138results about How to "Reduce processing latency" patented technology

The invention relates to the technical field of unmanned aerial vehicles, and discloses an inspection unmanned aerial vehicle flight control management method, which comprises the following steps: step 1, an unmanned aerial vehicle obtains environment three-dimensional point cloud data through a laser radar, captures terrain visual information through an RGB camera and a depth camera, obtains real-time position and attitude information of the unmanned aerial vehicle through a GPS and an inertial measurement unit, and obtains the real-time position and attitude information of the unmanned aerial vehicle; and fusing the collected data to construct a spatial grid map, and taking the grid map as input data of path planning. A high-precision space grid map is generated through three-dimensional environment perception and modeling in combination with an unmanned aerial vehicle multi-sensor fusion technology, and a path is updated in real time by using dynamic environment data, and an air route is planned and optimized, so that path dynamic adjustment and energy consumption minimization of the unmanned aerial vehicle in a complex dynamic environment are realized; and the effects of improving the task execution efficiency, reducing the flight energy consumption and improving the flight safety are achieved.

The invention relates to a task unloading prediction method and device for a power grid processing task, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring an initial strategy network model and an initial value network model, and acquiring sample power grid processing task information and current training environment information; in cooperation with other edge servers and a central cloud server, according to the current training environment information and the sample power grid processing task information, performing centralized training on the initial strategy network model and the initial value network model in the edge servers to obtain a trained target strategy network model; under the condition that a new power grid processing task is received, obtaining current state information of an edge server; and inputting the current state information and the task information of the new power grid processing task into the target strategy network model to obtain task unloading prediction information for the new power grid processing task. By adopting the method, the resource utilization rate can be improved.

The invention discloses a low-delay and high-reliability task unloading and scheduling method in a self-powered mobile edge computing scene. According to the method, efficient unloading and scheduling of tasks are realized by establishing a multi-device and multi-server mobile edge computing system architecture and combining Lyapunov optimization and reinforcement learning algorithms. The system architecture of the invention comprises a base station, a plurality of heterogeneous edge servers with different computing capabilities and a plurality of mobile devices equipped with energy collection modules, and can effectively deal with mobile computing scenes with limited energy. According to the invention, the mobile device obtains renewable energy from the environment through the energy collection module and supplies power to the device. The system is managed in a time slot division mode, and a scheduling period is uniformly divided into a plurality of equal discrete time slots. In each time slot, the system performs task unloading decision and resource scheduling optimization based on the current state to minimize task processing delay and ensure the stability of equipment energy and the reliability of an edge server at the same time.

A moving object real-time three-dimensional reconstruction system based on fringe projection comprises a processing system (PS end) used for communicating with a camera and a projector and managing acquisition and processing of image data; the programmable logic (PL end) is matched with the processing system (PS end) and is specially used for accelerating three-dimensional reconstruction, the programmable logic (PL end) comprises a three-dimensional reconstruction algorithm hardware acceleration unit, and a real-time three-dimensional reconstruction algorithm of a moving object in a dynamic scene is executed in a hardware acceleration mode; wherein the programmable logic (PL end) adopts a streaming computing architecture, the received image data is processed through a cache-free streaming design, the image data is analyzed immediately when each frame of image arrives, and a high-quality moving object real-time three-dimensional reconstruction result is continuously generated. When the method is used for processing three-dimensional reconstruction in a dynamic scene, high precision can be kept, high reconstruction speed can be realized, and challenges on reconstruction precision and reconstruction speed in the prior art are effectively solved.

The invention discloses a flow-based local message classification method and device, and relates to the field of message classification, and the method comprises the steps: carrying out the parallel comparison of a keyword of a to-be-classified message with a keyword temporarily stored in a shift register, obtaining a comparison result, and generating an index matching result through an arbiter according to the comparison result; according to the locality principle of a message flow, historically queried table item information is cached into a dynamic cache table, an arbiter arbitrates a comparison result of a shift register, calculates an offset address of the dynamic cache table and obtains a matching result, and whether an original rule table needs to be queried and whether a dynamic cache table memory needs to be updated are determined according to a search result. Under the condition that the matching is unsuccessful, the dynamic cache table memory can guide the same message to directly use the offset address to obtain the table item information in the next search without searching from an original rule table, so that the hit rate is increased, the matching efficiency is improved, and the storage resources are saved.

