Distribute the tasks assigned to each gateway node using collaborative computing according to the optimized task allocation scheme, and record the task execution history of each gateway node using blockchain to obtain task execution history record data; Step S32: Monitor the task execution status of each gateway node in real time and dynamically generate real-time resource usage data; Step S33: Using blockchain to perform task execution history data and real-time resource usage data, obtain task allocation execution result data; Step S34: Evaluate the computing capability of the current node based on the task allocation execution result data, and generate real-time computing result data of each node; Step S35: Use the communication protocol to perform data sharing and task coordination among the gateway nodes to obtain a data storage sharing strategy.

[0041] As an embodiment of the present invention, refer to Figure 4 As shown, Figure 1 Detailed step flow diagram of step S3 in the embodiment of the present invention, step S3 includes the following steps: Step S31: Distribute the tasks assigned to each gateway node using collaborative computing according to the optimized task allocation scheme, and record the task execution history of each gateway node using blockchain to obtain task execution history record data; According to the optimized task allocation scheme, the system of the embodiment of the present invention performs collaborative calculations on the tasks assigned to each gateway node. The system uses a central scheduler to analyze the computing power and current load of each node to ensure the rationality and effectiveness of task allocation. Using a distributed processing architecture, each node executes its assigned tasks in parallel, reducing the time for task execution. During the task execution process, the system records the task execution history of each gateway node through blockchain technology. This process ensures the immutability and transparency of the data, making subsequent audits and analysis more reliable.

[0042] Step S32: Monitor the task execution status of each gateway node in real time and dynamically generate real-time resource usage data; The embodiment of the present invention continuously monitors the task execution status of each gateway node through a real-time performance monitoring API. The monitoring system dynamically aggregates these real-time data to generate real-time resource usage data. These data can be displayed in the form of charts or dashboards, which is convenient for operators to understand the operating status of each node at any time. In order to ensure the stability and efficiency of the system, the system also sets a threshold warning mechanism. When the resource usage of a node exceeds the set threshold, the system will automatically send an alarm to prompt the operation and maintenance personnel to intervene. This real-time monitoring and feedback mechanism can help quickly identify and solve potential performance bottlenecks, thereby optimizing the operating efficiency of the entire IoT gateway system.

[0043] Step S33: Using blockchain to perform task execution history data and real-time resource usage data, obtain task allocation execution result data; The embodiment of the present invention integrates the task execution history record data of each gateway node with the real-time resource usage data through blockchain technology. When each node executes a task, its execution status will be recorded in real time on the blockchain to ensure the immutability and transparency of the data. The system compares and analyzes these historical records with the dynamically generated resource usage data. By comparison, the system can evaluate the resource utilization efficiency of each node when performing a specific task, and identify nodes with excellent performance or resource waste. Combined with this data, the system generates task allocation execution result data, including the execution efficiency evaluation of each node, resource usage status, and possible improvement suggestions.

[0044] Step S34: Evaluate the computing capability of the current node based on the task allocation execution result data, and generate real-time computing result data of each node; The embodiment of the present invention evaluates the computing power of each gateway node based on the task allocation execution result data. These result data include key performance indicators such as resource usage, task completion time, error rate and success rate when the node performs a specific task. The system compares and analyzes these indicators with the historical execution data of the node to identify the computing power performance of each node. This process can use data mining technology to evaluate the performance of the node by setting thresholds and standardized indicators. The evaluation results will be classified into different performance levels, such as "efficient", "normal" or "needs improvement". These levels not only help determine the current status of each node, but also provide a basis for subsequent task scheduling and resource allocation. The system will generate real-time calculation result data from the evaluation results, which will be used to guide task allocation and resource optimization between nodes, ensure the improvement of the overall performance of the system, and enhance the adaptability of nodes under different load conditions.

[0045] Step S35: Use the communication protocol to perform data sharing and task coordination among the gateway nodes to obtain a data storage sharing strategy.

[0046] The embodiment of the present invention uses a communication protocol to establish a stable communication channel between each gateway node. In this way, each node can send and receive real-time data to ensure the rapid sharing and transmission of information. During the data sharing process, the node actively sends its current resource usage, task execution status and computing power evaluation results to other nodes based on the real-time calculation result data. The receiving node will analyze the execution requirements of its own tasks based on the received data, and cooperate with the sending node to optimize task allocation. For example, when the resource utilization rate of a node is high, the system may assign new tasks to nodes with lighter loads to balance the overall load. Based on this information, the system generates a data storage sharing strategy to clarify the data storage and access rules between nodes.

