1973 results about "Transmission protocol" patented technology

The invention relates to the technical field of medical terminal data secure transmission and real-time management and control, in particular to a bank medical intelligent terminal data secure transmission and real-time management and control system and method. The behavior analysis module is used for calculating threat indexes through federated learning, the strategy module is used for dynamically switching algorithms and isolating anomalies, and the audit module is used for block chain verification and zero knowledge verification to generate a report. According to the method, dynamic encryption and fragmentation cutting are driven through sensitivity grading labels, the accuracy of data protection is improved, a time sequence attack path is blocked based on cooperation of fragmentation time sequence reference and an encryption transmission protocol, and dual guarantee of decentralized auditing and tampering positioning is realized by combining block chain hash identification and zero-knowledge proof verification, so that the security of data protection is improved. And full-link safe transmission and real-time management and control requirements of medical terminal data are met.

The invention discloses a network security situation early warning method and system based on a knowledge graph, and relates to the technical field of network security, the method establishes a normal behavior reference model of a network node through the combination of the knowledge graph and a deep learning algorithm, and enhances the accurate identification and real-time early warning capability of abnormal behaviors. Through an unsupervised learning algorithm, historical data of each node is learned and modeled, and a normal behavior reference value is formed. In the real-time monitoring process, deviation calculation is carried out on the current access behavior of each node and the reference value of the current access behavior, a deviation degree value is obtained and compared with a set deviation threshold value, and abnormal nodes deviating from normal behaviors are identified and marked. The deviation degree model combines key factors such as a transmission protocol and data transmission duration, and can sensitively detect tiny deviation of the node in communication frequency or authority, so as to quickly adapt to a dynamic network environment.

The invention relates to the technical field of integration of artificial intelligence security and network security, and discloses an AI dynamic security transmission system based on an SASE framework, which realizes security access control based on AI dynamic identity verification through an SASE integration access module, acquires and predicts network performance change in real time by using a network state sensing module, and transmits the network performance change to a network server. Equipment, environment and data content are subjected to multi-dimensional analysis by means of a security risk assessment module, a quantitative risk score is generated, and a transmission protocol, parameters and encryption strength are dynamically adjusted according to a network state and the risk score by means of a dynamic transmission optimization module and a self-adaptive encryption module; the problem that safety protection and transmission efficiency are difficult to cooperate in a traditional architecture is effectively solved, low-delay and high-reliability data transmission service can be provided for AI application in a complex network environment, meanwhile, self-adaptive dynamic protection of the whole data transmission process is achieved, and data safety is comprehensively guaranteed.

The invention provides a data management method, device and equipment and a readable storage medium, and the method comprises the steps: obtaining key value cache data generated by a first type of computing power unit in a pre-filling stage, transmitting the key value cache data to a memory pool, and caching the key value cache data in the memory pool; and in response to a data acquisition demand of the second type of computing power unit in a decoding stage, transmitting the specified key value cache data cached in the memory pool to the second type of computing power unit according to the data acquisition demand. According to the technical scheme of the invention, the memory pool is arranged and the aggregated transmission channel is utilized, so that the transmission efficiency of the key value cache data between the computing power devices is effectively improved, the data transmission delay is reduced, and the network transmission protocol overhead is reduced, thereby improving the data interaction efficiency of the computing power devices in a pre-filling stage and a decoding stage, and improving the user experience. The utilization of computing power resources is optimized, and the throughput and performance of large model reasoning are improved.

The invention relates to the technical field of Internet of Things communication, and discloses an Internet of Things data information transmission method, a switch and a transmission system. The method comprises the following steps: acquiring multi-source data streams of Internet of Things terminal equipment, dynamically fragmenting according to types to generate fragmented data packets, matching a target transmission protocol for the fragmented data packets, generating a dynamic routing path in combination with a priority mark and the like, and transmitting the dynamic routing path. The system also has the functions of link quality evaluation and route adjustment, redundant coding packet loss recovery, transmission delay and integrity monitoring processing, encryption transmission based on security level, resource optimization, transmission strategy adjustment and the like. The switch is integrated with a data fragmentation module, a protocol matching module and the like. The transmission system comprises a terminal device cluster, an edge node network, a cloud server and a protocol conversion gateway. The data transmission efficiency, reliability and safety are improved, resource utilization is optimized, and the data transmission problem of the Internet of Things is effectively solved.