The invention discloses a multi-node communication architecture based on RDMA (Remote Direct Memory Access), which comprises the following modules on a network card: a PCIe (Peripheral Component Interconnect Express) function module which supports PCIe x16, is downwards compatible, is used for data interaction between a master control on a local node and an RDMA function module, and supports high-speed transceiving; the MAC module is used for supporting high-speed data transceiving between the RDMA functional module and an external node by using a high-bandwidth MAC; and the RDMA function module is used for realizing a standard RoCEv2 protocol, supporting unicast and multicast, supporting reliable connection service and unreliable datagram service, supporting bilateral send / recv operation, and supporting unilateral write and read operation. The architecture can be used for a multi-core CPU heterogeneous airborne embedded supercomputing platform, realizes lossless Ethernet communication, has the characteristics of low delay, low CPU load and the like, and is used for meeting the application requirements of future airborne comprehensive processing platforms.

The invention discloses a data processing method and system. The method comprises the steps that in response to a data collection instruction of a processing system PS end, collected data are stored in a target cache according to the data type of the collected data, and the target cache belongs to a programmable logic PL end and corresponds to the data type; under the condition that the target cache is full, the collected data are stored in a target memory area according to the data type, and the target memory area belongs to the memory space mounted by the PS end and corresponds to the data type; and in response to the received analysis data, processing is carried out by adopting the target model based on the analysis data to obtain an exception identification result, the analysis data is obtained by analyzing the collected data by the PS end, and the PS end is used for generating an exception processing strategy based on the exception identification result. The technical problem that the data processing efficiency is not ideal in the prior art is solved.

The invention discloses a delay optimization method and system for cooperative video analysis of an unmanned aerial vehicle group, and the method comprises the following steps: constructing an unmanned aerial vehicle cooperative video analysis system comprising a plurality of unmanned aerial vehicles, collecting real-time videos from the ground by each unmanned aerial vehicle, and generating a reasoning task; generating a directed acyclic graph (DAG) for each unmanned aerial vehicle according to the reasoning task, initializing a segmentation point of the DAG of each unmanned aerial vehicle, and performing task unloading at the segmentation point by each unmanned aerial vehicle; and establishing an optimization objective function by taking minimization of task processing delay as an objective, solving the optimization objective function, and updating an unloading decision, communication resource allocation and a DAG segmentation point of each unmanned aerial vehicle according to a solving result. According to the method, the problem of delay minimization of video analysis in the centerless unmanned aerial vehicle group is solved, and task scheduling, communication resource allocation and DAG segmentation point selection can be optimized at the same time.

The invention provides a remote sensing image slicing system and method based on an FPGA (Field Programmable Gate Array). The system comprises a CPU (Central Processing Unit) module and an FPGA module, the CPU module is used for decoding an input original image and transmitting decoded image data and a corresponding first configuration parameter to the FPGA module; the FPGA module comprises an image slicing module and a memory module; the image slicing module is used for segmenting the original image into a plurality of slice images based on the first configuration parameter, and the memory module is used for storing the original image and the generated slice images. A CPU module and an FPGA module are combined, a plurality of image slices can be processed at the same time by means of the parallel computing capacity of an FPGA, and the processing speed and efficiency are improved; and the method has relatively low processing delay and flexibility.

The invention provides a data sharing system and a control method thereof.The data sharing system comprises a shared memory management module, the shared memory management module comprises a resource management pool, and a plurality of shared memory management nodes used for distributing shared memories are arranged in the resource management pool; an index corresponding to a shared memory management node is transmitted to a second application program through a first application program, the second application program generates a file descriptor through the index, and the second application program can directly access a shared memory corresponding to shared memory information after creating mapping through the generated file descriptor. And the generated file descriptor can also be transmitted to the driving program, so that the driving program uses the shared memory corresponding to the shared memory information through the acquired shared memory information, and memory sharing between the plurality of processes and the driving module is realized by using the file descriptor.

The invention provides a sparse system identification method and system based on an improved adaptive filter, and belongs to the technical field of adaptive system identification, and the method comprises the steps: obtaining an input signal at a current moment; updating a correlation estimation matrix and a cross-correlation estimation vector based on a conjugate gradient method; a nonlinear gradient is introduced, and the search direction of the filter is updated; introducing a regularization parameter to obtain a dynamic step length of the filter; updating the tap weight coefficient of the filter; and updating the moment to the next moment, updating the weight vector coefficient of the adaptive filter, and when the weight vector coefficient of the filter is equal to the pulse response of the unknown system, ending the identification of the unknown system. According to the method, the sparse unknown system can be identified more efficiently by modifying nonlinear gradient updating, regularization parameters and momentum enhancement updating.

