3483 results about "Transmission delay" patented technology

The invention discloses a transformer area intelligent fusion terminal data processing system based on edge calculation, relates to the field of edge intelligence, and solves the problems of poor real-time performance and poor data exception processing accuracy of an existing intelligent fusion terminal data processing system. According to the method, communication between micro-services is efficiently managed through the container arrangement engine and the service grid, the message transmission delay is reduced, and resource allocation is further optimized through a resource scheduling algorithm based on reinforcement learning, so that system resources are used most reasonably; according to the method, anomaly detection is rapidly and accurately carried out through a space-time heterogeneous fusion network model, hierarchical processing of data and on-cloud training of the model are realized through a cloud-edge collaborative architecture, edge nodes participate in model training through a federated learning mechanism, the model performance is optimized, the transmission time of the data in the network is shortened, and the problem positioning speed is increased; the real-time performance and the reliability of an existing system are greatly improved.

The invention provides a real-time streaming media transmission method and system based on a cloud game and a storage medium, and the method comprises the steps: monitoring network state parameters in real time, and generating network state data; dynamically adjusting the resolution, the frame rate and the bit rate of the video stream based on the network state; a redundant data packet is inserted, and the redundancy proportion is adjusted according to the packet loss rate and the jitter, so that the data reliability is enhanced; dynamically adjusting the transmission rate by adopting a congestion control algorithm; dynamically selecting an optimal server node according to a network condition and a server load; audio and video processing tasks are shared through edge computing nodes, and the load and transmission delay of a main server are reduced; setting a self-adaptive decoding buffer area, dynamically adjusting the size of the buffer area according to a network state, and reducing playing lagging; through real-time monitoring, dynamic adjustment and edge collaboration, smoothness is guaranteed, reliability is improved, delay is reduced, efficient load distribution and user experience optimization are achieved, and the method is suitable for real-time streaming media transmission in a cloud game scene.

The invention relates to the technical field of network time delay scheduling, and discloses a deterministic network time delay scheduling method and device based on a TSN and a storage medium. The method comprises the following steps: carrying out graph theory analysis on a TSN network topology structure to obtain a network node connection relationship and link bandwidth information; extracting time delay requirements and bandwidth requirement characteristics of the data streams, and generating a data stream priority queue and a resource requirement index matrix; inputting a deep Q network, establishing a state-action mapping relation including a network load state and a time slice distribution action, and generating an initial time delay scheduling strategy model; calculating queuing time delay, transmission time delay and processing time delay of each data stream, and generating a time slice resource redistribution scheme; generating a global resource allocation matrix based on the time slice resource reallocation scheme; and parameter feedback updating is carried out on the initial time delay scheduling strategy model to obtain a target time delay scheduling strategy model, and the utilization efficiency of network resources is remarkably improved through bandwidth borrowing and time slice reallocation.

The invention relates to the technical field of information retrieval, and discloses a distributed storage and indexing method, which comprises the following steps of: dynamically fragmenting an original file through an improved consistent Hash algorithm to generate a plurality of data blocks with timestamps; constructing a three-dimensional Bloom filter index matrix containing timestamps, data types and content features for the data blocks with the timestamps, associating a B + tree local index with an inverted global index through a hierarchical index structure, and establishing an index update priority queue by adopting a two-channel synchronization mechanism, performing real-time increment synchronization on the hotspot index through a heartbeat mechanism, performing batch synchronization on the cold data layer index according to a cold data synchronization period, predicting a data distribution probability through a distributed query statistics probability table during query, and initiating multi-path query in parallel based on probability weight, and the query path is dynamically optimized according to the node group storage medium type and the inter-node network transmission delay, so that rapid distribution adjustment and access of distributed storage are realized.

The invention relates to the technical field of communication, in particular to a low-delay data transmission system and method for marine observation data, and the system comprises a data collection module which collects the multi-modal data of a marine environment, and carries out the priority classification of the data according to the real-time performance and importance; the route optimization module dynamically adjusts a multi-path fragmentation strategy and single-path task distribution in combination with a reinforcement learning algorithm and path optimization data; the communication module supports multi-mode communication modes such as laser communication and low-orbit satellite communication, and monitors the link state in real time; and the data fusion and analysis module performs dimension reduction, fusion and real-time analysis on the data by using manifold learning and a graph neural network, and meanwhile, predicts a long-term trend through time sequence analysis to generate observation report data. The method effectively reduces the transmission delay of high-priority data, improves the response efficiency of the system to abnormal events, and is suitable for the scenes of marine disaster early warning, environment monitoring and the like.

