1894 results about "Web transport" patented technology

The invention provides a multi-network integration ship-shore communication system and an intelligent ship remote driving control system based on a ship Internet of Things, and the hardware part of the multi-network integration ship-shore communication system comprises an integrated circuit board, a power module, an edge calculation module, a communication module, and an extensible communication interface, wherein the power module, the edge calculation module, the communication module, and the extensible communication interface are installed on the integrated circuit board. The communication module comprises a 4G / 5G communication module and / or a satellite module and / or a microwave module and / or a VHF module and / or an AIS module and / or a Beidou satellite module, the edge calculation module is connected with the power supply module, the communication module and the extensible communication interface, and the software part comprises a multi-network integration management software module. And the multi-network integration management software module is installed in the edge computing module. The method has the advantages that the multi-link aggregation system is used, the network transmission rate and stability are improved in the application scene of ship inland river shipping, complementation with a satellite communication system can be formed, and the service stability is further enhanced.

The invention relates to the technical field of cloud side end computing, and discloses a cloud side end cooperative computing resource dynamic allocation method based on task-aware migration. The method comprises the following steps: acquiring real-time load characteristics and resource demand characteristics of calculation tasks in a cloud side end system, and dividing task priority queues in combination with task type identifiers; extracting historical execution records of tasks at cloud, edges and terminal nodes, constructing a task execution feature library, and generating a resource demand prediction model in combination with real-time load features; analyzing network transmission time delay characteristics of a cloud end and edge nodes, measuring real-time calculation capability fluctuation data of terminal equipment, and establishing an inter-node resource collaboration degree evaluation matrix; generating an initial migration strategy according to the prediction model and the evaluation matrix, monitoring actual resource occupancy deviation of the task, forming a final decision in combination with a node resource state correction strategy, triggering cross-node migration, and synchronously updating the priority queue and the evaluation matrix.

The invention relates to a feature defense method and system in a network transmission process, and the method comprises the steps: intercepting a network transmission data flow in a migration channel of a virtual machine in real time, and building a bidirectional flow mirror image pipeline; performing deep protocol analysis and recombination on the original transmission message in the mirror image pipeline to obtain a structured traffic log of complete load information and metadata labels; based on a preset traffic feature set, extracting a memory paging transmission time sequence feature and a disk data block check code distribution feature from the structured traffic log, and constructing a first detection sub-vector; according to the invention, a high-precision virtual machine migration security protection system is realized.

The invention provides a resource scheduling control method and system for a big data server, and the method comprises the steps: constructing a multi-dimensional resource portrait module, collecting the CPU, memory, network, storage I / O load and task queue length of each node in real time, and predicting a resource demand trend through a time sequence algorithm; extracting characteristics such as calculation intensity, data dependence, memory requirements, network transmission quantity and the like; adjusting the weight coefficients of the resource utilization rate, the task completion time and the energy consumption efficiency according to the system load and the historical effect; establishing a bipartite graph model by taking a resource trend as a node feature and a task vector as an edge feature, and calculating a matching score through graph convolution and a multi-objective optimization function; the scheduling scheme is synchronized by adopting a consistency algorithm; automatic rollback and reallocation are carried out when resources are detected to be insufficient; and optimizing a weight coefficient and a network parameter through reinforcement learning. Through the method, the system resource utilization rate can be improved, the task execution efficiency is improved, the overall scheduling effect stability is improved, and the system fault recovery time is shortened.

The invention discloses an e-commerce live broadcast real-time interaction quality evaluation system based on edge calculation, and relates to the technical field of e-commerce live broadcast, and the system comprises a multi-modal interaction data collection module which collects multi-modal interaction data of a live broadcast stream in real time through a distributed edge calculation node cluster, and constructs a multi-dimensional quality feature vector, the multi-modal interaction data comprises a video coding parameter, an audio quality index, user interaction behavior data and network transmission state data; according to the invention, the distributed edge computing node cluster collects the multi-modal interaction data of the live stream in real time, the lightweight space-time attention neural network model carries out data fusion processing, the deep reinforcement learning network generates a quality optimization scheme, and the adaptive fuzzy inference system corrects the optimization scheme in real time. And dynamic parameter adjustment is carried out in combination with network bandwidth fluctuation and a terminal device resource state, so that the effect of accurately and comprehensively evaluating the e-commerce live broadcast interaction quality in real time is achieved.

