435 results about "Single node" patented technology

The invention discloses an adjustable load security access method for a virtual power plant, and relates to the technical field of power system automation, and the method comprises the following steps: in the operation process of a virtual power plant scheduling system, after an upper-layer scheduling center issues a unified adjustment instruction according to an operation demand, all access nodes are monitored in real time, and the adjustment instruction is sent to the upper-layer scheduling center; the method comprises the following steps: receiving a scheduling instruction from an access node, collecting response behavior data of the access node to the scheduling instruction, preprocessing the collected original response data of a single node, and carrying out unified coding and formatted storage on historical and current response behaviors according to node identification and scheduling time sequence information to construct a structured data set. According to the method, accurate identification and dynamic correction of the adjustable load frequency response offset risk in the virtual power plant are realized, the heterogeneous load perception and control capability is improved, frequency staggering resonance and scheduling failure caused by inconsistent response are avoided, the system cooperative adjustment stability and the load safety access reliability are enhanced, and the method has a good application prospect.

The invention relates to a federated learning system based on multi-key homomorphic encryption and adaptive differential privacy, and belongs to the technical field of privacy computing. According to the system, on the premise that no trusted third party exists, a multi-client collaborative key generation and threshold decryption mechanism is achieved, it is ensured that model parameters are always in an encrypted state in the aggregation process, and leakage of a single node is prevented. By introducing a parameter sensitivity analysis and selective encryption strategy, the system only encrypts high-risk parameters, and the encryption burden is effectively reduced. Meanwhile, in combination with an adaptive privacy budget allocation mechanism, the system dynamically adjusts noise intensity according to a model training state, and model performance and convergence speed are maintained while privacy protection capability is improved. According to the method, high robustness and collusion resistance are realized, stable operation under the condition that part of clients are offline is supported, and the method is suitable for application scenes such as medical treatment and finance with high data sensitivity and strict performance requirements.

The invention discloses a link state analysis method and device for a broadband ad hoc network, equipment and a medium. The method comprises the following steps: S1, acquiring coordinates and a signal intensity sequence of each node in a monitoring time period; s2, acquiring a link instability coefficient of the single node in the monitoring time period according to the difference of the nearest distances of the single node at different moments and the dispersion degree of the signal intensity sequence of the node; s3, according to the difference of the link instability coefficients of all the detection nodes in each emergency group, the correlation degree of the signal intensity sequences of any two detection nodes, and the dispersion degree of the coordinate distance of any two detection nodes at all moments, obtaining the regional co-variability of each emergency group; s4, the link global stability of the broadband ad hoc network system is obtained according to the mean value of all the link stability indexes; and S5, evaluating the link state according to the global stability of the link. According to the method and the device, the dynamic environment interference is integrally analyzed, so that the link state analysis accuracy is improved.

The invention relates to a heterogeneous cluster-oriented resource allocation method and device and a storage medium, and the method comprises the steps: executing a plurality of iterations of an initial model on a single node of each heterogeneous cluster, and obtaining the performance characteristics of the model; generating a plurality of parallel strategy combinations comprising the first parallelism degree and the second parallelism degree; generating a plurality of assembly line parallel combinations based on the first degree of parallelism, calculating the load imbalance rate of each assembly line parallel combination, and screening out N combinations with the minimum load imbalance rate from the assembly line parallel combinations; traversing the second parallelism degree and the micro-processing batch in each stage corresponding to each parallel combination to generate a plurality of stage strategy combinations; and calculating video memory occupation and execution time under each stage strategy combination, screening out K stage strategy combinations of which the video memories are smaller than or equal to a video memory threshold value and the execution time is shortest, and carrying out resource allocation on the heterogeneous cluster based on the stage strategy combinations. According to the invention, the problems of low training efficiency and low resource utilization rate are solved.