The invention provides a precise interference method and system for pilot signals of a remote controller of an unmanned aerial vehicle, and the method comprises the steps: receiving and processing an image transmission signal and a remote control signal of the unmanned aerial vehicle, and analyzing a starting time, a transmission period and different types of image transmission protocol classification results of the image transmission signal; extracting the time period of the remote control signal and the occurrence time of a pilot symbol in the remote control signal; generating optimized interference signal parameter configuration by utilizing a reinforcement learning algorithm, analyzing historical data by utilizing a long short-term memory network to obtain a historical analysis result, and predicting an optimal interference opportunity; monitoring a wireless communication environment around the unmanned aerial vehicle by using a real-time spectrum sensing technology so as to identify a potential conflict frequency band, and selecting a target interference frequency band by using a frequency agility technology; determining a precise interference method based on the historical analysis result, the optimal interference opportunity and the target interference frequency band; according to the invention, the interference precision and effect on the pilot signal of the remote controller of the unmanned aerial vehicle are improved.

The invention discloses a cloud edge cooperation method for AI intelligent Internet of Things equipment data processing, and relates to the technical field of data processing, and the method comprises the steps: S1, intelligent data collection, S2, edge side AI preprocessing, S3, edge-cloud end cooperation reasoning, S4, intelligent data transmission, S5, cloud end AI big data analysis, S6, real-time feedback and self-optimization, S7, adaptive resource scheduling, and S8, full-link visualization. Through AI-driven dynamic sampling and multi-modal data fusion, the efficiency and precision of data acquisition are optimized, redundancy or omission caused by fixed sampling is avoided, meanwhile, the transmission load is reduced, layered task dynamic unloading and intelligent transmission protocol optimization are achieved, the flexibility and stability of cloud edge collaboration are improved, and the cloud edge collaboration efficiency is improved. Manual intervention is reduced through a real-time feedback and self-optimization mechanism, the autonomy of the system is enhanced, and the interpretability and fault diagnosis capability of the system are remarkably improved through a visual panel and a causal reasoning model.

The invention relates to the technical field of water and fertilizer integration, and provides an intelligent water and fertilizer integration optimization method and device based on the Internet of Things technology, and the method comprises the following three core stages and interaction mechanisms: 1, a data perception and edge processing stage; 2, an intelligent decision-making and dynamic optimization stage; and step 3, an accurate execution and closed-loop control stage. Soil parameters, meteorological parameters and crop physiological parameters are comprehensively collected through a multi-modal sensor network, the data transmission efficiency is improved by using an LoRa / NB-IoT hybrid transmission protocol, data cleaning and standardization processing are completed in combination with edge computing nodes, and the data fusion depth and quality are improved; a multi-objective optimization function is constructed based on a crop growth model, a water and fertilizer regulation and control strategy is dynamically generated through a machine learning algorithm, and collaborative optimization of water saving, yield increasing and environmental protection is achieved.

The invention discloses an industrial odor online monitoring system based on big data. The system comprises a data acquisition module, a preprocessing module, a feature fusion module, a multi-source sensing weight analysis module, a dynamic risk assessment module, a self-adaptive correction module and a real-time feedback module. Data interaction among the modules adopts a block chain encryption transmission protocol, and a feature evaluation mapping chain with a timestamp is established in a distributed database. Through the innovative design of heterogeneous sensor network collaborative perception, cross-modal feature organic fusion, pollution diffusion three-dimensional dynamic deduction and a credible data governance architecture, a new industrial bad smell monitoring normal form with environment intelligent adaptability is constructed. The four technical effects form complementary support from four dimensions of data acquisition credibility, feature modeling scientificity, risk assessment accuracy and system decision robustness.

A fabric control protocol (FCP) is a data transmission protocol that enables spraying of individual packets for a given packet flow across a data center from an ingress interface of the source data processing unit (DPU) across a plurality of parallel data paths of a logical tunnel in the network fabric to the egress interface of the destination DPU. The FCP has congestion control mechanisms used to determine a degree of congestion at the egress interface of the destination DPU and to modify a send window size at the source DPU based on the degree of congestion. Reliable FCP (rFCP) extensions provide reliability enhancements and improved failure resilience within the data center. The rFCP extensions provide an unsolicited mode for low latency operation with enhanced reliability mechanisms. The rFCP extensions provide failure resilience mechanisms to identify and avoid failed paths among multiple parallel data paths within the logical tunnel.