A computer-implemented method is provided for a mobile device to detect, by a camera of the mobile device, a plurality of checks; determine, by a processing unit of the mobile device, that the image of the plurality of checks is of sufficient quality; instruct, by a display of the mobile device, a user to take a photograph of the plurality of checks; crop, by the processing unit, the photograph of the plurality of checks into a plurality of images, wherein each of the plurality of images contains one of the plurality of checks; and transmit, by a transmitter of the mobile device, the plurality of images to a server via a network. The plurality of images may be transmitted individually (i.e., one at time), or alternatively, collectively and in one payload.

Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).

The invention relates to the technical field of obstacle detection, and discloses an unmanned subway obstacle intelligent detection system based on a multi-mode AI sensor, and the system comprises the multi-mode AI sensor, a preprocessing unit, a data processing unit, and a communication unit. According to the method, in data preprocessing, point cloud filtering denoising, down-sampling burden reduction, image graying contour highlighting and Gaussian filtering denoising all improve the processing efficiency and the detection precision. Efficient data fusion establishes a multi-coordinate system conversion relation, blind area misjudgment is avoided, and the complex environment adaptability is enhanced. A comprehensive obstacle detection strategy covers laser radar multi-link processing and Canny algorithm application of visual images, mutual verification is carried out, and the reliability is improved. When obstacles are detected, real-time display and graded alarm can be achieved, early warning and scheduling control can be achieved by means of network transmission information, braking or avoiding can be achieved according to conditions, operation safety is guaranteed, and the system is reasonable in structure, has adaptability and expandability and assists technology development.

Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).

The invention relates to the technical field of industrial Internet of Things, and discloses a low-delay industrial Internet of Things data transmission system based on a 5G network. The system comprises a plurality of functional modules such as a data acquisition module, a data preprocessing module, a network transmission optimization module and a congestion control module. The data acquisition module acquires a heterogeneous data set, the preprocessing module performs standardization processing, the network transmission optimization module selects an optimal channel and node, and the congestion control module predicts flow and adjusts a transmission strategy. In addition, the system also has the functions of security encryption, heterogeneous data synchronization, dynamic spectrum allocation and the like. Through cooperative work of the modules, the system realizes low-delay and high-reliability transmission of industrial Internet of Things data, effectively processes heterogeneous data, guarantees data security, improves spectrum utilization efficiency and energy efficiency, enhances fault tolerance and compatibility of the system, and is suitable for various industrial scenes.

The invention belongs to the technical field of network transmission, and particularly relates to a time-sensitive network flow routing and scheduling method based on centralized control. Comprising the steps that CNC constructs network topology and generates global topology information; the CUC collects demand information of each to-be-transmitted traffic from each source node and divides traffic priorities according to the demand information; the CNC generates an optimal transmission path for each flow according to the global topological information; the CNC distributes a transmission time slot for each flow and dynamically adjusts the transmission time slot; carrying out synchronous distribution on the optimal transmission path and the transmission time slot, optimizing the transmission time slot and controlling the jitter of the transmission time slot; a scheduling table is generated according to the final distribution result of the paths and the time slots, and the CNC distributes the scheduling table to each network device; when the network state is changed, the scheduling table is dynamically adjusted to realize real-time routing and scheduling of the flow; according to the invention, the dynamic management of the flow priority is realized, the utilization rate of network resources is enhanced, and the service quality and high availability of transmission are ensured.