According to the user sensitive data protection system based on the cloud service and the block chain, an SM3 algorithm is adopted to fuse biological characteristics and dynamic tokens to generate an encryption credential, high-security identity authentication is achieved, differential fragmentation encryption is carried out on data based on semantic classification, Rabin threshold fragmentation and AES + ECC double-layer encryption is adopted for data of the highest security level, and the security level of the data is improved. A dynamic node optimization model is designed; an optimization coefficient is calculated according to the capacity, the transmission rate and the fault rate; the storage efficiency is improved by more than 40% in combination with a time period regulation factor; the node temperature and the vibration frequency are monitored in real time through a sensor; and verifying the validity period of the dynamic token and the fragment permission mark by using an intelligent contract to realize GDPR compliance fine-grained access control. The system remarkably improves the anti-attack capability and storage reliability of data, and is suitable for high-sensitivity scenes such as highway toll collection, finance and medical treatment.

The invention discloses a computer self-check cycle optimization method based on the Internet of Things in the technical field of server maintenance, and relates to the technical field of server maintenance. Server node operation state data is collected in real time, a dynamic load evaluation model is constructed, and a comprehensive load index is calculated; and dynamically dividing performance states based on the threshold values L1 and L2, and adjusting a self-checking period and a module priority. Calculating a single-node risk index Ri by adopting a fault risk model, generating a fault generalization risk factor R1 through a probability graph model in combination with network topology, and triggering a linkage mechanism; dividing and dynamically adjusting a self-checking period according to the early warning level; during advanced early warning, redundant resources are distributed to preferentially process key faults, edge calculation is combined to carry out data cleaning and standardization, distributed management is realized through a consistent Hash algorithm, and finally, a visual interface is used for displaying an optimized scheduling result, so that a closed-loop optimization system of data acquisition, risk prediction and resource scheduling is formed.

The invention relates to the technical field of keyboard pairing, and discloses a keyboard multimode pairing method and device, equipment and a storage medium. The method comprises the following steps: establishing a switching time calculation model of a keyboard according to the reference switching time of keyboard hardware, a protocol node cooperation coefficient, an equipment response weight coefficient and a pre-connection optimization coefficient; calculating the theoretical optimal switching time of the current switching scene; selecting a working mode of single-node direct switching, double-node pre-connection or three-node parallel pre-connection of a keyboard Bluetooth node, a 2.4 GHz node and a USB node; activating a corresponding communication node, sending a connection handshake signal to the target equipment and establishing a communication link pre-connection state; and switching keyboard input and output from the current equipment to the target equipment to finish quick connection switching between the equipment. According to the invention, a pre-connection mechanism is adopted, the target equipment connection is established in advance before the user completes the switching instruction, passive response switching is converted into active prediction switching, and instantaneous equipment switching is realized.

A honeycomb-shaped active power distribution network topological structure selection and optimization method based on a graph theory comprises the following steps: taking line impedance and rated apparent power as constraints, constructing a multi-target weight factor, adopting an improved spectral clustering algorithm to cluster and distribute power grid nodes, and transiting a micro-grid group after cluster division into a honeycomb-shaped active power distribution network; abstracting each micro-grid as a honeycomb distribution network single node, constructing a connection relation mathematical representation of the HSPH and the micro-grid, and realizing sparse matrix method modeling of the honeycomb active power distribution network; optimizing a site selection strategy of the HSPH by taking a maximized HSPH return on investment index and a system stability index as a target function; and optimizing the energy storage capacity of the HSPH based on the net load time sequence data of the micro-grid group, and finally generating an optimal topological structure of the honeycomb-shaped active power distribution network. And through honeycomb topology and HSPH addressing and sizing optimization, the new energy consumption capability of the power distribution network is improved, and the economy, reliability and flexibility of the power distribution network are improved.

The invention provides a model training method, device and system based on federated learning and safety protection, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the current training of a target model based on local training data, and obtaining a current model parameter; the local training data is obtained by performing quantum encryption on the original training data; performing homomorphic encryption on the current model parameter to obtain a current encrypted model parameter; uploading the current encryption model parameter to an aggregation node; and receiving global model parameters distributed by the aggregation nodes, and carrying out next training on the target model based on the global model parameters. According to the method, the device and the system provided by the invention, quantum encryption is adopted in an acquisition stage, and homomorphic encryption is adopted in an interaction stage, so that the privacy of an aggregation process is ensured, and a potential attacker cannot obtain model updating details of any single node; in the collaborative training process, it is ensured that data privacy is strictly protected, data are not attacked or tampered, and the efficiency of multi-party collaborative training is improved.