The invention provides a monitoring video transmission method and system based on wireless communication, and relates to the technical field of monitoring video transmission, and the method comprises the steps: obtaining and preprocessing network state data, the network state data comprising bandwidth, time delay and packet loss rate; establishing a network state prediction model based on the LSTM neural network, and predicting a future network state according to the network state prediction model; based on the future network state, a multi-objective optimization algorithm is adopted to perform transmission path selection; and for the selected transmission path, video coding parameters are adjusted, the coding parameters comprise a code rate, a resolution ratio and a frame rate, and a self-adaptive transmission protocol is adopted to dynamically adjust the transmission rate according to a real-time network state. According to the method, different paths can be dynamically selected, network congestion or degradation is avoided, and the video transmission quality and rate are adaptively and flexibly adjusted according to the current network state, so that stable transmission of the video quality under different network conditions is ensured.

The invention relates to the technical field of satellite communication, in particular to a high-orbit and low-orbit satellite communication resource scheduling method and system, which collects real-time state information of high-orbit and low-orbit satellites, performs digital simulation of a satellite network based on the real-time information, constructs a satellite network management model and predicts satellite trajectory change. The method comprises the following steps: performing multi-dimensional evaluation on a satellite network management model by using a pre-constructed network evaluation framework, generating cross-orbit link evaluation information, analyzing parameters such as link quality and bandwidth, obtaining current service demand information, analyzing a communication resource allocation strategy in combination with a cross-orbit link evaluation result, and formulating a resource scheduling strategy according to strategy analysis. And a high-orbit and low-orbit satellite communication network is constructed through execution of a hierarchical network management mechanism and a cross-orbit data transmission protocol.

The invention relates to the technical field of data compression and transmission, in particular to a dynamic data compression and transmission system and method based on big data. The method comprises the following steps: a data acquisition and processing unit acquires original data from various data sources and processes the original data; the data compression execution unit compresses original data through an LZ4 compression algorithm, and introduces a layered matching DEW-LZ4 technology based on dynamic entropy weight into the LZ4 compression algorithm to optimize the compression process; the data transmission unit performs network transmission on the compressed data through a transmission protocol HTTPS, and dynamically adjusts transmission parameters by adopting a machine learning Q-Learning model according to a network state; and a receiving end decompression unit obtains the transmitted compressed data from the network, decompresses the compressed data by using an LZ4 decompression algorithm, and recovers the compressed data to an original data format. According to the design of the invention, by introducing a layered matching DEW-LZ4 technology based on dynamic entropy weight, the system can intelligently select an optimal compression strategy according to different characteristics (Shannon entropy values) of data.

A fabric control protocol (FCP) is a data transmission protocol that enables spraying of individual packets for a given packet flow across a data center from an ingress interface of the source data processing unit (DPU) across a plurality of parallel data paths of a logical tunnel in the network fabric to the egress interface of the destination DPU. The FCP has congestion control mechanisms used to determine a degree of congestion at the egress interface of the destination DPU and to modify a send window size at the source DPU based on the degree of congestion. Reliable FCP (rFCP) extensions provide reliability enhancements and improved failure resilience within the data center. The rFCP extensions provide an unsolicited mode for low latency operation with enhanced reliability mechanisms. The rFCP extensions provide failure resilience mechanisms to identify and avoid failed paths among multiple parallel data paths within the logical tunnel.

The invention relates to the technical field of data transmission, in particular to a meteorological data compression and transmission intelligent control system which comprises a network state evaluation module, a data priority evaluation module, a data compression and encryption module and a data transmission control module. According to the invention, network conditions can be effectively predicted and key data can be transmitted preferentially by evaluating network volatility and data emergencies, the reliability and efficiency of data transmission are improved, delay and packet loss in the data transmission process are reduced through targeted data compression and encryption processing, and the data transmission efficiency is improved. Meanwhile, the safety of data in the transmission process is guaranteed, especially in a bandwidth-limited network environment, quick and accurate transmission of key meteorological information can be guaranteed by adjusting data transmission bandwidth allocation and selecting a proper transmission protocol, resource allocation is optimized, the adaptive capacity of the system to complex network conditions is enhanced, and the service life of the system is prolonged. Therefore, the system can work efficiently under the condition that the network load is large or unstable.