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

The invention discloses an electronic lead seal automatic detection method applied to logistics tracking, and relates to the technical field of Internet of Things safety monitoring. The problems of packaging data loss, tampering risk increase and real-time monitoring failure caused by wireless communication signal interference, transmission delay and state updating lag of an existing electronic lead seal are solved. The method comprises the following steps: fusing multi-physical field sensing data through a space-time correlation sampling algorithm, and constructing an anti-interference characteristic matrix; evaluating communication quality based on the dynamic probability network model, and triggering a multi-path fragmentation concurrent transmission strategy to avoid signal attenuation; a hybrid reasoning model is deployed at an edge end to screen key event data, and the transmission efficiency is optimized in combination with differential coding and an IEEE 1588 clock synchronization mechanism; the cloud end adopts a space-time diagram fusion analysis model to carry out cross-modal abnormal association scoring, corrects misjudgment and updates an edge model; according to the invention, the communication reliability, the real-time transmission efficiency and the anomaly detection precision of the lead sealing state data in a complex environment are obviously improved.

A system for the temporal ordering of multi-channel data streams, comprising the following: a multi-channel data reception module configured to receive real-time data streams from multiple sources, extract temporal metadata, and detect discrepancies in timestamps; a time synchronization module configured to align data packets using timestamp normalization, adaptive buffering, and AI-based predictive modeling; an AI-powered predictive modeling module trained to estimate missing or delayed timestamps and to reorder out-of-order data packets based on learned patterns; an adaptive buffer module configured to dynamically adjust buffer sizes based on real-time data arrival rates and network conditions; an ordering and output processing module configured to reconstruct the correct order of the data packets and transmit them to a processing or analysis system; and a module for error detection and correction that is configured to detect inconsistencies in timestamps, transmission delays and missing data points, thus ensuring increased reliability of the ordered data sequence.

The invention provides an MBB multi-channel local aggregation superposition transmission method and an MBB multi-channel local aggregation superposition transmission system. Belongs to the technical field of communication. The method comprises the following steps that: a plurality of physical links are established in a wireless communication system, and the system selects the plurality of optimal physical links for aggregation according to a current network environment, a current equipment state and a current user demand; dividing data to be transmitted into a plurality of data packets, packaging each data packet according to the characteristics of the selected physical link, and transmitting the packaged data packets in parallel through the selected physical link; in the transmission process, the system monitors the transmission state of each link in real time, and dynamically adjusts the transmission rate and power distribution of each link according to the current network load and equipment state. By transmitting a plurality of physical links in parallel, the network bandwidth can be fully utilized, the data transmission rate is improved, and the transmission delay is reduced.

The invention relates to a distributed large two-layer network intelligent routing method and system based on edge cloud nodes, and belongs to the technical field of computer networks. Aiming at the problems of slow routing decision response and low fault recovery efficiency of the existing network in a dynamic environment, the invention provides a method for periodically collecting link bandwidth utilization rate, transmission delay and other state information through an edge cloud node, uploading the state information to a central cloud platform to generate a global routing strategy and issuing the global routing strategy to the edge node, and triggering fault switching in combination with local dynamic threshold monitoring. According to the technical scheme, bidirectional communication between edge nodes and a central platform, a neural network model of spatial-temporal feature fusion and a path priority generation mechanism of multi-objective optimization are included. The method and the system are suitable for a large-scale distributed network environment, and network resource utilization rate and service continuity can be improved.

An adaptive adjustment method of packet-level transmission priority for delay guarantee in programmable networks. The method realizes the adaptive adjustment of packet-level transmission priority in programmable networks from three aspects to satisfy the preset transmission delay requirements, namely: adaptive adjustment of priority in programmable switches based on processing delay state and switch queuing state, adaptive adjustment of priority among programmable switches based on transmission delay in upstream switches, and adaptive adjustment of global parameters based on packet transmission delay satisfaction, so as to realize the packet-level transmission delay guarantee in different positions with different time scales. In addition, for a scene with a large number of time-sensitive flows, based on the optimization model and heuristic algorithm, the optimization deployment of time-sensitive flows can be realized in polynomial time under the condition of limited network resources to improve the overall extent of delay satisfaction.