The present disclosure relates to a liquid cooling server cabinet, including a cabinet body, a liquid cooling module, and a pluggable assembly. The cabinet body is provided with a receiving cavity, and the pluggable assembly is arranged in the receiving cavity. The pluggable assembly includes at least one pluggable portion. The liquid cooling module includes at least one liquid cooling unit corresponding to the at least one pluggable portion. The pluggable portion is configured for a plugging and mounting of a single-node server that defines a cooling cavity. When the pluggable portion is mounted with the single-node server, the liquid cooling unit is communicated with the cooling cavity of the corresponding single-node server.

The invention relates to the technical field of data processing and storage, in particular to an asynchronous verification and batch storage system and method for high-concurrency voucher data. Certificate verification is executed based on the memory snapshot, and verification time consumption is improved from the millisecond level of database IO to the microsecond level of memory calculation; a batch persistence mechanism enables the throughput of the system to be improved by dozens of times, and a concurrent storage scene of ten thousand-level TPS can be easily supported; the voucher storage response time is reduced from a hundred millisecond level to a millisecond level; the response is immediately returned to the user after the verification is passed, the user almost does not need to wait, and the operation experience is smooth; the introduction of the message queue enables the system to have peak clipping and valley filling capabilities, and can deal with burst traffic leisurely; the multi-node cluster deployment supports horizontal capacity expansion, the fault of a single node does not influence the overall service availability, and the system reliability is improved.

The invention relates to a configuration implementation method and system for a large-scale FPGA (Field Programmable Gate Array) interconnection system-on-chip. The system comprises 32 data interconnection FPGA core particles and a control FPGA core particle, the control FPGA is connected with the data FPGA through 32 groups of independent Slave Serial interfaces to realize parallel configuration, and state monitoring is carried out through 32 groups of UART (Universal Asynchronous Receiver / Transmitter) interfaces; configuration data are received externally by adopting an RGMII interface, and an upper computer is connected through a system UART. The method comprises the following steps that: after the FPGA is controlled to be self-started from the Flash, an upper computer issues a configuration data packet through the RGMII; the FPGA is controlled to synchronously drive 32 groups of Slave Serial time sequences to complete parallel configuration; the state is fed back in real time through a dual-mode monitoring mechanism, and timeout fault-tolerant logic is implanted. According to the configuration implementation method and system, the configuration efficiency is improved, interface signals are optimized and reduced, single-node fault isolation is supported, and the system availability is improved.

The invention relates to the technical field of communication, in particular to an intelligent chemical single-process optimization design method and system based on dynamic decision, work order state change is carried out through a process engine according to a rule result, and when a rule engine returns a single node, a state field of a current work order record is updated as a target node name; the method has the beneficial effects that the flexibility and the automation degree of the process are improved, automatic adjustment of the process path is realized through a dynamic decision mechanism, manual intervention is reduced, and the processing efficiency is improved; multi-system integration and cooperative processing are supported, and seamless connection with a third-party system is realized due to an open interface and an integration capability, so that the cooperative efficiency of a business process is improved; the mobile terminal is adapted, so that the service linkage efficiency is improved; the process is imported and exported in a one-button mode, the traceability and stability of process configuration are ensured through a process management and version control mechanism, and maintenance and optimization of the process are facilitated.

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 clock synchronization method and device, electronic equipment and a medium, and relates to the technical field of communication. And then one or more clock maintenance nodes can be determined by using the time delay between the target node corresponding to the global clock information and each other node except the target node. And if the target node or the clock maintenance node receives the clock synchronization request of the to-be-synchronized node, responding to the clock synchronization request, and pushing the global clock information to the to-be-synchronized node. Both the target node and the clock maintenance node in the distributed system have the global clock information, so that high availability of the global clock information in the distributed system is ensured, and the problem of unreliability caused by clock synchronization depending on a single node in the distributed system is solved.