The invention relates to the technical field of highway management and control, in particular to a highway hard shoulder opening management and control method based on artificial intelligence. The scheme comprises the steps of collecting traffic flow and vehicle speed in real time; transmitting the preprocessed data to a central control system through a high-speed communication network; testing and optimizing the intelligent decision algorithm by using traffic simulation software, evaluating the performance of the algorithm by simulating different traffic scenes, and adjusting parameters according to a test result; testing and optimizing the optimal strategy by using traffic simulation software, and adjusting parameters according to a test result; integrating the optimized intelligent decision algorithm into a control system of the expressway; the performance of the expressway control system is continuously monitored, the performance comprises the passing efficiency and the accident rate, and the optimal strategy for opening the hard road shoulder is optimized online. According to the scheme, road side sensing is combined with automatic road shoulder development control dynamic adjustment, and safety and passing efficiency of a road system are achieved.

The invention discloses a ship management method and system based on digital twinborn scene construction. The method comprises the following steps: acquiring multi-source scene data of a target water area in real time, and constructing a corresponding ship management digital twin model; performing integrity evaluation on the constructed digital twinborn model, and performing defect compensation according to an evaluation result to obtain an optimized digital twinborn model; further collecting ship density and weather condition data of each sub-region of the target water area, constructing a network transmission delay prediction model, analyzing related data based on the model, and generating a network delay coefficient distribution diagram of the target water area; and according to the delay distribution diagram, determining the real-time updating lag amount of each subunit of the optimization model, and correcting the ship position information in the digital twin model. According to the method, the real-time performance and accuracy of the digital twin model can be remarkably improved, and the ship operation management efficiency and safety in a complex water area environment are enhanced.

The invention relates to the technical field of communication routing, in particular to a network connection automatic tuning system and device based on an SRv6 protocol. According to the method, the state data of network equipment is collected in real time, key network indexes such as delay, bandwidth, packet loss rate and hardware performance are combined, the health condition of network connection is dynamically evaluated, and path optimization is carried out in combination with an SRv6 protocol. By automatically calculating a path scoring matrix, the system can automatically select an optimal network path according to the priority of network transmission tasks, and intelligent adjustment and optimization are realized under the conditions of dynamic traffic and complex tasks; the invention provides a path calculation and scheduling mechanism based on an SRv6 protocol, the priority of a network path is automatically adjusted according to different types of data transmission tasks, and the selection of an optimal path is ensured. Meanwhile, the system has an automatic switching mechanism, and can automatically switch to an alternative path when the network path has a fault, thereby improving the reliability and fault-tolerant capability of the network.

The invention provides a vehicle-mounted data grading processing method, system, device and medium, the method is cooperatively realized by a cloud end and a terminal device, and the method specifically comprises the following steps: the cloud end generates a structured configuration file containing an acquisition signal, a data type, a transmission condition, a priority and a compression rule based on a service scene, a first processor of the terminal equipment analyzes a received structured configuration file to generate an acquisition white list, a second controller filters controller messages according to the white list, executes double verification of cyclic redundancy check and counter tamper-proofing, and transmits valid data passing the verification in a hierarchical manner according to priorities, and a cloud terminal performs hierarchical decompression analysis on the received data and sends the analyzed data to a server. A historical data supplement mechanism is triggered when the data is abnormal, and the terminal equipment responds to the request to upload data in a specified time period and performs compensation analysis; according to the method, the collection flexibility is realized through dynamic configuration, and the problems of high computing power pressure of terminal equipment, non-uniform network transmission distribution and low cloud computing power utilization rate are solved.

The invention relates to the technical field of electric digital data processing, and particularly discloses a hierarchical federated learning method for adaptive compression coding, which comprises the steps of hierarchical federated learning architecture construction, edge server matching, model generation performance judgment, compression ratio matching and hierarchical federated learning architecture judgment, and specifically comprises the following steps: firstly, constructing a hierarchical federated learning architecture; each layer can make full use of computing resources thereof, edge servers corresponding to the terminal devices are obtained through matching, the terminal devices are used for generating environment data training models, corresponding compression rates are obtained according to network transmission performance of the edge servers, and the compression rates are used for data compression. The edge server receives the environment data training model of each terminal device and carries out adaptive compression coding and edge aggregation in sequence according to a corresponding compression ratio, and the cloud server receives an edge aggregation result and carries out global aggregation; and finally, judging whether the cloud server to which the hierarchical federated learning architecture belongs uploads a global aggregation corresponding result to an environment resource scheduling cloud platform or not.