[0047] Through collaborative computing, the present invention enables each gateway node to process the assigned tasks at the same time, improves the overall data processing speed, reduces the burden of a single node, and realizes efficient use of resources. The blockchain technology is used to record the task execution history, ensure the immutability and transparency of the data, enhance the trust mechanism of the system, and ensure the compliance and traceability of task execution. The task execution status and resource usage of each node are monitored in real time, so that the system can be dynamically adjusted according to real-time data, effectively identify nodes with heavy loads, and timely optimize resource allocation to avoid system bottlenecks. Based on the task allocation execution result data, the system conducts a comprehensive evaluation of the computing power of each node, ensuring that each node operates under the most suitable conditions, and further improving the efficiency and accuracy of task execution. Through the communication protocol, each node can efficiently share data, realize task collaboration, and ensure the timely transmission and processing of information. This strategy enhances the system's collaborative ability and promotes the rational allocation and utilization of resources. The work efficiency, reliability and flexibility of the Internet of Things gateway are significantly improved, resource utilization and system performance are optimized, and strong support is provided for data processing and task execution in the Internet of Things environment.

[0048] Preferably, step S4 comprises the following steps: Step S41: Perform homomorphic encryption processing on the real-time calculation result data and divide the encrypted data into blocks to obtain encrypted data blocks; The embodiment of the present invention uses a homomorphic encryption algorithm to encrypt the real-time calculation result data, so that even if the data is intercepted during processing or storage, unauthorized users cannot interpret its content. The encrypted data is processed in blocks and split into multiple encrypted data blocks.

[0049] Step S42: selecting storage nodes using a distributed algorithm according to the real-time calculation result data and the real-time resource usage data to obtain a data storage allocation plan, wherein the storage node selection standard is to give priority to nodes with free storage space and sufficient network bandwidth for data storage; The embodiment of the present invention analyzes the real-time calculation result data and evaluates the current load, storage capacity and network bandwidth of each storage node. In order to optimize storage efficiency, the system gives priority to nodes with free storage space and sufficient network bandwidth for data storage. The system generates a list of candidate storage nodes and sorts them according to the availability and performance indicators of the nodes. Using a distributed algorithm, the most suitable node is selected from the candidate nodes for data storage. The generated data storage allocation plan will provide clear guidance for subsequent data synchronization and storage processes to ensure efficient and secure data storage.

[0050] Step S43: Based on the data storage allocation plan, the encrypted data blocks are synchronized and redundancy checked in real time using the blockchain network to obtain a data synchronization log; According to the data storage allocation plan, the system of the embodiment of the present invention first confirms the selected storage nodes and their corresponding encrypted data blocks. Using the blockchain network, the system synchronizes these encrypted data blocks in real time. Through the distributed characteristics of the blockchain, each storage node verifies the received data blocks in the network. The system records the storage location, timestamp and storage node information of each encrypted data block on the blockchain to form a data synchronization log. In addition, the system performs redundancy checks to ensure that each data block has a backup on multiple nodes to improve data availability and security.

[0051] Step S44: Monitor the usage of storage node resources in real time through the storage performance monitoring module, verify data integrity and security using smart contracts, and generate a distributed data storage optimization solution; The embodiment of the present invention monitors the resource usage of distributed storage nodes in real time through a storage performance monitoring module. The monitoring module collects parameters such as storage space usage, network bandwidth occupancy, and processing performance of each storage node to ensure that the node operates in the best state. At the same time, the system uses smart contracts to perform data integrity and security verification on the blockchain. Smart contracts automatically verify whether the encrypted data blocks stored on each node maintain integrity, that is, to ensure that the encrypted data blocks are not tampered with or lost during storage and transmission. Through the tamper-proof characteristics of the blockchain, all verification operations will be recorded on the chain to form an open and transparent verification record. When the monitoring module detects that some nodes are short of resources or have degraded performance, the system will generate a distributed data storage optimization plan based on these monitoring data. The optimization plan may involve reallocating storage resources, migrating data blocks to nodes with more sufficient resources, or dynamically adjusting storage strategies to improve the storage efficiency and security of the entire system.

[0052] Step S45: dynamically adjust the data storage sharing strategy according to the distributed data storage optimization solution to obtain a data storage sharing solution.

[0053] The embodiment of the present invention analyzes the real-time data provided by the storage performance monitoring module and evaluates the performance and resource usage of each storage node. The system will identify nodes with greater storage pressure and appropriately distribute their storage load to nodes with more sufficient resources. At the same time, the system will also consider factors such as network bandwidth and latency to ensure the efficiency and stability of data transmission. In this process, the dynamic adjustment strategy may include adding new nodes, redistributing data blocks, or modifying the storage priority of existing data. The adjusted data storage sharing scheme will be applied to the system in real time to ensure the reasonable distribution of data among nodes and optimize storage efficiency and data security. At the same time, the adjustment process and results of the scheme will be recorded on the blockchain for subsequent auditing and analysis to ensure the transparency and reliability of the system.