The invention discloses an Internet of Vehicles double-layer block chain fragmentation method, and relates to the field of intelligent transportation systems.The Internet of Vehicles double-layer block chain fragmentation method is characterized in that consensus tasks are processed in a labor division mode through an'mining-packaging 'double-layer fragmentation structure, parallel transaction processing is achieved, single-node load is reduced, and the overall processing capacity is improved; a node reputation evaluation mechanism is used for dynamically evaluating and screening consensus nodes, low-reputation even malicious nodes are effectively eliminated, the Byzantine risk is reduced, and safe operation of the block chain is guaranteed.

Systems and methods are disclosed to revolutionize blockchain consensus mechanisms by introducing a novel, inclusive framework that enhances efficiency, scalability, and environmental sustainability. Central to this breakthrough are a cluster-based scoring system and a multi-queue dynamic scheduling mechanism, designed to replace resource-intensive consensus models like Proof of Work and Proof of Stake. This approach allows nodes to participate based on merit, determined through an iterative scoring process within clusters, democratizing access, and participation across the blockchain network. The system dynamically adjusts mining complexity as the blockchain evolves, ensuring scalability and reducing energy consumption. A key innovation is the introduction of cooldown periods to prevent dominance by any single node, promoting fairness and security. This decentralized, efficient, and scalable solution paves the way for broader blockchain adoption, maintaining the technology's foundational principles while addressing its traditional limitations.

The application relates to a service scheduling and deployment method for Internet of Things edge computing node resources, which is realized based on an Internet of Things edge computing system. The system comprises a cloud data center, a convergence layer core network and a plurality of access layer switch networks connected in sequence. Each access layer switch network is in communication connection with a plurality of edge computing nodes, and each edge computing node is in communication connection with a plurality of data acquisition terminals. The application comprehensively considers the current running state of the edge computing system, network delay problems and running results after deployment, and performs service scheduling and deployment of Internet of Things edge computing node resources on each real-time data stream computing application. The application is suitable for the decision environment of the real-time computing task load and bandwidth dynamic change of the Internet of Things edge computing node, realizes global optimization from the system level, takes into account the single node load capacity, and realizes the optimal scheme and application planning and deployment decision suggestion of the long-period stable operation and real-time task flexible scheduling strategy.

The invention relates to the technical field of network data security, in particular to a power fgOTN power low-delay secure transmission method. Obtaining a service bearing network topology and link transmission parameters, and constructing a network connection matrix; simulating a flow redistribution process after a fault of a single node, and calculating a topology betweenness centrality index of the substation node; the method comprises the following steps: analyzing payload contents of power business data frames at a fgOTN mapping preceding stage, extracting continuous monitoring features and discrete control features, and calculating a real-time business criticality index of each data frame in combination with a frequency deviation and a voltage fluctuation state of a current network; establishing a two-dimensional decision matrix, and generating a defense strategy according to mapping positions of the topological betweenness centrality index and the criticality index value in the matrix; processing the service data according to the generated defense strategy, and mapping the service data to a fine granularity time slot of the fgOTN; and embedding a security state signaling in the frame overhead, and sending the security state signaling to opposite-end equipment through an optical transmission unit.

The embodiment of the invention discloses an interaction method and device for an OCFS2 cluster service and a block storage service, and the method comprises the steps: receiving a volume operation request through the block storage service, carrying out the analysis of the volume operation request, and determining a request type and a resource identifier; initiating a corresponding lock request to a distributed lock manager of any OCFS2 cluster service through the block storage service according to the request type; performing lock conflict detection on the lock request through the distributed lock manager, and granting a corresponding lock permission to the target resource when a lock conflict detection result is no conflict; executing a corresponding target operation on the target resource through the block storage service according to the lock permission and the resource identifier; according to the scheme, the problem that the interaction reliability of the cloud operating system is low is solved, the OCFS2 cluster service of any node can execute the target operation on the target resource in the OCFS2 cluster file system based on the volume operation request, normal interaction of other nodes is not affected by a single node fault, and the interaction reliability in the cloud operating system is remarkably improved.

