320 results about "Consensus algorithm" patented technology

The invention discloses a digital production plan scheduling method and system, and belongs to the technical field of optimal scheduling, and the method comprises the steps: constructing a distributed storage architecture based on edge computing nodes; a central coordinator is adopted to realize cross-node data synchronization through an improved Raft consensus algorithm, multi-version concurrency control is realized based on a vector clock, and a global consistent data view is established; a visual scheduling platform is built based on a Vue3 framework, and man-machine interaction is realized by adopting a Canvas and WebGL collaborative rendering framework; establishing a dynamic coordinate conversion model based on bilinear interpolation, designing a space mapping function containing distortion compensation, establishing a multi-thread coordinate service based on WebWorker, and realizing submillimeter-level bidirectional mapping of pixel coordinates and physical coordinates; constructing a three-dimensional space-time analysis model fused with the multi-dimensional features; and all the units are subjected to feature fusion through residual connection, and finally a scheduling scheme with a confidence coefficient weight is output. The method and the device have the effect of meeting various scheduling requirements.

The invention relates to the technical field of unmanned aerial vehicle cluster control, and particularly discloses an intelligent cooperative flight path planning method and system for an unmanned aerial vehicle cluster system, and the method comprises the steps: firstly constructing a dynamic environment perception model, collecting data through all unmanned aerial vehicle sensors, and carrying out the preprocessing, attention feature extraction and federal learning fusion, and generating a global environment situation map; planning and screening a candidate track set by adopting a particle swarm-genetic hybrid optimization algorithm for adaptive weight adjustment on the basis of the image; a global optimal track consensus is achieved through an improved consensus algorithm and conflict resolution through a distributed collaborative negotiation mechanism and no human-computer interaction evaluation indexes; and finally, monitoring the environment in real time during execution, triggering dynamic re-planning when the environment is abnormal, and ensuring track adaptation through multi-level threshold and incremental planning. According to the method, the unmanned aerial vehicle cluster can quickly respond to the environment change and adjust the flight path, so that the task execution efficiency and success rate of the unmanned aerial vehicle cluster in the complex dynamic environment are improved.

The invention discloses a goaf unmanned aerial vehicle inspection system based on monitoring and early warning, and the system comprises an observation data collection module which is used for collecting settlement and fracture main variables to form a time stamp observation set; the data fusion module is used for generating a unified monitoring data set by adopting a fractal small-world network coding consensus algorithm; the initial route planning module is used for constructing a route sequence based on a main variable evolution tensor and a risk map; the flight path execution module is used for collecting a flight path and environment data; the fault-tolerant control module triggers a fractional order sliding mode fault-tolerant and degradation mechanism based on the consistency error; and the closed-loop optimization module is used for dynamically updating the main variable tensor and the path cost function and outputting an optimized track and a structured early warning result. The system has high dynamic responsiveness and multi-source risk adaptability.

The present invention relates to the technical field of communication anti-interference, and relates to an interference confrontation method, system, device and medium for a wireless communication network, the method comprising: obtaining spectrum data, the spectrum data comprising spectrum data deployed and collected by a wireless network according to an initial deployment scheme; performing feature extraction and fusion processing on the spectrum data to generate a spectrum situation map; performing reinforcement learning decision processing according to the frequency spectrum situation map to generate a dynamic anti-interference strategy; according to transmitting node combination parameters in the dynamic anti-interference strategy, a collaborative bait node group is obtained through distributed consensus algorithm processing; sending a virtual signal to an interference source according to the dynamic anti-interference strategy and the collaborative bait node group; and calculating the strategy effect of the virtual signal by using a reinforcement learning reward function to obtain an optimized anti-interference strategy, thereby breaking through the limitation of insufficient static coping and cooperation of a traditional anti-interference method, and realizing communication reliability and anti-interference adaptability in a complex dynamic interference environment.

The invention relates to a carbon emission checking system and method based on a block chain, and the system comprises a basic resource layer which collects enterprise energy consumption data in real time, employs cloud computing resources to provide data storage and computing capability, and employs a Hash algorithm to process the enterprise energy consumption data, and obtains a data abstract; the block chain network layer carries out distributed storage through an alliance chain architecture, carries out consensus evidence storage on the data abstract by adopting a PBFT consensus algorithm, and generates an encrypted data abstract; the intelligent contract layer receives the encrypted data abstract transmitted by the block chain network layer, and executes verification, calculation and supervision rules; and the application service layer calls the processing result of the intelligent contract layer, and respectively provides an enterprise carbon checking terminal service interface, an institution carbon checking terminal service interface and a competent department carbon supervision terminal service interface for the enterprise, a third-party checking institution and the competent department to check the carbon emission. According to the invention, high-efficiency check, high-credibility verification and whole-process traceable supervision of the carbon emission data are realized.