[0054] The homomorphic encryption processing of the present invention ensures the privacy and security of data during storage and prevents unauthorized access. Through data segmentation, the system improves the flexibility and storage efficiency of data processing. The distributed algorithm is used to select the optimal storage node to ensure the reliability and access efficiency of data storage. The process reduces storage latency and improves resource utilization by giving priority to nodes with free storage space and sufficient network bandwidth. Blockchain technology is used to achieve real-time synchronization and redundancy checking of encrypted data blocks, enhancing the integrity and traceability of data. This mechanism ensures that any abnormal situation in the storage process can be detected and corrected in a timely manner. By real-time monitoring of the resource usage of storage nodes and combining smart contracts, the integrity and security of data are further guaranteed. This dynamic monitoring provides a data basis for storage optimization, making the storage solution more efficient. The storage strategy is dynamically adjusted according to the optimization solution to ensure the reasonable allocation and sharing of data among the storage nodes, and improve the overall performance and flexibility of the storage system. It not only improves the security and efficiency of data storage in the Internet of Things environment, but also realizes the optimal configuration and dynamic management of resources, which meets the needs of modern Internet of Things applications.

[0055] Preferably, step S44 includes the following steps: Step S441: using the storage performance monitoring module to monitor the resource usage of each storage node in real time and generate storage performance data; The embodiment of the present invention deploys a storage performance monitoring module that can track the resource usage of each storage node in real time. The monitoring module regularly collects and summarizes the performance data of each storage node and generates a corresponding storage performance data report. In addition, the monitoring module also sets a threshold so that an alarm can be triggered in time when the resource usage of the storage node exceeds the preset range. The collected storage performance data will serve as an important basis for subsequent optimization plans, helping the system to formulate a more reasonable distributed data storage strategy to improve the overall efficiency and reliability of data storage and access.

[0056] Step S442: Based on the data synchronization log, the integrity and security of the stored data are verified using the smart contract to obtain a data security verification result; The embodiment of the present invention extracts the relevant records of the storage node during the data synchronization process based on the data synchronization log. The extracted synchronization log is analyzed by using the smart contract to verify the integrity and security of the data. The smart contract will automatically execute the preset verification rules, including checking whether the hash value of the data block matches, confirming whether all expected data blocks have been successfully stored, and detecting whether there are any unauthorized access attempts. During the verification process, if the integrity of the data block is threatened or a security issue is found, the smart contract will generate a corresponding alarm, notify the system administrator, and record the event for subsequent auditing. The execution result of the smart contract will be recorded as a data security verification result, providing a detailed report on the security of the stored data.

[0057] Step S443: Generate a distributed data storage optimization solution based on the storage performance data and data security verification results.

[0058] The embodiment of the present invention aggregates storage performance data, and at the same time, data security verification results are also taken into consideration, which indicate the integrity and security status of the stored data. The storage performance data and security verification results are comprehensively evaluated using an analysis algorithm. The system determines the load of each storage node based on the performance data, identifies performance bottlenecks, and determines which nodes may need to adjust resource allocation. In addition, the security verification results will help identify storage nodes that perform poorly in terms of security. Based on the above analysis, the system generates a distributed data storage optimization solution.

[0059] The present invention realizes real-time monitoring of resource usage of each storage node through a storage performance monitoring module, and the generated storage performance data provides a basis for subsequent analysis. This real-time performance ensures that the system can respond quickly to potential resource bottlenecks, thereby avoiding system performance degradation. The integrity and security of the stored data are verified by smart contracts to ensure the security of the data during storage and transmission. This measure can effectively prevent data tampering and loss, and improve the reliability of the system. Comprehensive storage performance data and data security verification results are used to generate a distributed data storage optimization plan. This plan can propose scientific adjustment measures for current storage resources and security conditions, such as optimizing data allocation, increasing redundant storage, etc., to ensure the efficient operation of the system. Through real-time monitoring, data verification and generation of optimization plans, intelligent management of distributed data storage is achieved, which greatly improves the performance and security of the system, and enables the Internet of Things gateway to process large amounts of data more effectively.

[0060] Preferably, step S5 comprises the following steps: Step S51: monitor the task execution effect of each gateway node in real time, collect key performance indicators of each gateway node during the task execution process, and generate task execution monitoring results; The embodiment of the present invention records the performance data of each node in the process of executing tasks in real time through the monitoring module installed on each gateway node. The monitoring module aggregates the real-time data and sends it to the central control system for analysis and processing. The system standardizes the collected performance indicators to ensure the consistency and comparability of the data. The generated task execution monitoring results will form a dynamically updated performance baseline to provide data support for subsequent resource allocation and task scheduling.