The invention relates to the technical field of data packet transmission, and discloses a data packet transmission control method and device for a low-power-consumption dual-mode Bluetooth chip, and the method comprises the steps: obtaining a signal strength parameter, a power consumption parameter, a transmission rate parameter and an environment parameter of the dual-mode Bluetooth chip, inputting the parameters into a deep time convolution network, and carrying out the time sequence feature extraction, obtaining a transmission mode switching judgment result; calculating transmission state evaluation data; the chip transmitting power is adjusted in a grading mode, standby power consumption is controlled through a nanoamp LDO circuit, and a dynamic power control parameter is obtained; performing compression coding on the data packet to obtain a dual-mode transmission protocol configuration parameter; executing time sequence sampling, and constructing a dual-mode state feature sequence; the data packet delivery success rate, the end-to-end transmission time delay and the total power consumption of the system are calculated, transmission control parameter optimization is carried out through double-layer deep reinforcement learning, target transmission control parameters are obtained, and the optimal balance of the transmission performance and the power consumption of the dual-mode Bluetooth chip is achieved.

The invention relates to the technical field of data fusion, in particular to a multi-source heterogeneous data fusion method and system based on cloud computing, and the method comprises the steps: carrying out the feature extraction of multi-source heterogeneous data, and generating standardized metadata comprising a data type, a transmission protocol and a semantic tag; an adaptive interface is dynamically generated based on the metadata, the adaptive interface comprises a data format conversion module, a protocol packaging module and a semantic analysis module, and cross-domain compatible data streams are output; performing data fragment encryption and priority marking on the cross-domain compatible data stream to generate a secure transmission block carrying a transmission feature vector; incremental fusion is executed at the cloud fusion node, semantic conflicts are detected by constructing a knowledge graph, and a fusion intermediate state is generated; and performing dynamic verification on the fusion intermediate state based on the credibility evaluation model, and outputting final fusion data with a credibility label. According to the method, the dynamic verification and hierarchical labeling of the fusion result are realized, and the semantic consistency and expandability of the fusion intermediate state are ensured.

The invention discloses a hierarchical optimization scheduling method for deep peak regulation of thermal power generating units, and the method comprises the following steps: system layering: dividing a power system into a plurality of subsystems, each subsystem comprising a thermal power generating unit cluster and differentiated load demands; subsystem-level prediction: generating a basic scheduling plan; dynamic preference-driven multi-target collaborative optimization: receiving multi-target data from each subsystem, carrying out multi-target collaborative optimization, modeling three targets of a power grid company, an environmental protection department and a terminal user as game participants, quantifying the priority of each party by adopting a fuzzy membership function, generating a dynamic game solution through a Nash equilibrium solver, and carrying out multi-target collaborative optimization; screening out a Pareto optimal solution giving consideration to interests of multiple parties; performing online verification on the dynamic security domain; virtual synchronous machine cooperative support: simulating operation characteristics of a synchronous generator; and global coordination and iterative optimization: uploading the optimal scheduling scheme of each subsystem to a scheduling center through a message queue telemetry transmission protocol, and performing global constraint verification.

The invention provides an HPLC (High Performance Liquid Chromatography) and micropower wireless dual-mode communication method, which belongs to the technical field of multiplexing communication, is used for realizing cooperative transmission of power line carrier communication and micropower wireless communication, and comprises a modulation end method and a demodulation end method. According to the modulation end, firstly, HPLC and micropower wireless signals are collected, and band-pass filtering and spectrum sensing are carried out, so that frequency bands which do not interfere with each other are obtained. Then, a unified time reference is established, transmission delay is calculated, and delay compensation is carried out; and then, modulating and transmitting by adopting an orthogonal frequency division multiplexing technology. And at a receiving end, main and standby channels are selected according to the signal strength, and demodulation and data recovery are performed by adopting an adaptive modulation and demodulation technology. According to the scheme, the advantages of HPLC and micropower wireless are fully utilized, fusion of two communication technologies is achieved, and the technical problem that effective cooperation is difficult to achieve due to the fact that existing HPLC and micropower wireless communication often adopt independent communication carriers and transmission protocols is solved.

A fabric control protocol (FCP) is a data transmission protocol that enables spraying of individual packets for a given packet flow across a data center from an ingress interface of the source data processing unit (DPU) across a plurality of parallel data paths of a logical tunnel in the network fabric to the egress interface of the destination DPU. The FCP has congestion control mechanisms used to determine a degree of congestion at the egress interface of the destination DPU and to modify a send window size at the source DPU based on the degree of congestion. Reliable FCP (rFCP) extensions provide reliability enhancements and improved failure resilience within the data center. The rFCP extensions provide an unsolicited mode for low latency operation with enhanced reliability mechanisms. The rFCP extensions provide failure resilience mechanisms to identify and avoid failed paths among multiple parallel data paths within the logical tunnel.