The invention provides an artificial intelligence monitoring model method based on thermal power plant edge side single node deployment, and relates to the technical field of thermal power plant intelligent monitoring. The method comprises the steps of obtaining DCS system data of a thermal power plant and image data of an infrared thermal imager, constructing a special operator library to extract feature information, constructing a monitoring neural network model by using an improved MobileNetV3, introducing a dynamic pruning strategy and a knowledge distillation technology to perform model compression, and deploying a final model at an edge side single node to execute a task. Through a special operator library and a lightweight model architecture, efficient feature extraction of the model and reduction of a storage space are realized, the weight is converted from FP32 to INT8 in combination with quantitative perception training, the reasoning efficiency is improved, and meanwhile, high-precision monitoring is kept. Under a multi-task scene, a resource allocation priority function is adopted to dynamically allocate resources, a fault prediction task is guaranteed preferentially, the real-time performance and the response speed of the model are remarkably improved, the equipment fault risk of the thermal power plant is reduced, and support is provided for intelligent upgrading of the thermal power plant.

The invention belongs to the technical field of resonance stability of a power system, and discloses a high-voltage reactance configuration method for improving resonance stability of the power system, which solves the precision defect caused by neglecting voltage fluctuation in traditional modeling by establishing a fan and static var generator precise admittance model considering DC voltage fluctuation. The dq admittance model of the alternating current system is obtained according to the nodes, connected to the alternating current system, of the fan and the static var generator, general calculation of dq admittance of the multi-node alternating current system is achieved, the limitation that only single-node modeling is supported in a traditional method is broken through, the complex stability problem is quantized into an optimizable amplitude margin index, and the stability of the system is improved. A clear basis is provided for resonance stability analysis, high reactance configuration is expanded from traditional reactive compensation to resonance stability active optimization, and the resonance stability design efficiency of the new energy grid-connected system is remarkably improved.

The invention discloses a data security storage system and method suitable for a resource-constrained network node, and relates to the technical field of data security storage, and the method comprises the steps: carrying out the homomorphic encryption of to-be-transmitted data through employing an elliptic curve public key, packaging a homomorphic ciphertext pair through employing a session key, obtaining a transmission message, and transmitting the transmission message to a network node; transmitting the transmission message to a relay node; determining a target storage node by calculating the distance between the storage node and the aggregated ciphertext pair, performing secondary packaging on the aggregated ciphertext pair by using a storage key, performing disk falling on the target storage node, generating a Verkle proof, and establishing a data storage index; and the secondary ciphertext load is unpacked by using the storage private key, and decryption is performed by using the elliptic curve private key to obtain plaintext data. According to the method, distributed mapping is carried out, secondary packaging is carried out through a storage key derived by homology, lightweight verifiable disk falling and multi-copy redundancy are completed in combination with Verkle certification, and single-node indexing and certification expenses are reduced.

The invention discloses a distributed sensor abnormal event identification method for intelligent traffic, and particularly relates to the technical field of traffic information perception and identification, and the method comprises the following steps: generating an abnormal information initial confidence value through deploying a sensor node with a confidence value dynamic adjustment function; during fusion processing, independent identification priorities of single node anomalies are reserved; after sequence reconstruction of a unified time reference, judging whether a response condition is met or not in combination with trajectory evolution; if yes, an abnormal response process is triggered, a space-time compensation set is constructed based on historical data of the sensing blind area for verification, and finally an abnormal intervention instruction is output and a traffic scheduling system is linked; according to the method, the sensing sensitivity, the fusion accuracy and the response timeliness of the abnormal information in a complex traffic environment are improved, the problem of an identification blind area that single-point abnormity is covered is avoided, state reconstruction and supplementary verification of the sensing blind area are realized, and the rapid intervention capability of an intelligent traffic system on emergencies is enhanced.

The invention provides a distributed storage node connection optimization method based on network layer load balancing. According to the distributed storage node connection optimization method based on network layer load balancing, dynamic balanced distribution of the connection number of the storage node clients is achieved, the utilization rate and stability of system resources are improved, and the problem of downtime caused by overload of a single node is effectively avoided.