[0061] Step S52: monitoring the data storage status of each gateway node based on the data storage sharing solution to obtain storage monitoring data; The monitoring module of the embodiment of the present invention will regularly collect key indicators such as the storage capacity, used storage space, available storage space and storage utilization rate of each node, and these data will be sent to the central control system through the monitoring interface. The monitoring module will also track the read and write speed and delay time of the stored data to evaluate the storage performance. In addition, the system will also monitor the data backup status and redundancy to ensure the security and reliability of the data. By analyzing the collected storage monitoring data in real time, the system can identify storage bottlenecks or potential storage problems. This information will be used to optimize subsequent data storage strategies to ensure the efficient operation of each node in terms of data storage. The generated storage monitoring data will be combined with other monitoring results to provide basic data support for consensus verification and resource allocation adjustment.

[0062] Step S53: Using the blockchain consensus mechanism to verify the task execution monitoring results and generate a consensus verification result; The embodiment of the present invention packages the task execution monitoring results into transaction data and submits them to the blockchain network. The nodes in the network verify the submitted data through a consensus algorithm. During the verification process, each node will compare the monitoring results with each other to ensure that the results of all nodes are consistent to prevent data tampering or fraud. Once a consensus is reached, the system will generate a consensus verification result and record it in the blockchain for subsequent auditing and tracking. The generated consensus verification result will be used as an important basis for dynamically adjusting resource allocation and task scheduling strategies.

[0063] Step S54: dynamically adjust the resource allocation and task scheduling strategy of the gateway system according to the consensus verification result, and update it to the smart contract to generate a resource allocation adjustment plan; The embodiment of the present invention analyzes the consensus verification results to evaluate the performance of each gateway node in task execution. Combined with the task execution monitoring results, nodes with insufficient or overloaded resources are identified. By analyzing these data, the system can determine whether it is necessary to adjust the task allocation, priority or resource allocation strategy of each node. Once the adjustment plan is determined, the system will automatically update the resource allocation and task scheduling strategy through the smart contract mechanism to ensure that these adjustments can take effect in real time. The smart contract will record all changes for subsequent auditing and tracking. The generated resource allocation adjustment plan will provide the system with greater flexibility and efficiency, ensuring that each gateway node can effectively respond to different load requirements in a changing environment.

[0064] Step S55: Generate a system optimization control model based on the task execution monitoring results, consensus verification results, and resource allocation adjustment plan.

[0065] The embodiment of the present invention analyzes the task execution monitoring results and evaluates the performance of each gateway node in the process of executing the task. The system combines the consensus verification results to confirm which nodes perform well in task execution and which nodes have problems. By comparing the monitoring results and the consensus verification results, the system can identify the shortcomings of the current resource allocation and task scheduling strategies. Based on the resource allocation adjustment plan, the system formulates specific parameters and strategies for the optimization control model, including the reordering of task priorities and the reallocation of resources. The generated system optimization control model will be used for real-time monitoring and adjustment.

[0066] The present invention ensures that the system has a comprehensive understanding of task execution efficiency and resource utilization, and helps to identify potential performance bottlenecks and storage problems. Through the blockchain consensus mechanism, the task execution monitoring results are verified to ensure the reliability and consistency of the data. This process increases the security and trust of the system, ensures the authenticity of the node execution results, and provides a reliable data basis for subsequent decision-making. The system is more efficient and flexible in resource utilization, and can optimize task scheduling and resource allocation according to actual operating conditions to improve the overall performance of the system. The system optimization control model improves the system's adaptive ability, ensures balanced and efficient operation under different task loads, and ensures that the system can continuously optimize resource usage in future task scheduling, improve stability and task execution efficiency. It reflects that through intelligent and distributed task monitoring, data verification, and resource adjustment mechanisms, the Internet of Things gateway system can achieve efficient and secure task execution and resource management.

[0067] Preferably, step S6 comprises the following steps: Step S61: Perform performance analysis on the task allocation execution result data and the gateway initial state data according to the system optimization control model to generate comprehensive evaluation data of the gateway node task execution; The embodiment of the present invention extracts the task allocation execution result data of each gateway node according to the system optimization control model. At the same time, the system also collects the initial state data of the gateway, covering the hardware configuration, available resources and current network status of the node. The system performs performance analysis on these data, mainly by comparing the task execution efficiency, resource occupancy rate and task processing capacity of different nodes, and calculates the comprehensive evaluation data of task execution of each node. By using the optimization control model, the system can automatically identify the bottlenecks and deficiencies in resource allocation during task execution, and objectively evaluate the actual performance of each node.

