745results about How to "Improve data transfer efficiency" patented technology

The invention discloses a cloud edge cooperative control method, which comprises the following steps: establishing a cloud edge cooperative architecture, collecting data by edge nodes, and selecting a corresponding data compression strategy to compress the data; generating an edge-cloud collaborative uploading data stream; the cooperative control layer executes adaptive load balancing based on a cloud-side node state, task characteristics and a network condition which are monitored in real time so as to realize task allocation and scheduling between the cloud and the side; the cloud receives the data stream transmitted by the edge node, decompresses and processes the compressed data according to the metadata information, completes the task and feeds back an execution result; a node performance prediction model is constructed by using system state monitoring information, a task allocation strategy and a resource allocation and data compression strategy are adjusted in real time according to a prediction result, and cloud-side collaborative optimization is realized. Efficient data transmission, flexible task scheduling and self-adaptive resource management are realized, and the performance of the system in a complex and changeable environment is comprehensively improved.

The invention provides a private domain live broadcast room hotspot prediction and adaptive routing method based on swarm intelligence, and relates to the technical field of data processing, and the method comprises the steps: constructing a dynamic interest community through a dynamic graph neural network, extracting group interaction mode features through a multi-layer graph attention network, and carrying out the group interaction mode features; the method comprises the following steps: generating time sequence correlation features in combination with an improved bidirectional gating loop unit, extracting high-order semantic features, performing hotspot prediction through a multi-task learning framework, constructing a multi-level network topology model according to a prediction result, and performing path exploration in combination with an improved heuristic search algorithm to obtain an optimal transmission path. Flow distribution is carried out through a weighted polling algorithm, a deep learning distributed load balancing controller and a congestion control algorithm are combined, the data transmission rate is dynamically adjusted, and self-adaptive routing pushing of live broadcast content is achieved.

The invention discloses a data cooperative transmission method and system for a low earth orbit satellite Internet of Things terminal, and the method specifically comprises the steps: carrying out the classification cutting of environment data, and forming a plurality of environment data subsets; determining a plurality of cooperative sending terminals and respective optimal communication paths between the first low earth orbit satellite Internet of Things terminal and each cooperative sending terminal based on a communication topological structure relationship between the low earth orbit satellite Internet of Things terminals in the ad hoc network; transmitting the environment data subsets with different priorities to corresponding cooperative sending terminals through different optimal communication paths; and according to the environment data subsets sent by each cooperative sending terminal and received by the low-orbit satellite, splicing the environment data subsets and forwarding the spliced environment data subsets to a target terminal or a ground station or a data center. According to the invention, the cooperative effect among a plurality of low-orbit satellite Internet of Things terminals can be fully utilized, and stable and reliable data transmission under the requirements of large data volume and high real-time performance is realized.

The invention provides a low-altitude industry chain information intelligent cooperation and airspace management platform based on federal learning. Through cluster ad hoc network and decentralized federated learning, the method is divided into three stages of data acquisition, data preprocessing and analysis application, low-altitude scene data communication of dynamic topology and static topology is realized, and the efficient communication requirement in a low-altitude operation scene is met. According to the system, differential data transmission strategies are adopted, optimization design is carried out on a single machine, a co-task cluster, a cooperative cluster and a non-cooperative cluster, and the communication efficiency and the resource utilization rate are improved. In the data preprocessing stage, federated learning aggregation of multi-source data fusion, data anonymization and decentralization is combined, and data privacy protection and safe sharing of three parties of industry, university and research are ensured. In the analysis and application stage, low-altitude aircraft task scheduling, airspace flow control and environmental condition evaluation are realized through aircraft analysis, airspace analysis, environmental analysis and digital twinborn technologies.

The invention provides a resource scheduling method and system for a converged network, an intelligent terminal and a medium, and particularly relates to the technical field of network communication, and the scheme comprises the steps: carrying out the priority division and sorting of target data collected in real time according to a preset priority evaluation strategy through employing a 5G network, and obtaining the target data with the marked priority; performing time synchronization processing on all the target data marked with the priorities by using the TSN equipment to obtain the target data after time synchronization; and according to the priority and the current network state, carrying out dynamic resource allocation on the target data after time synchronization, obtaining a resource allocation result and executing a resource scheduling operation. According to the scheme, priority scheduling and a time synchronization strategy are combined based on the 5G-TSN fusion network, priority processing and accurate time synchronization of key data are ensured, the reliability and effectiveness of data transmission can be improved, bandwidth allocation is dynamically adjusted according to the data priority, and the accuracy of data resource scheduling and the data transmission efficiency can be improved.