The invention relates to the technical field of audio pushing optimization, and discloses an audio stream pushing crash prevention method and system, a storage medium and equipment, and the method comprises the steps: dynamically generating a format perception pre-detection thread based on a current audio stream format, and adjusting the priority and sampling frequency of the thread according to the audio bit depth and the sampling rate; multi-level intelligent buffer area management with sound quality priority is implemented, and dynamic adjustment of the size of a buffer area and adaptive switching of the buffer area are realized according to different audio formats and input source types; establishing a cross-brand equipment coordination framework, and setting a watchdog timer with preferential tone quality to perform timed monitoring so as to process response timeout; triggering an elegant degradation strategy of sound quality priority according to the resource availability score, and reducing the audio processing quality step by step to maintain the playing continuity; the key characteristics of each transmission protocol are identified and utilized, the transmission protocols are adaptively switched according to the network condition and the processing capability of brand equipment, and real high-quality and zero-interruption audio experience is brought to users.

The invention belongs to the technical field of data synchronization, and particularly relates to a real-time data synchronization method for cloud computing heterogeneous resources. In order to solve the problem of data synchronization among heterogeneous resources, the method comprises the following steps: aggregating a plurality of files in batches to generate a packaged file; performing metadata compression processing on the generated packaged file, and eliminating repeated data through a deduplication algorithm; dynamically selecting a lightweight data transmission protocol; establishing a multi-dimensional index structure; only retaining the file of the latest version through a version control mechanism; dynamically adjusting the allocation of synchronization tasks based on the load condition of available resources in the cloud computing environment; and rescheduling the uncompleted synchronization task. Through a multi-dimensional index structure, version control, self-adaptive transmission scheduling and a dynamic resource allocation mechanism, efficient and stable file synchronization among heterogeneous resources is realized, repeated transmission and storage waste are reduced, and real-time performance, reliability and resource utilization efficiency of synchronization are improved.

The invention provides a TCP / UDP (Transmission Control Protocol / User Datagram Protocol) collaboration-based video stream low-delay transmission and real-time decoding rendering method. The method comprises the following steps of: carrying out connection management and signaling interaction; the sending end captures data for coding, and dynamically captures screen content; synchronizing the collected multi-source data according to a timestamp, transmitting the data to an encoder, and preprocessing the data before transmission; a packaged data packet is sent according to a designed transmission protocol, after receiving the data packet, a receiving end analyzes and restores the data packet according to the protocol to obtain data format information, creates and initializes decoder parameters, and then sends a prompt that preparatory work is ready to wait for receiving video stream data to a sending end; video stream data in the data transmission process are transmitted through a TCP, and in the process of rendering and displaying frame data after the video stream data are received by a receiving end, hardware acceleration is performed by using an OpenGL and utilizing a GPU, and decoded frames are displayed on a screen in real time. The method has the advantages of low delay, high reliability, high rendering efficiency, cross-platform compatibility and the like.

The invention discloses a reliable communication system based on a publishing and subscribing mode in a satellite-ground weak network environment, and aims to solve the problems of high round-trip delay, limited link bandwidth, high instantaneous packet loss rate, easiness in blocking and switching influence of links and the like in a data transmission process between a low-orbit satellite and a ground station. A publishing and subscribing model is introduced into an application layer to realize service logic decoupling, deep fusion with an underlying enhanced QUIC transmission protocol is realized, and mechanisms such as message persistence, breakpoint resume, forward error correction and connection migration are combined, so that stable, orderly, complete and safe transmission of service data can still be ensured under the conditions of link instability, quality fluctuation and communication interruption, and the service data transmission efficiency is improved. And high availability and continuity of a satellite-ground communication task under a weak network condition are realized.