The invention discloses a dynamic security authentication method for cross-platform information system integration, and relates to the technical field of cross-platform dynamic authentication. A non-tampering identity trust chain is established through a block chain consensus algorithm, the problems of single-point fault and expansibility of centralized identity management are solved, cross-platform unified identity verification is realized, the problem that multi-factor authentication lacks intelligent risk assessment is solved through intelligent contract automatic verification and user behavior analysis, threats can be dynamically responded, and the user experience is improved. The authority is dynamically adjusted based on the risk level, and a real-time access control decision engine is combined, so that the problem of response lag of traditional access control is solved, accurate authority control is realized, and finally, a continuously optimized security authentication mechanism and a unified and coordinated cross-platform security protection system are formed.

The invention relates to the technical field of energy storage systems, and provides a self-adaptive power distribution method and system for multiple energy storage units of an island microgrid. According to the invention, a discrete consistency algorithm is adopted to realize coordination control of multiple units, each unit only exchanges information with adjacent units, and power distribution targets of all the units are converged to a consistent value through iterative computation, so that the communication bottleneck and the single-point fault risk of centralized control are avoided; according to the invention, a complete fault-tolerant processing mechanism is designed, the operation state of each energy storage unit is monitored in real time, topology updating and power redistribution are automatically carried out when a unit fault is detected, and the self-healing operation of the system is realized. Experiments show that compared with a traditional method, the method has remarkable advantages in key performance indexes such as capacity balance among energy storage units, system operation efficiency, communication overhead and fault recovery time, and the operation efficiency and reliability of the island microgrid system are remarkably improved.

A heterogeneous storage-oriented hot and cold data management method and system, wherein hot and cold data are managed by means of the following steps: at table granularity, storing data from each table into an independent data bucket in the form of object storage, each data bucket comprising a plurality of partitions, the data being randomly distributed in each partition, and the consistency of replicas of the partitioned data being ensured by means of a distributed consensus algorithm; collecting statistics about the access frequencies of the partitions in one data bucket; when the access frequency of one partition reaches a set threshold, adding a new replica to a target storage medium by means of a membership change in the distributed consensus algorithm; and when data synchronization between the new replica and an old replica is completed, detecting the old replica. In this way, the migration of the partitioned data on different storage media is realized, and data cooling and heating are implemented. The method and system can maximize the use efficiency of high-performance storage media, ensure the access efficiency of users, and can reduce the costs of data migration and maintenance.

The invention discloses a multi-unmanned-aerial-vehicle cooperative hoisting method and system, and the method comprises the steps: firstly, enabling each unmanned aerial vehicle to operate an extended state observer, regarding internal and external disturbances (such as airflow, unknown load parameters, internal coupling force and the like) as a lumped disturbance, and carrying out the real-time estimation; and then, through a communication network operation consensus algorithm between the unmanned aerial vehicles, fusing the local disturbance estimation values of the unmanned aerial vehicles into a global consistent system-level disturbance estimation. And finally, each unmanned aerial vehicle actively counteracts the influence of disturbance by using the accurate disturbance estimation value in a feedforward compensation controller, and accurately tracks the respective target trajectory in combination with feedback control. According to the method, active observation of disturbance, distributed fusion and feed-forward compensation are combined, dependence on an accurate system dynamic model is eliminated, and trajectory tracking accuracy, stability and stability of the system in a complex environment are remarkably improved.

The invention provides an optimization method for proposal node selection of a consensus algorithm of a carbon Popingness block chain, and belongs to the technical field of carbon Popingness block chains. The optimization method comprises the following steps: starting a new era through a node, counting candidate node information, calculating a mathematical mean value and a standard deviation of a consensus efficiency score to identify an outlier node; evaluating the network performance of candidate nodes by applying a carbon popularity performance prediction model and a dynamic memory adjustment function, generating a proposal node list after removing outlier nodes, performing transaction verification and state verification by verification nodes, executing a multi-round voting verification process by a consensus algorithm, and adding consensus participation points for participation nodes, and after the block is submitted, each node sends a score list to the next height proposal node and writes the scoring data into the block head part, and through the complete node selection and consensus verification process, the technical problems that the proposal node selection efficiency is low and the nodes with abnormal performance cannot be effectively excluded in the block chain consensus algorithm are solved.