The embodiment of the invention provides a distributed data deduplication method and product. The method comprises the steps of obtaining a data key of data to be subjected to deduplication; distributing the data to be subjected to duplicate removal to the ith sub-bucket according to the mixed hash value of the data key; mapping the mixed hash value according to a hash function attribute value configured for the ith sub-bucket to obtain k position numbers; reading numerical values of positions corresponding to the k position numbers from a bit array which is stored at the current moment and corresponds to the ith sub-bucket to obtain k numbers; if it is confirmed that the k numbers are all first numerical values, it is confirmed that the data to be subjected to duplicate removal belong to duplicate data; and if at least one of the k digits is confirmed to be a second numerical value, confirming that the data to be subjected to duplicate removal belongs to new data. According to the embodiment of the invention, the speed and accuracy of big data deduplication processing are remarkably improved, and the problem of single-node calculation overload (different buckets can be distributed to different calculation nodes) is effectively solved.

The invention discloses a PLC-IoT street lamp electric leakage detection method and system based on edge calculation, and relates to the technical field of smart power grids and Internet of Things. According to the invention, the self-adaptive threshold adjustment algorithm is adopted to dynamically calibrate the electric leakage detection threshold, so that the problem that the traditional fixed threshold method is easy to generate false alarm or missing alarm when the environment changes is effectively solved, and the accuracy and reliability of detection are remarkably improved; through a multi-node collaborative decision algorithm and a data fusion technology, the regional electric leakage risk can be accurately judged, misjudgment caused by local interference in single-node detection is avoided, the robustness of the system is enhanced, through a parameter optimization mechanism and a machine learning regression algorithm, an environment correction coefficient and detection algorithm parameters can be dynamically adjusted, and the reliability of the system is improved. The electric leakage risk trend is predicted, dynamic and accurate evaluation of the electric leakage risk is realized, and the intelligent level and the management efficiency of the system are improved.

The embodiment of the invention provides an inference acceleration method and system based on a large language model. The method comprises the following steps of: firstly, reading a query vector, a key vector and a value vector which are calculated by a matrix processing kernel and are subjected to offset addition and quantization operation from a shared cache by virtue of a multi-head attention kernel in a system, respectively calculating an attention score and target key value data, and outputting data to be decoded; the single-node calculation efficiency is guaranteed through customized hardware pipeline design; then, the query vector is recalculated in the decoding stage, the target key value data stored in the high-bandwidth storage key value cache region in the pre-filling stage are directly reused, and resource waste caused by repeated weight loading is avoided; finally, a model parallel strategy is adopted, calculation tasks of the large language model are distributed to all accelerator nodes, distributed execution of large-scale matrix operation among multiple nodes is achieved, the node number can be flexibly expanded according to the model scale in the scheme, and the expansibility of the reasoning acceleration scheme is remarkably improved while reasoning efficiency is guaranteed.

The invention discloses a multi-source property right data verification method, and relates to the technical field of data processing. The method comprises the following steps: acquiring property right data from different data sources, and converting the property right data into a unified field according to semantics of the property right data and a preset mapping rule; after the knowledge graph is constructed based on the uniform field, the business rule vectors are coded into node attributes of the knowledge graph; and traversing nodes and edges in the knowledge graph through a preset graph traversal algorithm, and verifying the property right data according to the business rule vector to obtain a verification result. According to the method, the association relationship between the knowledge graph integration entities is constructed, and the service rule is encoded into the knowledge graph for verification, so that verification is not limited to single node data any more, cross-node verification can be performed in combination with the association information, and the verification accuracy is improved.

The invention provides a disaster recovery database data synchronization method and device, equipment and a storage medium. Relates to the technical field of data processing. The method comprises the steps that logs of all nodes are written into log queues corresponding to all the nodes; determining that the transaction corresponding to the queue head log in each log queue is a single-node transaction or a distributed transaction; writing the submission transaction identifier and the transaction information of the queue head log into a global playback queue according to the sequence of writing the submission transaction identifier of the single-node transaction and the corresponding transaction information and then writing the submission transaction identifier of the multi-node transaction with the minimum submission transaction identifier and the corresponding transaction information; analyzing the transaction information in the global playback queue to obtain statement blocks; writing the statement blocks into at least one playback queue according to the submission transaction identifiers corresponding to the statement blocks; and sending the statement blocks in the playback queues to the disaster recovery database, and enabling the disaster recovery database to execute the statement blocks so as to synchronize data of the source end database in real time. The problem that disaster recovery switching time is long is solved.