The invention discloses a motor working condition monitoring method with a high-speed data transmission capability, and relates to the field of motor operation working condition detection and information transmission. The method comprises the following steps of: synchronously acquiring multi-dimensional time sequence data of a motor under multiple working conditions, and performing data segmentation, standardization, fixed-step downsampling, frequency domain conversion and feature fusion to form a multi-dimensional feature vector; then building a BiLSTM-Attention deep learning model, extracting bidirectional time sequence dependence of the sequence, focusing key time step features, and training to obtain a working condition monitoring model; the monitoring reliability is guaranteed through a dual detection mechanism, and high-speed synchronous transmission of multi-sensor data is realized based on an EtherCAT communication protocol stack. According to the method, through collaborative modeling of multi-dimensional time-frequency feature fusion and a deep learning model, a high-speed synchronous transmission protocol stack and a dual detection mechanism are combined, motor working condition feature expression can be remarkably enhanced, and high-precision data transmission and reliable monitoring can be achieved.

The invention relates to the technical field of data acquisition, in particular to a multi-platform data acquisition method, which comprises the following steps of: detecting hardware and software environments of acquisition equipment; when it is detected that the acquisition devices run in different operating systems and network conditions, data acquisition scripts related to the acquisition devices are generated according to detection results; based on the data acquisition script, starting a protocol plug-in corresponding to each acquisition device, and establishing a communication link with each acquisition device; after the communication link is established, a data acquisition task is started, and the acquired data is subjected to standardization processing and converted into a unified format; the method comprises the following steps: performing primary processing, including filtering and aggregation, on converted data on edge equipment, and transmitting the processed data to a central cloud system for unification through an encryption transmission protocol, thereby being capable of adapting to the universality and compatibility of a data acquisition mode in a multi-platform and multi-equipment environment; and the accuracy and efficiency of data acquisition are improved.

Interactive video game content for a video game is streamed to a client device using a first streaming protocol configured for low-latency streaming. When an indication of non-interactive content to be inserted into the video game is detected, streaming of the interactive video game content to the client device is paused and the non-interactive content is streamed to the client device using a second streaming protocol configured for adaptive bitrate streaming. Upon receiving an indication that streaming of the non-interactive content to the client device has ended, streaming of the interactive content to the client device is resumed using the first streaming protocol.

The invention discloses a multi-dimensional holographic image real-time rendering method and system based on dynamic light field modulation, and relates to the technical field of holographic display, the method is applied to terminal equipment and a server, the terminal equipment determines a space coordinate range based on quantum dot super-structure surface characteristics by obtaining related parameters of a target holographic scene, and the real-time rendering of a holographic image is realized. A quantum dot excitation sequence is generated to regulate and control the micro-nano structure of the super-structure surface, a joint coding model is constructed, a target light field modulation instruction set is generated through optimization, corresponding multi-dimensional light field data is requested from a server, and a holographic scene is generated through processing, fusion and rendering; the server receives the request, calls original holographic data, constructs a coding model and a compression model, and sends multi-dimensional light field data subjected to entropy compression to the terminal through a multi-channel transmission protocol; according to the method, efficient real-time rendering of the multi-dimensional holographic image is achieved, the rendering efficiency and quality are improved, and the method is suitable for scenes with high requirements for real-time performance of the holographic image.

The invention relates to a task processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring data processing tasks from an edge processing node, and acquiring task demand information corresponding to each data processing task; acquiring node state information of each processing node in the computing power network; according to the node state information and task demand information carried by the data processing task, determining a target processing node by taking resource utilization rate maximization of each processing node in the computing power network as a target; determining a target transmission path and a target transmission protocol by taking maximization of transmission bandwidth and minimization of transmission delay as targets according to data size information and time delay requirements carried by the data processing task, and a network state and a transmission protocol of a target processing node; and transmitting the data processing task to the target processing node through the target transmission path and the target transmission protocol. By adopting the method, the task processing efficiency can be improved.

The invention relates to a remote memory read-write method and device based on an RDMA transmission protocol. The method comprises the following steps: creating a virtual character device based on memory information transmitted by a remote node, and mapping the memory information to a local virtual device; when missing page interruption is triggered, distributing a physical memory, initiating an RDMA read request, reading target memory data of a remote node to the physical memory, performing write protection on the target memory data, marking a dirty mark on the target memory data when a process of a user mode modifies the target memory data, and performing write protection on the target memory data; periodically detecting a local physical memory according to a preset time interval, when target memory data carrying a dirty mark is detected, initiating an RDMA write request, writing back the target memory data carrying the dirty mark to a far-end node, and when detecting that the physical memory is overtime, recovering the physical memory; by adopting the method, the data synchronization performance between the local node and the remote node can be accelerated, and the memory utilization efficiency can be improved.