The invention relates to the technical field of power systems and energy management, and discloses an energy-carbon integrated virtual power plant multi-agent collaborative management and control method and system, and the method comprises the steps: S1, constructing a three-layer control architecture comprising a resource sensing layer, a region coordination layer and a global optimization layer; s2, establishing an energy-carbon coupling state space model, and outputting a target optimization result by taking photovoltaic output, energy storage charging and discharging power, a load demand elastic coefficient and a carbon emission right transaction volume as input variables; s3, generating a scheduling instruction by adopting a rolling optimization strategy; and S4, realizing multi-agent collaboration through a distributed consistency algorithm, exchanging power deviation information by each node based on a local constraint condition, and carrying out iterative calculation until the power deviation of all nodes is less than 1%. A three-layer control architecture is constructed, scheduling lag is shortened through decision making and stage processing of the global optimization layer after preprocessing of the regional coordination layer, the limitation of a single node is broken through through cross-regional coordination, and the overall operation efficiency of the virtual power plant is enhanced.

The invention discloses a Raft consensus algorithm-based dynamic management method and a related device, and relates to the technical field of communication, when a slave node server does not receive a heartbeat packet of a master node server overtime, the slave node server is automatically converted into a candidate node server and broadcasts an election request; and if the number of the received feedback information for confirming that the candidate node server is changed into the master node server is greater than half of the total number of all the slave node servers, determining that the candidate node server is changed into the master node server. The delay risk that a master-slave centralized architecture depends on manual monitoring and manual switching is thoroughly eliminated, fault discovery and response are solidified on an algorithm level, and automatic disaster recovery without human intervention is achieved.

The invention discloses a leader node transfer method, a distributed system, electronic equipment and a storage medium, and relates to the field of distributed systems.The method is applied to a leader node in the distributed system and comprises the steps that parameter values of performance parameters of the leader node are determined according to the hardware performance, the load condition and the network delay of the leader node, obtaining a target parameter value; obtaining N parameter values corresponding to N following nodes in the distributed system; determining candidate leading nodes from the N following nodes and the leading nodes according to the target parameter value and the N parameter values; and under the condition of determining to carry out leader node transfer, executing leader node transfer operation, so that the candidate leader node becomes a new leader node in the distributed system. By adopting the scheme, the performance of the distributed system is improved, and the problem that the performance of the distributed system is easy to be poorer due to the fact that the leader node is fixed in a consensus algorithm is solved.

The application belongs to the field of smart grid, and particularly relates to a smart grid economic dispatching control method based on a fixed time event triggering consistency algorithm; the method comprises the following steps: obtaining interaction information of a generator in a power grid system, determining a topological structure and a convergence parameter of the system according to the interaction information; calculating a fixed time upper bound according to the convergence parameter; sending self state information of the generator to neighbor generators; judging whether an update event triggering condition is met according to the self state information of the generator, the state information of the neighbor generators and an update event triggering protocol; if the triggering condition is met, the generator updates the self state information according to a control protocol; judging whether the system converges according to the self state information, and if the system converges, recording a convergence time; judging whether the convergence time is less than the fixed time upper bound, and if the convergence time is less than the fixed time upper bound, the generator saves the current state information to realize the economic dispatching control of the power grid; the application can reduce the cost of the smart grid and the continuous communication probability of the system.

The invention discloses an intelligent shuttle vehicle control system for tray conveying, which belongs to the technical field of intelligent shuttle vehicle control and comprises a multi-mode sensing module S1, a dynamic path planning module S2, a multi-vehicle collaborative scheduling module S3, an energy efficiency optimization module S4 and an edge calculation module S5. The multi-mode sensing module S1 comprises an environment sensing sub-module S11 and a cargo state monitoring sub-module S12, the environment sensing sub-module S11 comprises laser radar data preprocessing and visual sensor calibration and fusion, and the laser radar data preprocessing adopts a filtering algorithm based on statistics to remove outliers generated by environment interference. Through the distributed consensus algorithm and the task allocation strategy, the system throughput is improved, the path conflict rate is reduced, the work waiting time is remarkably shortened, the improved A * algorithm is combined with the reinforcement learning model, the time consumption of single path planning is shortened, the path generation efficiency is improved, and the method adapts to the high-dynamic storage environment.