The invention provides an intelligent recognition method and system for an ultra-large format document based on block parallel. The method comprises the following steps: acquiring image data of a to-be-recognized document; a self-adaptive blocking strategy is adopted, dynamic blocking is conducted according to an available memory of a system or image features, a certain overlapping area is kept between every two adjacent blocks, and then blocking tasks are converted into an asynchronous task queue; using a thread pool to process each block in parallel, or adopting a distributed computing architecture to distribute tasks to a plurality of computing nodes for execution; detecting a text region and a table structure, and performing text recognition on the detected text region through a text recognition model; processing results of all the blocks are collected and combined according to the recorded position information; and performing confidence scoring according to an identification result output by the text identification model to optimize a text region, and performing visualization processing and layout analysis on the optimized text to generate an output result in a standard format.

The invention discloses an after-sales product technical service problem processing method, device and equipment system, relates to the technical field of computers, and solves the problems that the problem processing efficiency is low due to insufficient communication caused by limited experience and frequent personnel replacement when field engineers solve product problems; the method comprises the following steps: submitting product problem information to a server through a mobile terminal, and judging whether the server stores the corresponding product problem information or not; related processing personnel select a processing flow and a related product responsibility unit according to the product problem information, and the responsibility unit edits a problem analysis processing report according to the processing flow; judging whether the problem analysis processing report passes internal verification approval or not; judging whether a corresponding product problem is solved or not; if yes, generating a product problem tracking report, feeding back the product problem tracking report to the server, displaying the product problem tracking report on the mobile terminal, and marking the problem state of the corresponding product as being processed; if not, an early warning signal is sent out; according to the invention, the accuracy and efficiency in the process of processing product problems are improved.

The invention relates to the technical field of delay optimization, in particular to a multi-user cooperative reasoning delay optimization method and device based on the batch processing technology, and the method comprises the steps: obtaining reasoning tasks of a plurality of users, and dividing the reasoning tasks into a plurality of subtasks; traversing the segmentation points of the plurality of subtasks through a target iterative traversal algorithm to find an optimal task segmentation point of the plurality of subtasks, and dividing the plurality of subtasks into a server reasoning subtask and a local reasoning subtask based on the optimal task segmentation point; and calculating the minimum total completion time of the server reasoning sub-task and the local reasoning sub-task based on the actual broadband and the energy constraint condition, and generating a delay optimization strategy of the cooperative reasoning task of the multiple users. According to the method, the task processing delay can be reduced, the system performance of multi-user cooperative reasoning can be effectively improved, the energy consumption of the user equipment can be reduced, the method has relatively high applicability and robustness, and powerful support is provided for application of edge calculation in the fields of Internet of Things and artificial intelligence.

The invention discloses a biasing circuit and a radio frequency power amplifier, and belongs to the technical field of amplifiers. The bias circuit comprises bias control modules which are arranged in one-to-one correspondence with amplifiers at all levels in the radio frequency power amplifier; the bias control module comprises a coupling control unit and a clamping transistor. The coupling control unit is used for filtering the radio-frequency signal of the bias end and then outputting the radio-frequency signal through a second connecting end of the coupling control unit; a parasitic clamping diode is arranged between the control electrode and the first electrode of the clamping transistor, and the parasitic clamping diode is used for chopping a signal of the second connecting end of the coupling control unit, so that the change trend of the direct current component of the voltage of the first electrode of the clamping transistor is the same as the change trend of the envelope amplitude of the radio frequency signal; the voltage of the first electrode of the clamping transistor passes through the coupling control unit and then is provided to the bias end as a bias voltage. According to the embodiment of the invention, the working state of the amplifier is optimized by adjusting the bias voltage in real time.