[0068] Step S62: Analyze the computing power, resource utilization and task execution history data of each gateway node according to the comprehensive evaluation data to generate performance indicator data; The embodiment of the present invention obtains the computing power, resource utilization and historical record data of task execution of each gateway node from the comprehensive evaluation data. Through these data, the system can fully understand the operating status and historical performance of each gateway node. The system will evaluate the current computing power of each gateway node based on the computing resource usage of each gateway node. At the same time, the efficiency of each node in resource utilization is analyzed. Combined with the task execution history records, the system can identify the strengths and weaknesses of each node in previous tasks. The generated performance indicator data lays the foundation for the subsequent definition of task priority and the design of resource allocation rules.

[0069] Step S63: defining the task priority and resource allocation rules of each gateway node based on the performance indicator data and the task execution history record data, and generating node task execution rules; The embodiment of the present invention extracts key information such as the computing power and resource utilization of each node from the performance indicator data. At the same time, combined with the task execution history of each node, the execution effect of each node in past tasks is evaluated, including task completion speed, resource consumption efficiency, etc. The system will assign appropriate task priorities to each gateway node based on these data, that is, give priority to nodes with strong computing power, sufficient resources and good historical performance in the gateway collaboration network. Based on the priority and resource utilization efficiency of the node, the system formulates specific resource allocation rules to ensure that resources can be efficiently allocated to the most suitable nodes.

[0070] Step S64: Using the blockchain consensus mechanism to verify the node task execution rules and generate verification result data; The embodiment of the present invention verifies the rationality and consistency of the task execution rules through the collaboration of each participating node in the blockchain network. Each node reviews the task allocation rules to confirm that they are consistent with the node's computing power, resource utilization, and historical task execution. The decentralized characteristics of the consensus mechanism ensure the security and tamper resistance of the verification process. After the verification is completed, the system will generate verification result data as the basis for passing or modifying the rules.

[0071] Step S65: constructing a distributed gateway collaboration network model according to the verification result data; The embodiment of the present invention determines the collaborative relationship between different gateway nodes based on the task execution rules and consensus verification results of each gateway node. Based on these relationships, the system establishes a distributed gateway collaborative network model, which optimizes the task allocation and resource sharing of each node in a decentralized manner. In the process of building the model, the system will comprehensively consider factors such as the computing power, resource utilization, and task priority of each gateway node to ensure that the role and task load of each node in the entire collaborative network are reasonably distributed. At the same time, blockchain technology ensures the security and reliability of the model to prevent data tampering or improper behavior of nodes.

[0072] Step S66: Optimizing the task scheduling strategy by using the system optimization control model and the distributed gateway cooperation network model to generate an optimized task scheduling solution; The embodiment of the present invention utilizes a distributed gateway collaborative network model to evaluate the task execution, resource occupancy, and network status of each gateway node. Combined with the historical data on task execution, resource allocation scheme, and current performance of the node in the system optimization control model, the system will analyze whether the existing task scheduling strategy is effective. Based on the above analysis results, the system will optimize the bottlenecks and deficiencies in task scheduling and generate an optimized task scheduling scheme. This scheme ensures that the distribution of tasks in the network is more balanced and efficient, reduces delays, and improves resource utilization by considering multiple factors such as the computing power of each node, task load balancing, and communication efficiency between nodes.

[0073] Step S67: Based on the distributed gateway cooperative network model, the system is dynamically optimized and controlled using an optimized task scheduling solution to generate dynamic optimization control data to improve the scalability and reliability of the overall gateway system.

[0074] The embodiment of the present invention continuously monitors the resource usage, task execution status and network conditions of each gateway node based on the optimized task scheduling scheme. On this basis, the system uses a distributed gateway collaborative network model to adjust the task execution rules of the gateway node to ensure that the task allocation matches the node resource status. The system dynamically adjusts the allocation and execution order of tasks based on the performance data collected during actual operation and the communication efficiency between nodes to ensure the load balancing of task processing between gateway nodes. At the same time, smart contracts and blockchain consensus mechanisms will also verify the transmission and storage security of data between nodes in real time to ensure the integrity and reliability of the data. Based on these dynamic adjustments, the system generates dynamic optimization control data.