The invention relates to the technical field of data synchronization, and discloses a distributed account book remote data synchronization method and system, and the method comprises the steps: carrying out the Hash mapping calculation of all nodes of a distributed account book system, and obtaining a distributed storage architecture; performing hierarchical network construction on the nodes, and setting an inter-region remote synchronization link and an intra-region local synchronization link to obtain a double-layer communication architecture; performing parallel compression coding, digital signature generation, transmission scheduling arrangement and consistency verification processing on the data blocks to obtain a node synchronous data set; calculating a correlation coefficient of node processing delay and network transmission delay to obtain a synchronous delay analysis model; based on a data block corresponding to the synchronous delay analysis model, adding a time sequence identifier and calculating an integrity check code, and generating a synchronous reliability guarantee mechanism; according to the method, the consistency and the traceability of the distributed account book data are ensured.

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

The invention provides an intelligent short message link efficient detection method and system. According to the method, unmanned aerial vehicle cluster deployment is used for forming a dynamic communication topology, and the dynamic communication topology is used for monitoring the time delay mutation rate and the packet loss rate of a damaged short message link in real time and generating a state fluctuation sequence. When it is detected that the transmission time delay gradient exceeds an emergency communication threshold value, an abnormal marking mechanism is triggered, and abnormal association clusters and the space-time coupling relation of the abnormal association clusters are recognized by analyzing the data. Then, the information is bound with timestamps, and a block chain state change event is generated by using a multi-node parallel evidence storage technology; and adjusting the distribution density of the unmanned aerial vehicle according to a verification result, and generating a topology reconstruction factor so as to update a short message transmission path and optimize a communication network. According to the technical scheme provided by the invention, the stability and reliability of efficient detection of the short message link can be improved.

The invention relates to the technical field of data transmission, and provides a data transmission method and device, electronic equipment, a storage medium and a program product.The method comprises the steps that resources needed by RDMA are initialized, and the initialization process comprises the steps of creating a registration memory of the RDMA and creating a plurality of work queue pairs according to different data transmission logics of a target data packet to be transmitted, each work queue pair corresponds to one data transmission logic; dividing a data buffer area in the registered memory into memory blocks with preset sizes; writing the to-be-transmitted target data packet into a data buffer area by taking a memory block as a unit; and selecting the corresponding target working queue based on the data transmission logic of the to-be-transmitted target data packet, and sending the to-be-transmitted target data packet in the data buffer area to an opposite end, or receiving data of the opposite end to the data buffer area. According to different data transmission logics, different working queues are selected to complete operation on the logic channels serving as data transmission, multiple pieces of data are transmitted in parallel, and transmission delay is reduced.

The invention provides an old cell environment sensor data processing method and system based on ultraviolet light communication. The method comprises the following steps: acquiring an environment feature set of an external facade of an old community building through a distributed environment sensor array, and constructing an ultraviolet channel reflection skeleton in combination with an obstacle coordinate; fusing the aging factor attenuation model and the physical space topological structure through a dynamic space-time grid division engine, and generating a multi-dimensional feature segment set carrying space-time attenuation weights; analyzing channel interference in real time based on the interference intensity probability matrix of the ultraviolet channel reflection skeleton, and generating a multi-band transmission configuration result; and calibrating multipath transmission time delay through a phase compensation factor to construct an ultraviolet light pulse sequence carrying a path feature code, and when the difference degree of adjacent units exceeds a critical condition, triggering a closed loop feedback mechanism and updating a link weight. According to the technical scheme provided by the embodiment of the invention, the efficiency and precision of old cell environment sensor data processing can be improved.

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

The invention is suitable for the field of GPU management, and provides an intelligent dynamic management method for GPU computing power and a cloud platform, and the method comprises the following steps: collecting task data and GPU state data, and generating a task queue and a resource allocation strategy in combination with a scheduling plug-in; based on the task queue and the GPU real-time load, dynamically adjusting a resource allocation proportion through reinforcement learning to analyze a task dependency relationship and generate a migration plan; optimizing a communication path and adjusting asynchronous transmission delay according to the task dependency relationship and the GPU communication topology, and outputting a synchronous state mark; and monitoring abnormity in combination with the synchronization state and the GPU hardware state, executing thermal migration according to the migration plan, performing video memory recovery, and updating the resource idle list. According to the invention, through algorithm innovation and hardware collaborative optimization, intelligent, dynamic and efficient resource scheduling in the multi-GPU system is realized.

The invention provides a communication performance test method and system for a base station network side transmission path. The method comprises the following steps: determining a target monitoring node from a plurality of monitoring nodes deployed on a network side transmission path of a to-be-tested base station, and monitoring transmission delay data, packet loss rate data and bandwidth utilization rate data of a test data stream on a specific road section of the transmission path in real time; detecting periodic and non-periodic changes of transmission delay to obtain an analysis result; evaluating the influence of the packet loss rate data on the transmission performance to obtain an evaluation result; predicting the change trend of the bandwidth utilization rate data to obtain a prediction result; calculating a communication performance index of the specific road section by integrating the three results; and generating a communication performance test report according to a comparison result whether the communication performance of the specific road section reaches a predetermined standard. The communication performance of the base station network side transmission path is comprehensively evaluated by integrating the chaos theory, the fuzzy logic system and the deep learning algorithm, so that the communication performance testing efficiency is improved.