The invention discloses a traceability monitoring system suitable for logistics supply chain monitoring, and particularly relates to the technical field of logistics supply chains, which comprises a data acquisition system, a data processing system, a traceability analysis system, a visual monitoring system, an early warning feedback system, a dynamic optimization system and a data synchronization system. According to the invention, through collaborative innovation of the Internet of Things sensor and the block chain technology, the problems of fragmentation and low credibility of traditional logistics data are solved; based on real-time data collection of RFID, a temperature and humidity sensor and a GPS, in combination with a PBFT consensus algorithm and a Merkle tree structure, efficient synchronization and tamper-proof storage of cross-mechanism data are achieved, the data integrity verification efficiency is improved by 50%, meanwhile, an Apache Flink stream processing engine is linked with an isolated forest algorithm, millisecond-level anomaly detection (such as temperature and humidity overrun and track loss) and cubic spline interpolation restoration are supported, and the data integrity verification efficiency is improved by 50%. The data cleaning accuracy is improved to 98%, and a high-confidence data basis is provided for subsequent analysis.

The invention discloses a dynamic optimization method for a USV-AUV collaborative navigation network topological structure based on a consensus algorithm, and relates to the technical field of collaborative navigation of an ocean unmanned system. Comprising the steps that according to a positioning equation between the unmanned surface vehicles and the autonomous underwater vehicles, the relation between the positioning error of the autonomous underwater vehicles and the distance measurement error between the unmanned surface vehicles and the distance measurement error between the autonomous underwater vehicles and the position error between the unmanned surface vehicles is constructed through a partial differential method; designing a positioning precision evaluation function by using an optimal estimation criterion; solving an optimal solution for the evaluation function by using an alternating direction multiplier method, and performing consistency estimation on a formation center and adjusting dynamic formation parameters through a consensus algorithm to obtain an optimal topological structure; and acquiring the number of the formation aircrafts in real time, if the number of the formation aircrafts changes, performing iteration, and if the number of the formation aircrafts does not change, keeping a topological structure. The method is high in dynamic adaptability, constraint collaborative optimization is achieved, the safety margin is improved, and robustness is enhanced.

The invention provides an eyesight health data management and privacy protection method based on a block chain, and the method comprises the steps: verifying the role identity of a requester through an intelligent contract if a query request is detected in an encrypted archive structure, judging whether the role identity accords with a preset hierarchical authorization rule or not, and obtaining an authorization verification result; after the filtered data response is obtained, generating a hash value of query operation by adopting an encryption algorithm, and determining a unique identifier of the access so as to facilitate subsequent tracking; broadcasting the generated hash value and access details to all nodes of the block chain network through a consensus algorithm, judging whether the network is consistent or not, and obtaining a confirmed log recording block; historical access behaviors are retrieved from the confirmed log record blocks, if an abnormal access mode is found, an alarm mechanism is triggered, and a complete traceable audit path is obtained to maintain data privacy.

The invention discloses an engineering building BIM (Building Information Modeling) data security management method, which comprises the following steps of: 1, embedding authority parameters into BIM model metadata through an attribute-based encryption algorithm; 2, deploying a permission management smart contract in an alliance chain, when project management triggers a stage change event, automatically calling the permission matrix generated in the step 1 by the smart contract, calling a BIMBase platform API to obtain a latest model version, recalculating the permission matrix, verifying the identity of an operator, and distributing an encrypted new permission set to related nodes; 3, constructing an auditing module containing a three-party alliance chain, and performing auditing confirmation within 5 seconds by adopting an improved PBFT consensus algorithm; a BIM event log visual interface is developed, and multi-dimensional retrieval according to roles, time and operation types is supported; 4, constructing an anomaly detection module of the LSTM-CNN hybrid model; constructing a normal behavior baseline model through transfer learning; when continuous three times of baseline deviation operation are detected, the module automatically triggers a three-level response mechanism.