[0075] The present invention performs performance analysis on the task allocation execution results and the initial state data of the gateway, and generates comprehensive evaluation data. This enables the system to have an in-depth understanding of the task execution performance of each gateway node, and provides basic data for subsequent optimization. The distributed gateway collaboration network model ensures that the task collaboration rules between gateway nodes are transparent and secure. The system uses the optimization control model and the distributed gateway collaboration network model to optimize the task scheduling strategy and generate an optimized task scheduling scheme. Through this scheme, the system can allocate tasks more intelligently and ensure efficient use of resources. The system performs dynamic optimization control based on the optimized task scheduling scheme and the distributed gateway collaboration network model. This not only improves the task collaboration efficiency between nodes, but also further enhances the scalability and reliability of the system, so that the entire Internet of Things gateway system can flexibly respond to various challenges in a dynamic environment and achieve more efficient resource allocation and task processing.

[0076] Preferably, the present invention further provides an Internet of Things gateway, which is used to execute the control method of the Internet of Things gateway as described above, and the Internet of Things gateway comprises: The status and identity authentication module is used to obtain the initial status information of the IoT gateway node and obtain the initial status data of the gateway; connect each gateway node to the blockchain network according to the initial status data of the gateway, perform device identity authentication on each gateway node and access device through blockchain technology, and use smart contracts to allocate initial tasks and resources to each gateway node to generate initial resource allocation data; The data processing and monitoring module is used to perform local data processing on the gateway node through edge computing according to the initial resource allocation data, and generate local data processing results; use the real-time performance monitoring API to monitor the system operation status of each gateway node in real time to obtain system operation status data; based on the local data processing results and system operation status data, dynamically adjust the task priority and resource allocation strategy, and generate an optimized task allocation plan; The collaborative computing and recording module is used to perform collaborative computing and distributed task processing on each gateway node according to the optimized task allocation plan, and use the blockchain to record the task execution history and resource usage of each gateway node to obtain the task allocation execution result data; based on the task allocation execution result data, real-time computing results are generated based on the real-time computing capability of the node to obtain real-time computing result data; data sharing and task collaboration are performed on each gateway node to obtain a data storage sharing strategy; The distributed storage management module is used to encrypt and store data through distributed storage technology based on real-time calculation results, synchronize data between nodes through the blockchain network, and generate a distributed data storage optimization plan; according to the distributed data storage optimization plan, the data storage sharing strategy is dynamically adjusted using smart contracts to obtain a data storage sharing plan; The task monitoring and verification module is used to monitor and evaluate the task execution effect of each gateway node according to the data storage sharing solution, and generate task execution monitoring results; based on the task execution monitoring results, the blockchain consensus mechanism is used to verify the task execution status, and resources and tasks are dynamically adjusted according to the verification results to generate a system optimization control model; The optimization control and scheduling module is used to comprehensively schedule the task execution and resource allocation of the IoT gateway system according to the system optimization control model, and to build a distributed gateway collaboration network model; through the distributed gateway collaboration network model, the tasks of each gateway node are coordinated and dynamically optimized and controlled, and dynamic optimization control data is generated to improve the scalability and reliability of the gateway system.

[0077] The present invention realizes the secure connection between the gateway node and the blockchain, ensures the accurate verification of the device identity, reasonably allocates the initial resources and tasks, and enhances the security and initial configuration efficiency of the system. The local data processing capability is improved through edge computing, the system operation status is monitored in real time, the task priority and resource allocation are dynamically optimized, and the real-time response capability and resource utilization efficiency of the gateway are improved. The collaborative computing and distributed task processing between gateway nodes are supported, and the task history and resource usage are recorded by blockchain to realize real-time computing and data sharing, and improve the collaboration efficiency and task management capability. Through distributed storage and blockchain synchronization mechanism, the encrypted storage and secure sharing of data are ensured, the storage strategy is dynamically adjusted, the data storage and synchronization performance are optimized, and the data security and storage efficiency are improved. The task execution effect of each gateway node is monitored in real time, the task execution is verified by the blockchain consensus mechanism, and the resource allocation and task scheduling are dynamically adjusted to improve the reliability of task execution and the flexibility of the system. Based on the optimization control model to schedule system tasks and resources, a distributed gateway collaboration network is constructed, and the scalability, stability and resource management efficiency of the system are improved through dynamic optimization control.