Provided in the present invention is a node-type edge computing system. The system comprises a micro-service module, a CI / CD module, an application management module, an observation module and a security module. The node-type edge computing module in the present invention has the characteristics of having a low network delay, supporting mass data access, having an elastic infrastructure, etc. Moreover, in addition to reducing the transmission delay, the advantages brought about by shortening a spatial distance further comprise the delay of various PLCs, gateways, routing-transfer, and network device processing in a complex network is also reduced. In addition, since the probability of network link contention is greatly reduced, the overall delay can be significantly reduced. By means of the node-type edge computing module, a distributed capability is added to a traditional cloud center, some service logic is deployed on an edge side, and related data processing is completed, such that the pressure of transmitting data back to a center cloud can be greatly relieved. The node-type edge computing module can also provide an elastic virtualization capability, such as calculation, networking and storage, based on an edge location, and can truly realize "cloud-edge collaboration".

The present invention discloses a method, device, equipment, medium and product for clock synchronization between clusters. The method is applied to a slave clock synchronization system in each cluster, and the slave clock synchronization system includes: a clock synchronization module and a calculation module; the clock synchronization module obtains the timestamp of the high-precision time synchronization protocol PTP message between the master clock server and the master clock server, and sends the timestamp to the calculation module; wherein the PTP message includes at least: a synchronization message, a follow-up message, a delay request message and a delay response message; the calculation module determines the corresponding master-slave clock deviation and transmission delay according to the received timestamp, and sends the clock synchronization signal determined according to the master-slave clock deviation, transmission delay and the local slave clock to the clock synchronization module; the clock synchronization module generates the corresponding slave clock second pulse according to the clock synchronization signal sent by the calculation module to complete the slave clock correction. This scheme can realize accurate clock synchronization between computing clusters in a multi-computing cluster system.

The invention relates to the field of 5G and digital information transmission, in particular to a 5G cloud-side collaborative content caching method, which comprises the following steps of: in a cloud-side collaborative scene, modeling user experience by comprehensively considering factors such as hit rate, transmission delay and traffic load; and the constructed cloud edge collaborative caching model is solved, and the solving process comprises content prediction based on Transform and solving based on a multi-agent reinforcement learning technology. The method comprises the following steps: splitting a cache model into a # imgabs0 # part and a # imgabs1 # part; solving # imgabs2 through a cache prediction scheme based on Transform, a deep neural network and super-dimensional calculation; and solving # imgabs3 # by adopting a deep reinforcement learning method. According to the method, the user preference information, the hot information and the user browsing history are comprehensively considered, and a differentiated feature extraction scheme is designed, so that relatively high prediction accuracy is achieved.

The invention relates to the technical field of ad-hoc network routing, in particular to an ad-hoc network routing method based on wireless link perception, which comprises the following steps of: calculating a link quality score of a node by monitoring and analyzing a wireless communication signal and spectrum environment data of the node, recording signal quality, interference condition and bandwidth use state of the node, and calculating a link quality score of the node; and generating link quality score data of the nodes. According to the method, the wireless link state of the node is accurately monitored and analyzed, so that the signal strength can be reflected in real time, the routing decision can be dynamically adjusted, in the aspect of spectrum resource allocation, the spectrum use efficiency of the network is optimized, optimization is performed based on a dynamic spectrum adjustment scheme and real-time feedback, and through a task migration mechanism, the resource allocation efficiency of the network is improved. The task can be automatically migrated to the optimal node, through the link state, the transmission delay is reduced, the network reliability is improved, the calculation efficiency is improved through the intelligent migration of the task load, and the calculation bottleneck problem in the network is effectively solved.

The invention relates to the technical field of wireless communication, in particular to an intelligent wireless communication control method applied to ships and boats. The method comprises the following steps: acquiring radar original point cloud data, an AIS ship attribute data set, a Beidou navigation state data set and night vision target feature data through a multi-dimensional sensor, and constructing ship multi-source standardized preprocessing data; therefore, the functions of multi-source heterogeneous data fusion, dynamic channel adaptive modulation, distributed relay communication guarantee, real-time air route dynamic planning, intelligent instruction generation and the like are realized; the problems of high data isolation, large transmission delay, rigid navigation path, slow obstacle avoidance response, insufficient formation collaboration and the like in the existing ship communication control technology are solved, and the communication stability, the navigation safety and the overall combat effectiveness of the ship formation in a complex dynamic environment are remarkably improved.