The invention discloses a rolling data stream digital comparison and coordinate capture device and method based on a comparison tree. The device comprises an input processing module, a subgroup comparison module and a global comparison module, the input processing module is connected with the subgroup comparison module, and the subgroup comparison module is connected with the global comparison module; the input processing module is used for receiving input data, performing bit extension according to parity of the data, triggering a comparison enable signal and providing data to be compared and X coordinate offset information of the data to be compared; the subgroup comparison module is used for carrying out local extreme value judgment on the received data subgroups based on a comparison tree structure and capturing and outputting corresponding coordinate information at the same time; and the global comparison module is used for summarizing the local extreme value information of each data subgroup, and determining the global extreme value of the whole data stream and the corresponding coordinate thereof through a continuous comparison process. According to the method, complete streamlined processing can be realized, and compared with a traditional scheme, the real-time processing requirement can be met, and meanwhile, the hardware design complexity is reduced.

The invention discloses a luggage falling identification system and method for an independent carrying unit of a luggage processing system, and the system is characterized in that the system comprises an image collection unit, an edge calculation unit, an information processing unit, and an alarm prompt unit; the image acquisition unit is used for acquiring image data of a luggage loading node and a plurality of nodes in a luggage conveying process; the edge calculation unit comprises a preprocessing module, a luggage feature recognition module, a character recognition module and a network module; the luggage feature recognition module comprises an input layer, a luggage feature enhancement layer, a backbone network, a feature fusion and attention mechanism layer and a luggage feature prediction head which are connected in sequence; the information processing unit is used for receiving the feature data sent by the edge device, performing deep analysis and comparison, and detecting the luggage falling condition; and the alarm prompt unit is used for detecting the falling of the luggage and immediately notifying related personnel when the luggage falls. According to the invention, through cooperative work of the edge calculation and the background server, a luggage falling event is accurately identified, and an alarm is triggered in time, so that the security and efficiency of the airport luggage processing system are improved.

The invention discloses a signal transmission management system for artificial intelligence stage lamp control, and relates to the technical field of stage lamp control. The system comprises a console, a sending module, a clock module, m concurrent modules and n receiving modules, the output end of the console is connected with the input end of the sending module, the output end of the sending module is connected with the input ends of the m concurrent modules and the input end of the clock module, and the output ends of the concurrent modules are connected with the input ends of all the receiving modules. By executing the first calibration program and the second calibration program, the transmission delay from the console to the stage lamp equipment is reduced, the control instruction is distributed through the concurrent module, the processing delay of the control instruction in the transmission process can be reduced, the execution of the synchronization program is notified, and the control accuracy of the stage lamp equipment is improved under the condition that the stage lamp equipment has control instruction packet loss. And the stage lamp equipment can perform synchronous compensation according to the control instruction of the adjacent receiving module.

The application discloses a video processing method, device, electronic equipment, storage medium and program product. The video processing method comprises: in the decoding stage, reading video frames in a to-be-processed video frame by frame, decoding a video frame to obtain a frame data in an original format after reading each video frame, and transmitting the frame data in the original format to a conversion stage; in the conversion stage, converting the frame data in the original format into frame data in a target format after each time, transmitting the frame data in the target format to an encoding stage; in the encoding stage, encoding the frame data in the target format to obtain semantic representation data, and transmitting at least one frame of semantic representation data to an inference stage; and in the inference stage, inputting at least one frame of semantic representation data to a multi-modal large model for inference to obtain an inference result after obtaining at least one frame of semantic representation data. The application can reduce the occupation of a storage area, reduce processing delay, and improve resource utilization.

The invention relates to the technical field of data communication, and discloses a cloud-side collaborative data distribution system, which comprises a cloud server, edge equipment, a data distribution module and a scheduling module, and is characterized in that the cloud server is used for storing and processing data, the edge equipment is arranged near a data source and is used for receiving, processing and forwarding data, and the data distribution module is used for distributing the data. And the data distribution module is used for realizing efficient flow of data between the cloud server and the edge equipment. According to the cloud edge collaborative data distribution system provided by the invention, the low delay characteristic of edge computing is utilized, the data can be primarily processed and quickly responded on the edge equipment close to the data source, and the waiting time for transmitting the data to the cloud end is shortened, so that the overall processing delay is remarkably reduced, and the processing efficiency is improved. The scheduling module is arranged to dynamically adjust the data distribution strategy according to the real-time data flow, the network condition and the load condition of the edge device, and it is ensured that data can efficiently flow between the cloud server and the edge device.