The invention provides a sewage treatment operation cloud platform based on Internet of Things and GIS, and the platform is characterized in that a data collection layer is used for obtaining user water consumption data and sewage pipe network data, and distributing all the data to each edge calculation node; the data storage layer is used for temporarily storing the data preprocessed by the edge computing node into a high-frequency storage chain, aggregating to obtain sewage pipe network comprehensive data, and permanently storing the sewage pipe network comprehensive data into a low-frequency storage chain; the data analysis layer is used for extracting sewage pipe network comprehensive data in the low-frequency storage chain, constructing a multi-dimensional dynamic GIS model by utilizing a GIS system, analyzing and predicting the multi-dimensional dynamic GIS model through a sewage treatment rectification analysis model, and generating a sewage treatment rectification plan of the sewage pipe network according to an analysis and prediction result; and the application service layer is used for acquiring all the sewage treatment and rectification plans and distributing all the sewage treatment and rectification plans to a management client held by a sewage pipe network manager. The sewage treatment device has the effect of efficiently and intelligently realizing sewage treatment.

The invention relates to the technical field of sensor upgrading, in particular to a remote upgrading method and system for a tire pressure sensor. The method comprises the following steps: acquiring real-time state data of a tire pressure sensor; carrying out outlier parameter elimination on the real-time state data of the tire pressure sensor, and carrying out state diagnosis mining, so as to generate a state diagnosis report of the tire pressure sensor; performing upgrade demand prediction based on the tire pressure sensor state diagnosis report, and performing priority upgrade analysis to extract a plurality of upgradable sensors; performing byte-by-byte difference identification on the plurality of upgradable sensors based on preset latest version information, and performing incremental data encapsulation to generate a plurality of incremental upgrading data blocks; acquiring a historical running log of the vehicle; performing dynamic vehicle using behavior analysis and vehicle idle time period prediction on the vehicle historical operation log to generate a plurality of idle prediction time periods; the upgrading efficiency and the safety performance of the tire pressure sensor are improved.

The invention discloses a multi-link fusion method and system based on an SD-WAN (Secure Digital Wireless Area Network) technology, which can timely discover and deal with the condition of network failure or performance reduction by monitoring network state parameters of a plurality of network links in real time, and is helpful for ensuring reliable network connection at any time point, thereby improving the reliability and the stability of the network, and improving the reliability and the reliability of the network. By dynamically adjusting distribution of data traffic, the optimal link combination can be selected for data transmission, so that congestion is avoided, delay is reduced, the packet loss rate is reduced, the utilization rate of network bandwidth is maximized, the data transmission efficiency is remarkably improved, the routing optimization step can quickly respond to service changes by utilizing flexibility and programmability of the SDN technology, and the service quality is improved. According to the method, the continuity and the high efficiency of services are ensured by optimizing data transmission routes, existing network resources can be fully utilized through multi-link fusion and intelligent scheduling, excessive dependence on a single link or an expensive high-performance link is avoided, and reduction of network construction and operation and maintenance cost is facilitated.

The invention provides a CT acquisition control communication system and method based on hybrid networking of multiple communication modes. The CT acquisition control communication system comprises a CT stator part communication subsystem, a CT rotor part communication subsystem and a master control PC. The master control PC comprises an upper computer, is operated through a visual interface and is responsible for task scheduling, scanning protocol setting, parameter configuration, data processing, patient registration, working state monitoring and image reconstruction of the whole system; the CT stator part communication subsystem comprises a lower computer core control module, a first WIFI module, a first switch, a rack control module, a patient bed control module, a power management module and a control handle; and the CT rotor part communication subsystem comprises a data acquisition and pay-off control module, a second WIFI module, a second switch, a collimator control module and a detector data acquisition and processing module. According to the invention, the overall communication efficiency and stability of the CT system and the expandability of the communication network can be improved, and the later maintenance cost of the communication system is reduced.

A CAE simulation result visualization system supporting multiple interaction modes comprises a multi-resolution rendering module used for obtaining interaction behaviors of a user and dynamically adjusting the resolution of a rendering area according to the interaction behaviors of the user; the key frame and time step screening module is used for analyzing the input simulation data, automatically screening out key frames and detecting the time step change of the simulation data according to a time sequence analysis method; the data compression and simplification module is used for compressing the data by using a feature-preserving compression algorithm, performing incremental storage and sparse representation on the compressed data, and recording data changes; and the dynamic local playing and frame-skipping rendering module is used for acquiring a user local time playing instruction, and processing user local time and non-user local time respectively through a frame-skipping rendering method so as to realize multi-frame rendering and switching. According to the method, the data analysis efficiency is improved, the rendering and data transmission efficiency is improved, and computing resources are saved.