The invention relates to the technical field of networks, and discloses a method for determining position information of a routing node, computer equipment, a storage medium, a program product and a network general system.The method comprises the steps that a first code and a second code of a first routing node are obtained, and a third code and a fourth code of a target routing node are obtained; determining whether the first routing node and the target routing node belong to the same network subsystem or not according to the second code and the fourth code; when it is determined that the first routing node and the target routing node belong to the same network subsystem, performing XOR operation on the first code and the third code to obtain a target code; determining the number of target numerical values included in the target code; and determining position information of a next routing node corresponding to the first routing node according to the number of the target numerical values, the first code, the second code, the third code and one or more elements in the target code. The invention can improve the network transmission efficiency.

The invention relates to the technical field of network transmission, in particular to a video data transmission method, which comprises the following steps of: based on a video transmission data packet, analyzing a sending time point of the video data packet, recording a sending moment and a serial number, checking a time stamp at a plurality of transmission nodes, and generating a time stamp data packet. According to the invention, by matching the timestamps and the serial numbers, marking the data packets and checking the transmission nodes, the security and reliability of data transmission are improved, errors and loss of the data packets in the transmission process are reduced, and the video quality is optimized by analyzing the video data, identifying abnormal image frames and adjusting transmission parameters. Compression parameters and server resource allocation are dynamically adjusted according to video contents and in combination with real-time user requirements, so that video quality is maintained under the condition that the bandwidth is limited, the size of a buffer area and the capacity of a data packet are adjusted according to network conditions, and the fluency and continuity of video playing are improved.

The embodiment of the invention provides a method and a device for processing a layout. The method comprises the following steps: receiving a plurality of OASIS file blocks respectively corresponding to a plurality of layout blocks of the layout; and merging the plurality of OASIS file blocks to generate an OASIS file corresponding to the layout. In this way, deserialization processing on the layout data on the main node and OASIS format conversion processing on all the layouts can be avoided, and therefore use of computing resources of the main node is reduced. In addition, merging processing on the original layout blocks on the main node can be avoided, and use of memory resources is reduced. In addition, layout data transmission can be carried out between the working node and the main node in an OASIS format, and the data volume of network transmission is reduced.

A queue storage management system under an RDMA network comprises a data management module, a network transmission module, a data storage module and a queue management module which run on an FPGA platform. The data management module is bidirectionally interconnected with the network transmission module, the data storage module and the queue management module respectively; the data management module comprises a main control processing sub-module, a logic control sub-module, a data caching sub-module and a data checking and processing sub-module; the main control processing sub-module is respectively and bidirectionally interconnected with the logic control sub-module, the data caching sub-module and the data checking and processing sub-module, and is used for controlling the overall working logic of the system, including data storage management, scheduling of data transmission, working state control, dynamic allocation of system resources, abnormal state processing and starting of a fault-tolerant mechanism; the method can be more flexibly deployed in various application scenes; for multi-level abstraction of an interface, network layer queue processing and storage layer queue processing are hidden for a user level, a user does not need to care about how to process queues in a data transmission process, and only needs to care about correctness of instruction transmission, so that the system is easy to deploy and use, and has the advantages of high operation efficiency, flexible deployment and high efficiency. And the availability is high.

The invention discloses an extensible content interactive display method and system based on streaming media playing, the extensible content interactive display method based on streaming media playing belongs to the field of streaming media, and the method comprises the following steps: S1, dynamically adjusting the resolution and code rate of content under different network conditions; dynamic self-adaptive stream transmission is realized; s2, directly acquiring data through the nearest edge node when the content is requested, and caching high-frequency interaction data at the edge node; s3, the user request is routed to the optimal node; s4, adopting a predictive buffering and preloading mechanism; s5, predicting user interaction behaviors by using a deep reinforcement learning algorithm; and S6, adopting H.265, and combining the characteristics of low delay and high reliability of the QUIC protocol to carry out transmission. The extensible content interactive display system based on streaming media playing comprises a user behavior analysis module, a content management and distribution module, an interactive prediction and recommendation module, a preloading and cache management module, a network transmission and optimization module and the like.