The invention discloses an uplink service message identification processing method and device, a terminal and a medium. The method comprises the following steps: acquiring core feature information corresponding to an uplink service message; obtaining a target message core data structural body according to the core feature information; obtaining a PDU session identifier corresponding to an uplink service message based on the target message core data structure body; obtaining a QoS flow identifier based on the PDU session identifier and the target message core data structure body; based on the QoS flow identifier, obtaining an uplink service message after scheduling processing; performing query processing on the QoS flow identifier to obtain a target packet data convergence protocol instance; and completing a QoS identification processing flow of the uplink service message based on the target packet data convergence protocol instance. The invention aims to realize rapid QoS identification, classification and processing of the uplink service message, improve the message processing efficiency and accuracy, and reduce the system resource overhead.

The present invention relates to the field of data encryption technology, and specifically, to a wireless transmission storage management system and method for encrypting network-related detection data of new energy stations. It includes: a data acquisition unit, which acquires observation data in new energy stations through a sensor module; a data encryption unit, which encrypts the observation data collected by the data acquisition unit using a dynamic key based on the AES algorithm; a wireless transmission unit, which transmits the encrypted observation data to a receiving and decrypting unit through a wireless network; a receiving and decrypting unit, which receives the encrypted observation data and decrypts the encrypted observation data; a storage management unit, which manages and stores the decrypted observation data to ensure the security and availability of the observation data. Using dynamic key encryption can effectively prevent data from being stolen or tampered with during transmission. Quickly decrypt encrypted data to reduce data processing delays. Ensure data security by verifying storage management policies.

This invention discloses a unified management method and system for provincial and municipal station dispatching, relating to the field of integrated operation and management technology. The method includes: receiving data from provincial and municipal station monitoring equipment, including timestamps, event codes, and associated parameters; analyzing the data to identify data fluctuations; and filtering potential fault signals by comparing historical patterns to obtain initial fault screening results. The unified management method for provincial and municipal station dispatching provided by this invention achieves early identification of fault signals and accurate classification of abnormal patterns by receiving and analyzing data from monitoring equipment. It improves the efficiency and accuracy of data analysis by comparing real-time and historical data, accelerates fault detection and enhances the handling capability of complex abnormal situations by identifying data changes in different time periods, sets alarm response times and processing priorities for different anomaly types to improve emergency response efficiency, optimizes network traffic management strategies and data transmission paths, reduces processing latency, improves network performance and stability, and effectively enhances operational efficiency and user experience.

The invention relates to the technical field of instant messaging, in particular to a doctor-patient platform instant messaging method and system, and the method comprises the steps: starting a doctor-patient instant messaging application, carrying out the identity verification, obtaining a verification parameter, judging whether the identity verification succeeds or not according to the verification parameter, and if the identity verification succeeds, defining an identification content field and a message content field, and pulling historical data; the method comprises the following steps of: constructing a display format set, updating data, obtaining updated data, sending real-time data, encrypting the data, generating a signature, obtaining encrypted data, verifying a signature packet, sending the data, calculating transmission delay, judging whether the transmission delay is in a delay range or not, and if the transmission delay is not in the delay range, sending the signature packet. If the transmission delay is within the delay range, self-adaptive adjustment is carried out, verification is carried out according to the verification signature packet to obtain verification data, and if the transmission delay is within the delay range, verification is carried out according to the verification signature packet to obtain verification data to complete communication. According to the invention, the security and privacy of doctor-patient communication can be improved.

This invention discloses a visual monitoring system and method for arc additive manufacturing equipment, relating to the field of visual monitoring. In this system, the host computer is used by the operator to calibrate the CCD camera, acquire monitoring data, and provides a unified interface for interaction. The PS terminal receives start commands and CCD camera calibration commands from the host computer, and sends program functions to the host computer to obtain the molten pool width, molten pool center point coordinates, molten pool collapse amount, and collapse direction obtained through CCD camera monitoring. It is also used to store the original molten pool image at a fixed location in the off-chip DDR3 memory. The PL terminal receives control commands from the PS terminal to the IP cores in the PL terminal. The CCD camera is used to acquire the original molten pool image. The LCD screen communicates with the PL terminal through a TFTLCD interface. This invention can improve the real-time performance of the monitoring system and reduce costs.