The invention provides a financial big data information processing system based on a block chain. The financial big data information processing system based on the block chain comprises a block chain network access module used for accessing financial institution nodes and data provider nodes to an alliance chain network and synchronizing distributed account books among the nodes through a Byzantine fault-tolerant consensus algorithm so as to realize tamper-proof evidence storage and multi-party trust cooperation of financial big data information. According to the financial big data information processing system based on the block chain, through homomorphic encryption, zero-knowledge proof and other technologies, operation and verification of data in an encryption state are ensured, privacy of sensitive information is effectively protected, and data sharing and calculation can be smoothly carried out while confidentiality is ensured.

The invention discloses an internet protocol address access protection method and equipment, and relates to the technical field of internet. According to the scheme, the method comprises the steps that IP access records and safety related data are recorded in a tampering-free mode through a block chain distributed account book, and after a newly-added block is chained, a block chain node automatically updates a state database through an intelligent contract to maintain safety attribute information of an IP in real time. Before a terminal initiates IP access, a query request is sent to a plurality of nodes in a block chain network, after security attribute information fed back by each node is obtained, distributed verification is completed through a preset consensus algorithm, and finally an access control action is determined. A single central server is replaced by a multi-node distributed architecture, so that the risk of single-point failure is eliminated; secondly, an automatic updating mechanism driven by the smart contract greatly shortens a time window for responding to novel threats and IP redirection; and finally, all access records are publicly and transparently recorded on the block chain, so that the credibility and reliability of the system are enhanced.

The invention discloses a coal mine operation data transmission integrity verification method based on a block chain, and belongs to the technical field of coal mine operation data transmission integrity verification methods. An acquisition end performs standardization processing on original data, performs classification according to types and extracts key feature fields, generates a digital signature based on an SM2 algorithm, and generates a data hash value in combination with an SM3 hash algorithm; the method comprises the following steps of: packaging a data transmission packet containing meta-information, deploying block chain nodes in an underground key area and above a well to construct an alliance chain, and adopting an intrinsic safety type block chain gateway as an underground node; an uplink request is submitted before a data transmission packet is sent, a node verifies a digital signature and a Hash value through an improved PBFT consensus algorithm, the Hash value, a signature abstract and an uplink timestamp are written into a block chain, and transmission link parameters are monitored through edge computing equipment.

The invention provides a self-adaptive data consistency maintenance method for an electric power information system based on incremental updating, and relates to the technical field of big data processing, and the method comprises an initialization step, a detection step and a feedback step. In the initialization step, a network including regional power data nodes and a distributed account book is constructed, and full power data is stored; in the detection step, power data changes are confirmed, key attributes are used for marking data, automatic conflict detection is carried out through a distributed consensus algorithm, solutions for coping with conflicts are dynamically selected, and then an incremental updating mechanism is adopted for synchronously changing the data; in the feedback step, a monitoring system with a closed-loop feedback mechanism is established, the data consistency state is automatically tracked when the electric power data is changed, and abnormity is recognized. Compared with a traditional data synchronization method which needs to synchronize full data, the method provided by the invention only synchronizes the changed data fragments through an incremental updating mechanism, thereby ensuring the consistency of the data, remarkably improving the data processing efficiency and saving the network bandwidth.

The invention provides a multi-agent cooperative medical treatment system and method based on dynamic weighted consensus. The method comprises the following steps: acquiring original medical data of a patient from a hospital heterogeneous information system; the dynamic weight of each specialized agent is calculated based on the domain correlation, the evidence authority level and the historical decision accuracy, and opinions are fused and processed and conflicts are processed through a weighted consensus algorithm; and recording the corresponding subsequent determination result of the final processing scheme, updating the historical decision accuracy of each specialized agent, and providing an efficient, accurate, comprehensive, personalized and explainable diagnosis and treatment scheme for each patient.

The invention relates to a practical consensus algorithm for file resource sharing, which comprises reputation-driven task allocation: according to reputation values calculated in real time, nodes with high reputation values are preferentially selected by the algorithm to form a core consensus group to execute the most critical consensus task, and the number of nodes participating in core communication is remarkably reduced. And protocol flow optimization: fundamentally reducing the communication complexity to O (n) level by limiting the scale of the core consensus group and reconstructing a message transmission path. And node state dynamic autonomy: the algorithm has real-time evaluation and dynamic adjustment capabilities on node types. The reputation model continuously monitors node behaviors, can automatically perform degradation processing on low-reputation or fault nodes, and can timely discover and safely isolate or delete bad nodes through a specific mechanism without restarting the system. Through test verification, the reliability, safety, higher throughput and lower delay of the consensus algorithm are verified.