The invention discloses a protocol method for realizing intelligent connection of a PLC (Programmable Logic Controller) with an AI (Artificial Intelligence) large model, which relates to the technical field of industrial automation, and comprises the following steps: in a PLC system, configuring an MCP client module by defining basic parameters of an MCP, and embedding a context management module in the MCP, the basic parameters comprising a data format, a communication protocol and a security mechanism; and establishing a bidirectional communication channel between the PLC and the AI system based on the configured MCP client module. According to the protocol method for intelligently connecting the PLC with the AI large model, seamless connection between the PLC and the AI system is achieved by defining a unified data format, a communication protocol and a security mechanism, the complexity and the error rate of data transmission are reduced, the overall data transmission efficiency is improved, and the method is suitable for popularization and application. The context management module embedded in the MCP can store and manage historical data, so that the AI system can make intelligent decisions based on comprehensive data, and the accuracy is improved.

The invention discloses a meat product foreign matter on-line detection method and system, and belongs to the field of visual detection.The detection method comprises the steps that a fixed detection area is set, a multi-mode sensor is installed above the fixed detection area, and the multi-mode sensor collects data and transmits the data to a data processing center through a wireless network; the data processing center decompresses and preprocesses the received data and fuses the image data twice to obtain a final fused image; according to the feature information in the final fusion, extracting fusion feature data; analyzing the feature data by using a support vector machine, and judging whether foreign matters exist or not and classifying the types of the foreign matters; a detection result is fed back to a production line control system in real time, and meat products containing foreign matters are positioned and removed. According to the method, the multi-mode sensor and an efficient data analysis technology are combined, and the accuracy and the real-time performance of meat product foreign matter detection are effectively improved.

The invention relates to the technical field of computers, and provides a high-speed data transmission method for micro-computing equipment, which comprises the following steps of: acquiring to-be-transmitted data of the micro-computing equipment, identifying the characteristics of the to-be-transmitted data, analyzing a transmission mode, determining a data priority, analyzing hardware configuration information based on the data priority, and detecting the performance of a data transmission interface. The method comprises the following steps: calculating an interface transmission rate and evaluating transmission quality to formulate a data transmission strategy, partitioning data, analyzing a transmission sequence, constructing a transmission time window, monitoring a window state to construct a high-speed transmission path, identifying a transmission node, analyzing a transmission index of the transmission node, and finally generating a data transmission scheme based on the transmission index. According to the invention, the data transmission efficiency of the micro-computing device can be improved.

The invention discloses an adaptive link construction method and system based on an OSPF (Open Shortest Path First) and oriented to a QoS (Quality of Service) demand, and the method comprises the following steps: announcing an LSA (Link State Advertisement) message by expanding the link state of the OSPF, and integrating QoS parameter information of a link into the LSA message; an SPF algorithm is used for dynamically adjusting the weight coefficient of a calculation formula through multiple times of calculation according to different limitations and priority requirements of a service on bandwidth, time delay and channels, and finally an optimal path meeting the QoS requirement of a user is obtained; the method comprises the following steps: compressing quintuple information of a service into a chain identifier by using a mechanism based on a link identifier, periodically packaging the chain identifier into a maintenance message, sending the maintenance message to each node on a path so as to monitor a link state, and quickly reestablishing a link when the link fails; the special link data flow is identified through the protocol type field of the Ethernet frame header, so that the analysis overhead of the three-layer message is avoided. According to the method, expansion is only carried out on the basis of the OSPF protocol, the existing network does not need to be transformed on a large scale, and the method has good practicability and deployability.

The invention provides a data transmission method and device, a storage medium and electronic equipment, and relates to the technical field of Internet of Things. The method comprises the following steps: caching and merging data packets of a plurality of nodes, and determining a transmission message; sending the transmission message to a target receiving end through a first transmission path, and predicting a congestion state of the first transmission path; and according to the predicted congestion state of the first transmission path, determining whether to send the transmission message to the target receiving end through a second transmission path. The data packets of a plurality of nodes are cached and merged to generate a single transmission message, so that the number of the data packets transmitted in a network can be remarkably reduced, and the data transmission efficiency is improved; the congestion prediction is performed on the first transmission path, the second transmission path is planned in advance before the first transmission path is congested, and when the first transmission path is congested, the second transmission path is switched, so that the time required for reconfiguring the network topology after the congestion occurs is reduced.