Claims

1. A control method for an Internet of Things gateway, characterized in that: The following steps are involved: Step S1: Obtain the initial state information of the IoT gateway node to obtain the gateway initial state data; Connect each gateway node to the blockchain network based on the initial state data of the gateway, perform device identity authentication on each gateway node and access device through blockchain technology, and use smart contracts to allocate initial tasks and resources to each gateway node to generate initial resource allocation data; Step S2: Perform local data processing on the gateway node through edge computing according to the initial resource allocation data to generate local data processing results; Use the real-time performance monitoring API to monitor the system operation status of each gateway node in real time and obtain system operation status data; based on local data processing results and system operation status data, dynamically adjust task priorities and resource allocation strategies to generate optimized task allocation plans; Step S3: Perform collaborative computing and distributed task processing on each gateway node according to the optimized task allocation scheme, and use blockchain to record the task execution history and resource usage of each gateway node to obtain task allocation execution result data; Generate real-time computing results based on the real-time computing capability of the nodes according to the task allocation execution result data to obtain real-time computing result data; Perform data sharing and task coordination on each gateway node to obtain a data storage sharing strategy; Step S4: Encrypt and store the data using distributed storage technology based on the real-time calculation result data, and synchronize the data between nodes through the blockchain network to generate a distributed data storage optimization plan; dynamically adjust the data storage sharing strategy using smart contracts based on the distributed data storage optimization plan to obtain a data storage sharing plan; Step S5: Monitor and evaluate the task execution effect of each gateway node according to the data storage sharing scheme, and generate task execution monitoring results; verify the task execution status using the blockchain consensus mechanism according to the task execution monitoring results, and dynamically adjust resources and tasks according to the verification results to generate a system optimization control model; Step S6: Comprehensively schedule the task execution and resource allocation of the IoT gateway system according to the system optimization control model, and build a distributed gateway collaboration network model; coordinate tasks and dynamically optimize the control of each gateway node through the distributed gateway collaboration network model, and generate dynamic optimization control data to improve the scalability and reliability of the gateway system.

2. The control method of the Internet of Things gateway according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: Acquire the initial state information of the IoT gateway node to obtain the gateway initial state data; Step S12: Connect each IoT gateway node to the blockchain network according to the gateway initial status data to obtain node connection status data; Step S13: Perform device identity authentication on each gateway node and the IoT device connected thereto using blockchain technology according to the node connection status data to obtain device identity authentication data; Step S14: Based on the device identity authentication data, the initial tasks and resources of each gateway node are dynamically allocated using smart contracts to generate initial resource allocation data.

3. The control method of the Internet of Things gateway according to claim 2, characterized in that: Step S11 includes the following steps: Step S111: monitor the hardware resource status in real time through the system resource monitoring tool and obtain the hardware information of each IoT gateway node to generate node hardware status data; Step S112: Using a traffic monitoring tool to record the network traffic, network performance and network connection status of each gateway node in real time, obtain the bandwidth usage, network delay and data transmission rate of each gateway node, and generate node network status data; Step S113: Obtain the security status of each gateway node through a security monitoring tool to generate node security status data; Step S114: using the IoT device management platform to collect device access information, detect and record information of IoT devices currently connected to each gateway node, and generate device access status data; Step S115: Integrate the node hardware status data, node network status data, node security status data and device access status data to generate gateway initial status data.

4. The control method of the Internet of Things gateway according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: using IoT devices to collect raw data and pre-process the data to generate standardized data; Step S22: using the initial resource allocation data to locally process the standardized data according to the computing capacity of the node, and using a local storage device to temporarily store the local processing result to generate a local data processing result; Step S23: using the real-time performance monitoring API to collect real-time system operation status data of each gateway node to generate system operation status data; Step S24: Analyze the current load status of the node in real time according to the system operation status data, identify the overloaded nodes, and obtain the node load data; Step S25: Analyze the local data processing results and system operation status data using a greedy algorithm to obtain node resource usage data; Step S26: Dynamically adjust task priorities and resource allocation strategies based on node load data and node resource usage data to generate an optimized task allocation plan.

5. The control method of the Internet of Things gateway according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: Distribute the tasks assigned to each gateway node using collaborative computing according to the optimized task allocation scheme, and record the task execution history of each gateway node using blockchain to obtain task execution history record data; Step S32: Monitor the task execution status of each gateway node in real time and dynamically generate real-time resource usage data; Step S33: Using blockchain to perform task execution history data and real-time resource usage data, obtain task allocation execution result data; Step S34: Evaluate the computing capability of the current node based on the task allocation execution result data, and generate real-time computing result data of each node; Step S35: Use the communication protocol to perform data sharing and task coordination among the gateway nodes to obtain a data storage sharing strategy.

6. The control method of the Internet of Things gateway according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: Perform homomorphic encryption processing on the real-time calculation result data and divide the encrypted data into blocks to obtain encrypted data blocks; Step S42: selecting storage nodes using a distributed algorithm according to the real-time calculation result data and the real-time resource usage data to obtain a data storage allocation plan, wherein the storage node selection standard is to give priority to nodes with free storage space and sufficient network bandwidth for data storage; Step S43: Based on the data storage allocation plan, the encrypted data blocks are synchronized and redundancy checked in real time using the blockchain network to obtain a data synchronization log; Step S44: Monitor the usage of storage node resources in real time through the storage performance monitoring module, verify data integrity and security using smart contracts, and generate a distributed data storage optimization solution; Step S45: dynamically adjust the data storage sharing strategy according to the distributed data storage optimization solution to obtain a data storage sharing solution.