The invention discloses a multi-source heterogeneous data pollution traceability and management system based on end-edge-cloud collaboration. The system comprises a multi-source heterogeneous data acquisition module, a cloud-edge collaboration data management and control module, an environment traceability graph embedded sensing module, an interpretable traceability analysis module, a closed-loop regulation and control decision module and a pollution abatement feedback module. A sensing end multi-dimensional sensor collects various types of data, edge end preprocessing and cloud deep analysis cooperation are carried out, an abnormal sensing algorithm is embedded based on an environment traceability graph, a dynamic pollution source identification mechanism is constructed by an interpretable environment pollution traceability analysis model, and a strategy is adjusted in combination with a data pollution closed-loop regulation and control decision model. And the links of early warning, patrol, traceability, disposal and feedback are covered. According to the system, the robustness and maintainability of a multi-source data system are improved, rapid response, accurate traceability and intelligent closed-loop management of pollution events are realized, the problems of insufficient monitoring data collaboration and poor traceability treatment closed-loop performance are effectively solved, and the fine management requirement of environment monitoring is met.

This invention relates to a robust image semantic perception adaptive masking transmission method for vehicle-to-everything (V2X) networks, comprising: Step 1: The transmitting end performs semantic analysis on the original input image, extracts high-precision semantic features, and identifies the regions of interest (ROI) and non-ROI regions of interest (NROI); Step 2: A Boolean mask is dynamically generated based on the semantic segmentation result and SNR; Step 3: The ROI features are directly masked based on the Boolean mask; Subsequently, the processed feature map is fed into a semantic encoder to extract multi-scale semantic features; Step 4: Power normalization is performed, dynamic feature encoding is performed, and then the encoded signal is transmitted through a typical analog wireless channel, and noise is superimposed before reception and recovery; Step 5: The receiving end receives the noisy feature signal, performs channel fading compensation and preliminary denoising, and sends the decoded features into a semantic decoder; Through progressive upsampling and multi-level semantic reconstruction, multi-scale features are fused, and finally, a high-quality reconstructed image is recovered and output.

The application provides a kind of based on edge computing and big data's wisdom campus safety early warning method and system. Through edge computing node, real-time collection is carried out to multiple video data streams, frame sequence segmentation and space-time feature extraction are carried out, initial behavior feature set is generated, initial behavior feature set is carried out multidimensional correlation analysis based on preset behavior semantic label, space-time behavior feature vector corresponding to target monitoring scene is extracted, and is transmitted to central server, space-time behavior feature vector is input into target behavior identification model, behavior semantic description sequence corresponding to video data stream is generated, and according to its matching result with preset abnormal behavior rule library, real-time behavior monitoring result is determined, real-time behavior monitoring result is received by edge computing node, and based on dynamic priority strategy, the collection parameters of video data stream are adaptively adjusted.The application can improve the real-time performance, accuracy and system sustainability of campus behavior monitoring.

This invention discloses a parallel optimization system for massive video processing. The system adopts a four-layer integrated parallel and collaborative processing architecture, comprising, from top to bottom: a parallel task layer for video stream access, grouping, splitting, encapsulation, and queue management; a resource abstraction layer for unified hardware modeling, status acquisition, topology construction, and capability assessment; a parallel scheduling layer for task-hardware matching, load balancing, priority scheduling, and dynamic adjustment; and an execution optimization layer for data stream localization, parallel read / write, cache optimization, and zero-copy processing. The parallel task layer, resource abstraction layer, parallel scheduling layer, and execution optimization layer form a complete parallel processing link: task input, resource awareness, accurate scheduling, and optimized execution. This invention implements concurrent rate limiting and smooth access for the input video stream to prevent traffic surges; and sets synchronization points and timing control for parallel tasks to ensure orderly output.

The present invention provides a method for realizing a two-step mode of a precision time protocol transparent clock, which comprises: S1: when a PTP message is detected on a PHY / MAC, an arrival timestamp IngressTs is recorded, and the process proceeds to step S2; S2: the PTP message is parsed by a switching chip, and it is determined whether it is a Sync or DelayReq message, if it is, the message feature information and the residence time are stored in a FIFO of the switching chip, and the exit PHY / MAC records the departure timestamp EgressTs in the FIFO of the switching chip, and then the process proceeds to step S4, otherwise, the process proceeds to step S3; S3: the switching chip is determined whether the PTP message is a FollowUp or DelayResp message, if it is, the FIFO is searched according to the message feature information to obtain the residence time, and the residence time is modified to the message correction domain, and then the processed PTP message is forwarded to the PHY / MAC and the process proceeds to step S4, otherwise, the switching chip directly forwards the PTP message to the exit PHY / MAC, and the process proceeds to step S4; S4: the message is sent through the exit PHY / MAC.