The invention discloses an artificial intelligence big data processing and management system and a data acquisition module, belongs to the field of big data processing, and comprises a data acquisition module, a preprocessing distribution module and a data analysis module. The method comprises the following steps: performing data acquisition on a plurality of data sources, and monitoring a data acquisition process to obtain logs and data acquisition time; preprocessing and privacy judgment are carried out on received collected data by utilizing a trained random forest model, and metadata is uploaded to a private chain or a public chain according to a label in a judgment result; an original data set is grouped by constructing a K-Means clustering algorithm model, the similar distance between each feature vector and a cluster center is calculated, and the consistency of a clustering result and real classification is evaluated; by analyzing the data transmission process, the data transmission interference ratio and the data transmission rate are obtained, and the data transmission effect is evaluated.

The invention discloses a hydrological RTU (remote terminal unit) monitoring method capable of operating under a severe working condition, and particularly relates to the field of environmental monitoring, and a fault prediction method comprises the following steps: S1, collecting data of each sensor in real time, carrying out denoising processing on the data by using a moving average method and Kalman filtering, and carrying out standardization processing on the data by adopting a standard score and minimum-maximum standardization; s2, vectorizing the data of each sensor, and generating a feature vector by using a pre-training embedding model and an auto-encoder; according to data prediction and anomaly detection, data change is predicted through RNN or LSTM, prediction deviation is calculated and normalized, anomaly detection is performed by using a maximum deviation value, the running state of the system can be monitored in real time, abnormal conditions can be found and processed in time, and stable running of the system is ensured. In conclusion, according to the method, through combination of multiple technical means, the operation stability and the data processing accuracy of the hydrological RTU under the severe working condition are remarkably improved, and the method has remarkable practical value.

The embodiment of the invention provides a data transmission method and device of a network-on-chip, electronic equipment and a storage medium. The method comprises the following steps: dividing at least two computing nodes with spatial topology into multicast domains; determining a target node for receiving the first message; according to a target multicast domain to which the target node belongs, adding a multicast control field in the first message to obtain a target message; determining a first routing path outside the target multicast domain according to the multicast control field and a routing algorithm; transmitting the target message to the target multicast domain based on the first routing path; determining a second routing path in the target multicast domain according to the intra-domain mask field; and sending the target message to the target node based on the second routing path. In the embodiment of the invention, the routing path of each message can be directly determined according to the multicast control field added in the message, so that the design complexity of the network-on-chip is reduced, and the data payload proportion and the data transmission efficiency of the network-on-chip are improved.

The invention belongs to the field of chip design, and provides a packet bus interconnection architecture of an SoC system, which comprises a system bus matrix SYSBUSMatrix, at least one processor bus matrix CBM, at least one high-speed peripheral bus matrix HPBM, at least one memory bus matrix RBM and one low-speed peripheral bus matrix SPBM, the CBM, the HPBM, the RBM and the SPBM are all connected with the SYSBUSMatrix through a bus bridge; the embedded processor is mounted on the CBM, and meanwhile, the CBM is connected with the RMB; a high-speed peripheral is mounted on the HPBM, and meanwhile, the HPBM is connected with the RMB; a random access memory (RAM) is mounted on the RBM, and meanwhile, the RBM is connected with the CBM and the HPBM; the SPBM is connected with a plurality of paths of AHB buses through an AXI-AHB bridge, the SPBM is connected with a plurality of paths of APB buses through an AXI-APB bridge, meanwhile, the SPBM is connected with SYSBUSMatrix, and a plurality of paths of low-speed peripherals are mounted on the AHB buses or the APB buses. According to the method, bus transmission among modules such as a processor, a high-speed peripheral and a storage can be balanced, bus competition among high-speed interfaces is effectively reduced, data transmission efficiency is improved, chip rear-end implementation is simplified, and therefore the performance of the whole SOC is optimized.