The invention discloses a multi-node collaborative logistics data real-time synchronization method and system, and particularly relates to the technical field of logistics data synchronization management. Round-trip delay between logistics nodes and a cloud platform is measured, delay jitter data is collected and analyzed, network transmission environment stability of the nodes is evaluated, when a network is unstable, initial time difference is recorded, the change trend of a clock drift value is evaluated, clock synchronization accuracy is analyzed, and the network stability and the clock synchronization accuracy are integrated. The method determines the severity of the time synchronization deviation between the logistics nodes, divides the time synchronization deviation into a slight deviation, a moderate deviation and a serious deviation, and generates a graded early warning signal to take a targeted treatment measure, thereby effectively solving the problems of data error sequence and scheduling error caused by the time synchronization deviation in the prior art, and improving the reliability of the system. The time synchronization accuracy, the network transmission stability and the overall operation efficiency of the logistics system are improved, and the accuracy and the reliability of logistics scheduling and event processing are remarkably improved.

The invention relates to the technical field of intelligent networked vehicles, in particular to an intelligent networked vehicle remote control and monitoring method. The method comprises the following steps: acquiring real-time running state information and roadside sensing data of a vehicle, and generating a remote takeover request; receiving a control instruction sent by the cloud control platform, and feeding back a control execution result; calculating instruction interaction delay and network transmission delay; the stability of the communication environment is evaluated by combining the two, and the vehicle driving mode is dynamically adjusted. Furthermore, time delay is calculated according to heartbeat signals and control instruction timestamps in the communication link, the stability index of the communication environment is evaluated, and the safe driving speed is adjusted according to the stability. And when the communication environment stability is lower than the threshold value or the instruction interaction delay exceeds the threshold value, an emergency stop mechanism is triggered. According to the method, the safety and the stability of the intelligent network connection vehicle under remote control can be improved.

The invention relates to the technical field of booster station monitoring systems, and discloses a booster station operation and maintenance work video auxiliary monitoring system comprising a three-dimensional perception interaction layer used for collecting equipment state data and providing a man-machine interaction interface and connected with an edge intelligent fusion layer through a wired or wireless transmission channel; and the edge intelligent fusion layer is used for locally analyzing and caching the state data. Through standardized interface interconnection of the three-dimensional perception interaction layer, the edge intelligent fusion layer and the cloud collaborative management layer, a collaborative working mode of data acquisition, local analysis and cloud optimization is formed, the architecture design breaks through the dependence of a traditional scheme on cloud centralized processing, data preprocessing sinks to the edge layer, the network transmission pressure is effectively reduced, and the network performance is improved. The local intelligent analysis capability can still be maintained when the network fluctuates, and compared with the delay problem caused by full data uploading in the prior art, the system response real-time performance and the availability under the network disconnection scene are remarkably improved.

The invention relates to the technical field of networks, in particular to a traffic transmission method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring transmission time period information and transmission network information corresponding to flow to be transmitted in a communication network; wherein the communication network comprises a plurality of communication nodes, and according to transmission time period information, determining that each transmission sub-time period takes transmission network information as a constraint condition, and according to node information of each communication node when the communication network transmits the to-be-transmitted flow in each transmission sub-time period, determining a target transmission path corresponding to the to-be-transmitted flow; and transmitting the to-be-transmitted traffic based on the target transmission path.