7. The control method of the Internet of Things gateway according to claim 6, characterized in that: Step S44 includes the following steps: Step S441: using the storage performance monitoring module to monitor the resource usage of each storage node in real time and generate storage performance data; Step S442: Based on the data synchronization log, the integrity and security of the stored data are verified using the smart contract to obtain a data security verification result; Step S443: Generate a distributed data storage optimization solution based on the storage performance data and data security verification results.

8. The control method of the Internet of Things gateway according to claim 1, characterized in that: Step S5 includes the following steps: Step S51: monitor the task execution effect of each gateway node in real time, collect key performance indicators of each gateway node during the task execution process, and generate task execution monitoring results; Step S52: monitoring the data storage status of each gateway node based on the data storage sharing solution to obtain storage monitoring data; Step S53: Using the blockchain consensus mechanism to verify the task execution monitoring results and generate a consensus verification result; Step S54: dynamically adjust the resource allocation and task scheduling strategy of the gateway system according to the consensus verification result, and update it to the smart contract to generate a resource allocation adjustment plan; Step S55: Generate a system optimization control model based on the task execution monitoring results, consensus verification results, and resource allocation adjustment plan.

9. The control method of the Internet of Things gateway according to claim 1, characterized in that: Step S6 includes the following steps: Step S61: Perform performance analysis on the task allocation execution result data and the gateway initial state data according to the system optimization control model to generate comprehensive evaluation data of the gateway node task execution; Step S62: Analyze the computing power, resource utilization and task execution history data of each gateway node according to the comprehensive evaluation data to generate performance indicator data; Step S63: defining the task priority and resource allocation rules of each gateway node based on the performance indicator data and the task execution history record data, and generating node task execution rules; Step S64: Using the blockchain consensus mechanism to verify the node task execution rules and generate verification result data; Step S65: constructing a distributed gateway collaboration network model according to the verification result data; Step S66: Optimizing the task scheduling strategy by using the system optimization control model and the distributed gateway cooperation network model to generate an optimized task scheduling solution; Step S67: Based on the distributed gateway cooperative network model, the system is dynamically optimized and controlled using an optimized task scheduling solution to generate dynamic optimization control data to improve the scalability and reliability of the overall gateway system.

10. An Internet of Things gateway, characterized in that: Used to execute the control method of the Internet of Things gateway according to claim 1, the Internet of Things gateway comprising: The status and identity authentication module is used to obtain the initial status information of the IoT gateway node and obtain the initial status data of the gateway; connect each gateway node to the blockchain network according to the initial status data of the gateway, perform device identity authentication on each gateway node and access device through blockchain technology, and use smart contracts to allocate initial tasks and resources to each gateway node to generate initial resource allocation data; The data processing and monitoring module is used to perform local data processing on the gateway node through edge computing according to the initial resource allocation data, and generate local data processing results; use the real-time performance monitoring API to monitor the system operation status of each gateway node in real time to obtain system operation status data; based on the local data processing results and system operation status data, dynamically adjust the task priority and resource allocation strategy, and generate an optimized task allocation plan; The collaborative computing and recording module is used to perform collaborative computing and distributed task processing on each gateway node according to the optimized task allocation plan, and use the blockchain to record the task execution history and resource usage of each gateway node to obtain the task allocation execution result data; based on the task allocation execution result data, real-time computing results are generated based on the real-time computing capability of the node to obtain real-time computing result data; data sharing and task collaboration are performed on each gateway node to obtain a data storage sharing strategy; The distributed storage management module is used to encrypt and store data through distributed storage technology based on real-time calculation results, synchronize data between nodes through the blockchain network, and generate a distributed data storage optimization plan; according to the distributed data storage optimization plan, the data storage sharing strategy is dynamically adjusted using smart contracts to obtain a data storage sharing plan; The task monitoring and verification module is used to monitor and evaluate the task execution effect of each gateway node according to the data storage sharing solution, and generate task execution monitoring results; based on the task execution monitoring results, the blockchain consensus mechanism is used to verify the task execution status, and resources and tasks are dynamically adjusted according to the verification results to generate a system optimization control model; The optimization control and scheduling module is used to comprehensively schedule the task execution and resource allocation of the IoT gateway system according to the system optimization control model, and to build a distributed gateway collaboration network model; through the distributed gateway collaboration network model, the tasks of each gateway node are coordinated and dynamically optimized and controlled, and dynamic optimization control data is generated to improve the scalability and reliability of the gateway system.

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