The invention provides an electric power monitoring data credible evidence storage and tracing method, which comprises the following steps of: acquiring state data in real time through an electric power tool integrated with a star flash communication module, and transmitting the monitoring data to an edge gateway in real time by adopting a star flash technology; the edge gateway receives the star flash data from each electric power tool, performs timestamp marking of Beidou clock synchronization, packages the data into blocks through an improved PBFT consensus algorithm, and stores the blocks in a local block chain; when the public network communication is recovered, synchronizing the local block chain data to a cloud block chain network through a wireless network; and carrying out tracing query on the block chain data based on the intelligent contract, and generating a credible tracing report containing a complete operation time sequence through timestamp comparison. The invention further provides a corresponding system. By implementing the method, the real-time performance, the integrity and the traceability of uploading the power monitoring data can be improved, and the traceability efficiency can be improved.

The invention discloses an intelligent traffic charging data storage and traceability method based on a block chain, and the method achieves the distributed storage and cross-department cooperative supervision of charging data through building a mixed chain structure comprising a main chain and a functional sub-chain. A dynamic data fragmentation technology is adopted to improve system throughput, and an improved PBFT consensus algorithm is combined to guarantee data consistency. A traceability system comprising data consanguinity tracking and a multi-party verification mechanism is innovatively designed, and rapid arbitration of charging dispute is supported. According to the scheme, the problems of data islands, tampering risks and the like existing in a traditional centralized charging system are effectively solved, and the traffic charging transparency and the operation efficiency are remarkably improved.

The invention discloses a reinforcement learning-driven block chain consensus algorithm dynamic selection method and system, and relates to the technical field of block chains, and the method comprises the steps: carrying out the performance evaluation of a target block chain, and determining the performance state information of the target block chain, including the transaction throughput, the average CPU utilization rate, the average memory utilization rate and the performance score; determining an optimal consensus algorithm by adopting a consensus algorithm selection method based on reinforcement learning according to the performance state information; and switching the current consensus algorithm to the optimal consensus algorithm based on the optimal consensus algorithm. According to the method, the optimal consensus algorithm can be selected and switched for the block chain system in real time, evaluation and optimization of the block chain consensus algorithm are realized, and the optimal performance of the block chain system under continuously changing fault scenes and workload conditions is ensured.

The invention discloses a multi-unmanned-ship multi-trajectory planning method and system based on a synchronization time consensus mechanism, and solves the problems of low precision and poor trajectory adaptability of multi-unmanned-ship cooperation synchronization in a complex water area environment by constructing a cooperation framework of the synchronization time consensus mechanism and dynamic trajectory optimization. The method is characterized in that the time information interaction frequency between the unmanned ships is dynamically adjusted by adopting an event trigger type communication mechanism, and the global optimal synchronization time is determined through a distributed consensus algorithm; and on the basis of the quintic polynomial parameterized trajectory, curvature minimization, path minimization and obstacle avoidance safety are taken as multiple trajectory planning targets, and an optimal trajectory adaptive to synchronization time is generated in combination with numerical differentiation and iterative optimization algorithms. According to the invention, the method can achieve the precise time synchronization and high-precision trajectory tracking of a plurality of unmanned ships in a scene with the limited network bandwidth and the dynamic change of environment interference, and remarkably improves the efficiency and reliability of an unmanned ship cluster in tasks such as cooperative hunting and regional patrol.

The invention discloses an abnormal transaction identification method and device based on edge node collaboration and electronic equipment, and relates to the technical field of distribution.The method comprises the steps that an encrypted transaction feature vector transmitted by an infrastructure end is received, a transaction request is generated based on the encrypted transaction feature vector, the transaction request is sent to a plurality of adjacent edge nodes, and the edge nodes send the transaction request to the infrastructure end; and receiving collaborative verification results of a plurality of adjacent edge nodes on the transaction request based on a preset consensus algorithm, performing abnormal transaction identification based on the collaborative verification results of all adjacent edge nodes by using a gradient boosting decision tree model, and executing the transaction request under the condition that the transaction identification result indicates that the transaction is a normal transaction. And a transaction execution result is fed back to the basic equipment end. According to the invention, the technical problem that the protection capability of a localized single-node detection system is easy to reduce for large-scale network attacks or fault conditions of individual nodes in the prior art is solved.