The invention provides an electric power wireless local area network multi-domain data processing method and system based on credibility certification, and the method comprises the steps: firstly calling a credibility certification model to carry out the credibility certification of terminal equipment, generating a terminal certification data set containing equipment identity and the like, obtaining a cross-domain original data flow, extracting the characteristics of equipment operation and the like through multi-mode characteristics, and carrying out the multi-mode certification of the terminal equipment; the method comprises the following steps: carrying out weighted fusion on credibility of equipment operation state characteristics based on a terminal authentication data set, carrying out dynamic association analysis on the credibility and network transmission quality characteristics to generate a cross-domain association characteristic set, and carrying out spatio-temporal context aggregation on the cross-domain association characteristic set and service operation semantic characteristics by utilizing a pre-trained multi-domain collaborative analysis model; and finally, according to the multi-domain collaborative optimization strategy set, dynamic resources of service domain nodes are reconfigured, and a network optimization execution instruction set is generated and fed back to terminal equipment to trigger trusted communication link upgrading operation. And effective multi-domain data processing and network optimization of the electric power wireless local area network are realized.

A method by which a network transmits a signal in a wireless communication system is disclosed. The method can comprise: establishing a communication link with a vehicle and at least one terminal positioned in the vehicle; receiving, from the at least one terminal, a first message for requesting a service or a second message for notifying of the occurrence of a shock event; and transmitting, to the vehicle, a third message indicating i) the provision of the service or ii) an instruction associated with the shock event, on the basis of the first message or the second message.

The invention relates to the technical field of audio and video emergency transmission, and discloses an audio and video low-delay return method and system in an extreme environment. The method comprises the following steps: acquiring original multi-modal data of audio and video acquisition equipment in a target area, and analyzing a data state of the original multi-modal data; and meanwhile, available network transmission links are monitored, and the quality is evaluated. Self-adaptive coding parameters are generated in combination with the link quality and the data state, dynamic coding is executed on original data, and a coding stream suitable for redundant transmission is formed. And carrying out cooperative distribution transmission based on the network link set and the coded stream to generate return data. According to the generation process, a device and energy management instruction is formed and issued to the acquisition and relay device. According to the method, the network state and the content characteristics are optimized in a dynamic coding link in a collaborative manner, and the audio and video quality, the real-time performance and the system energy efficiency which are transmitted back in an extreme environment are improved through a feedback closed loop for transmitting a result to equipment management.

The invention relates to the field of communication, and discloses a vehicle-mounted network time synchronization method and system, and the method comprises the following steps: a master clock periodically broadcasts a synchronization message to all slave clocks in a network, and the synchronization message comprises a current timestamp; the slave clock receives the synchronization message and records the receiving time T1; the slave clock sends a delay request message to the master clock, and the sending time T2 is recorded; after receiving the delay request, the master clock sends a delay response message and records delay request message receiving time T3; the delay response message comprises a timestamp T4 when the master clock receives the delay request message; and the slave clock obtains network transmission delay and clock skew Offset between the slave clock and the master clock according to the time T1, T2, T3 and T4, and the slave clock adjusts the time according to the clock skew. According to the invention, the time height of each node in the system can be ensured to be consistent. According to the invention, by using clock synchronization mechanisms such as IEEE1588 and the like, the timestamp is ensured to be accurate to the nanosecond level.

The invention is suitable for the technical field of toll station management, and provides an expressway toll station remote seat guarding and special situation vehicle handling system, which comprises a front-end sensing layer, a rear-end sensing layer and a control layer, the lane equipment comprises a photoelectric sensor, an infrared height limit alarm, a license plate recognition camera, an ETC antenna, an acousto-optic warning ball and a self-service equipment sensor; the network transmission layer is connected with lane equipment, a sentry box cabinet, a machine room core switch and a monitoring center through an optical fiber network; the remote control layer is composed of a remote seat center, and the remote seat center can carry out video monitoring, visual intercom and remote control; and the abnormity alarm layer is used for carrying out early warning on vehicle detention, vehicle height exceeding, ETC passing faults, toll evasion vehicles and handrail abnormity. The vehicle state can be sensed in real time, data are gathered to a remote seat center through a network transmission layer, an information island is broken, and special conditions can be automatically processed.