The invention discloses a data transmission and control method and system based on a Beidou short message, and relates to the technical field of remote monitoring and communication, and the method comprises the steps: a Beidou slave station receives remote signaling and telemetering data, carries out the data processing of the received data, packages the data into a Beidou short message format, carries out the data transmission through a multi-mode command transmission protocol, and carries out the data transmission through a Beidou short message transmission protocol; the method comprises the following steps: receiving command data converted by a Beidou master station, monitoring a system in real time through a command execution state, feeding back an execution progress and state to the master station in real time, automatically executing a recovery process through a fault self-healing mechanism when data transmission is abnormal, and automatically adjusting data transmission frequency and power by utilizing a self-adaptive energy management algorithm, so as to realize real-time data transmission. And through the data transmission prediction model, predicting a data transmission demand, and adjusting a data refreshing strategy in advance. Through the adaptive energy management algorithm and the prediction model, the data transmission frequency and power are dynamically adjusted, the energy consumption is optimized, and the data transmission efficiency and real-time performance are improved.

The invention provides an unmanned aerial vehicle control link system and method, the unmanned aerial vehicle control link system comprises an unmanned aerial vehicle end control module, a ground station control module and a communication link module, and the communication link module is a multi-link redundant communication link module; the ground station control module is used for generating a control instruction and sending the control instruction to the unmanned aerial vehicle end control module through the communication link module; and the unmanned aerial vehicle end control module is used for receiving the control instruction of the ground station control module and controlling the flight and task execution of the unmanned aerial vehicle. According to the technical scheme, by adopting the multi-link redundancy design, the stability and reliability of a communication link are improved, and continuous control of the unmanned aerial vehicle in a complex environment is ensured.

The invention relates to the technical field of load balancing, in particular to a cluster-based load balancing implementation method, which comprises the following steps of: S1, defining load balancing requirements and targets; s2, selecting a load balancer; s3, deploying a load balancer; s4, configuring a server pool; s5, realizing a load balancing algorithm; s6, realizing a fault-tolerant processing mechanism; s7, a monitoring and alarming system; s8, recording and analyzing logs; s9, performing regular maintenance and optimization; and S10, continuously improving. The cluster internal network topology structure is optimized through the network optimization module, the data transmission efficiency and the response speed are improved, the system performance and the user experience are improved through the load balancer, the safety protection module, the prediction module and the data processing transmission module, and the stability and the performance of the whole system are improved. The higher disaster recovery capability is realized through the load balancing architecture module, the more accurate load distribution is realized through the algorithm processing module, the load balancing strategy is adjusted in advance through the load balancing adjustment module, and the intelligence is improved.

The invention discloses an unmanned aerial vehicle airborne control method and system with an RTK accurate positioning function, and the method comprises the steps: obtaining an air route task, and obtaining the position of an RTK module disposed on an airborne device; based on the position of the RTK module, a deviation value between the position of the unmanned aerial vehicle and the position of the RTK module is calculated, and positioning correction is carried out; and taking the corrected positioning value as real-time position information of the unmanned aerial vehicle, and combining with an intelligent inspection route to ensure that the unmanned aerial vehicle arrives at a specified waypoint to take a picture. Transmission and control between the background and the unmanned aerial vehicle are realized, equipment dependence is reduced, communication stability is improved, flight safety is enhanced, data transmission efficiency is improved, and maintenance cost is reduced.

The invention relates to the technical field of data processing, and discloses an esophageal cancer patient nursing remote monitoring system and method capable of improving the nursing level, and the system comprises a data collection module, a personalized data transmission module, a remote monitoring center and a remote service module. The personalized data transmission module is used for predicting potential key data of a patient by using a collaborative recommendation algorithm, distributing corresponding personalized transmission parameters to the potential key data and non-potential key data in the monitoring data, and transmitting the monitoring data to the patient based on a 5G communication technology and the corresponding personalized transmission parameters; the potential key data and the non-potential key data are transmitted to a remote monitoring center; and the remote monitoring center is used for receiving the monitoring data and performing remote monitoring analysis on the nursing condition according to the monitoring data. According to the method, the doctor seeing burden of the patient can be relieved, medical staff can obtain key data in the first time, a more appropriate treatment scheme is formulated for the patient, and therefore the overall medical care level is improved.

The embodiment of the invention provides a data storage method and device in a direct connection mode, electronic equipment and a computer readable storage medium, and relates to the technical field of video transmission. Comprising the following steps: receiving a pixel value and first address information of a first pixel; determining a first physical storage address of the first pixel in a memory, a first target strip to which the first pixel belongs and a target matrix corresponding to the first target strip; determining a first target address block to which the first physical storage address belongs, a first position of an identifier of the first target address block in the initial address block matrix, and a second position of the first physical storage address in the first target address block; and determining a second target address block corresponding to the first position in the target matrix corresponding to the first target strip, and storing the pixel value of the first pixel in a physical storage address corresponding to the second position in the second target address block. According to the embodiment of the invention, the data transmission efficiency in the direct mode is improved, and the consumption of physical resources is reduced.

The invention relates to the technical field of Internet of Things, in particular to an Internet of Things intelligent linkage control method and an Internet of Things intelligent linkage control device, and the method comprises the steps: S1, obtaining the working state of home equipment and the real-time data of environment information, and transmitting the real-time data to a central control platform; s2, preprocessing the real-time data to obtain preprocessed data; s3, analyzing the preprocessed data, and generating a corresponding linkage control instruction; s4, encoding the linkage control instruction to generate encoded data, and performing lossless compression on the encoded data by adopting a ZSTD compression algorithm to obtain a compressed code; s5, searching an optimal sending communication network by adopting a flora optimization algorithm, and sending the compressed code to the home equipment; and S6, the home equipment decompresses the compressed code by using an LZMA compression algorithm, and executes the linkage control instruction. According to the invention, the ZSTD compression algorithm and the flora optimization algorithm are adopted, the delay of data transmission and processing is significantly reduced, the overall response speed of the smart home system is improved, and the user experience is better.

According to the model training-oriented gradient data transmission method and the related equipment provided by the invention, the compression ratio is dynamically determined according to the change of the transmission rate by monitoring the transmission rate in real time, so that the gradient data can be intelligently compressed according to the compression ratio, the data transmission quantity is remarkably reduced, and the network burden is relieved; and meanwhile, the transmission rate of each working end is adjusted through congestion control according to the bandwidth of a transmission link between the switch and the parameter server so as to relieve congestion. Under the combined action of the two, the transmission time of the gradient data is remarkably shortened, and the data transmission efficiency is improved, so that the training process of the distributed artificial intelligence model is accelerated, and the overall training efficiency is improved.

The embodiments of the present invention relate to the field of communications, and disclose a slave channel access method, an electronic device, and a storage medium. The method includes: after determining that a terminal has the slave channel access capability, negotiating slave channel access with the terminal, and reaching a consensus with the terminal on the slave channel access method; when the main channel is unavailable or busy, determining whether there is an idle slave channel in the slave channels that have reached a consensus with the terminal on the slave channel access method; sending MU‑RTS to the terminal on the determined idle slave channel; receiving CTS sent by the terminal on the slave channel indicated by the MU‑RTS or on the slave channel determined according to specific rules. The embodiments of the present invention improve the channel utilization rate of the terminal when transmitting data in MU‑MIMO and OFDMA modes by using slave channel access to transmit data when the main channel is busy.

The invention relates to a multichannel PCM data real-time acquisition and output system and method based on an ALSA framework, and the system comprises a multichannel analog quantity input unit and a multichannel analog quantity output unit, and also comprises a system configuration unit, a memory resource unit, an AD acquisition conversion unit, an audio routing unit, a DA output conversion unit and an ALSA DMA cache region distribution unit. The ALSA DMA cache region allocation unit is used for building a PCM data path of a user space and a kernel space and providing an annular cache region queue for storing DMA resource descriptors, and the audio routing unit obtains the returned DMA resource descriptors from the ALSA DMA cache region allocation unit and allocates the DMA resource descriptors to an output end to complete synchronous multichannel input and output of PCM data. According to the system provided by the invention, the ALSA DMA buffer area distribution unit is adopted, so that the DMA configuration process is simplified, and the data transmission efficiency is improved.

The invention relates to the field of hardware control, and provides a device and method for outputting a running log of a basic input / output system based on a virtual serial port, and the device comprises a substrate management controller which is provided with a first virtual serial port control module, the receiving module is used for receiving serial port data sent by a host through an enhanced serial peripheral interface bus; a first virtual serial port driving module and a second virtual serial port control module are arranged on a south bridge chip of the host, and the first virtual serial port driving module is used for sending operation log information to the first virtual serial port control module through an enhanced serial peripheral interface bus; the second virtual serial port control module is used for outputting the running log information to a text file under the universal serial bus flash disk when the existence of the universal serial bus flash disk is detected; and the enhanced serial peripheral interface bus is connected between the first virtual serial port control module and the first virtual serial port driving module and is used for mutually transmitting data between the first virtual serial port control module and the first virtual serial port driving module.