The invention discloses a TSN scheduling optimization method and device based on flow sensing autonomous learning, equipment and a medium. The method comprises the following steps: deploying a lightweight flow detection module in a switch or a router, and after a controller receives a data request, automatically identifying a newly arrived unknown service flow by using the lightweight flow detection module, and judging whether the newly arrived unknown service flow is a periodic TT flow or an unpredictable burst flow; the controller performs classification management on the identified service flow types, collects topological information and flow requirements of the whole network and issues the topological information and the flow requirements to the terminal nodes through a network management interface; the controller constructs an intelligent queue scheduling task based on the collected network topology information and traffic demand and converts the task into a Markov decision process MDP, network resources, queue states and priorities are used as a state space, a scheduling strategy is used as an action space, a reward function is designed in combination with throughput and delay indexes, and an intelligent queue scheduling task is obtained. Driving a dynamic environment through real-time data and training a DRL model; an enhanced queue scheduling mechanism Pro-CQF is adopted, different priority labels are configured according to classified flow types, and then mixed flow scheduling is carried out; the controller periodically collects time delay, packet loss rate and end-to-end transmission delay indexes and feeds back the indexes to the DRL model, and a scheduling strategy is updated online. According to the method, the traffic sensing and scheduling efficiency is greatly improved in a network environment in which multiple service flows coexist and end-side equipment functions are different, and the reliability and the expandability of the TSN in industrial Internet of Things, edge computing and other high-real-time application scenes are remarkably enhanced.

The invention discloses a converged network-oriented task awareness and intelligent scheduling method, and relates to the technical field of communication networks, the method is applied to a converged network, and the method comprises the following steps: constructing a converged network architecture; extracting a user equipment node of the current to-be-processed task from the computing power identifier of the current to-be-processed task as a source node; based on the converged network architecture, determining a corresponding path by using a path search algorithm when the source node is used as a starting point and each computing power center node is used as a destination node; according to the computing power identifier of the current to-be-processed task, selecting an optimal path from paths corresponding to all computing power center nodes; according to the method, the transmission time delay and the service time delay are considered when the optimal path is selected, so that the reasonability of task perception and intelligent scheduling oriented to the fusion network can be improved.

The invention relates to the technical field of terminal management, and particularly discloses a remote diagnosis management method and system based on a vehicle-mounted terminal, and the method comprises the steps: obtaining multi-source heterogeneous data collected by the vehicle-mounted terminal in real time; performing dynamic priority classification on the multi-source heterogeneous data to obtain a multi-source data priority set; constructing an edge-cloud collaborative multi-modal model according to the multi-source data priority set, and obtaining multiple pieces of dynamic data information according to the edge-cloud collaborative multi-modal model; and acquiring data association information and semantic information of each piece of dynamic data distribution information, and constructing a vehicle data association topological graph according to the data association information and the semantic information. According to the invention, the analysis and utilization capability of the vehicle data is effectively improved. The constructed edge-cloud collaborative multi-modal model can efficiently process multi-source data, reduce transmission delay and cloud burden, and improve real-time performance and decision accuracy.

The invention relates to the technical field of power distribution station supervision, in particular to an intelligent auxiliary and artificial intelligence visual gateway control method and system for a station building, which monitors network state parameters in real time, calculates a network quality score and dynamically selects an optimal transmission path based on a reinforcement learning algorithm. Comprising a high bandwidth mode, a low delay mode and a disaster recovery backup mode, stage processing and dynamic compression are performed on transmission data according to data types and network quality scores, link switching and a local caching mechanism are automatically triggered when a network is abnormal, and finally, multi-gateway load balancing and visual monitoring are realized through a software defined network architecture. The problem of transmission delay or interruption caused by the fact that a static data transmission framework cannot adapt to network state changes in the prior art is effectively solved, and the reliability and the real-time performance of data transmission are remarkably improved through dynamic path optimization, intelligent hierarchical transmission and a fault self-healing mechanism.

The invention discloses a digital twin auxiliary edge network resource allocation optimization method, and belongs to the technical field of edge computing. Comprising the following steps: establishing a resource allocation system of the digital twin auxiliary edge network; determining transmission time delay and energy consumption required by task calculation in the unloading mode; constructing a multi-intelligent deep reinforcement learning model; and training the multi-intelligence deep reinforcement learning model, and realizing a resource allocation strategy by using the trained multi-intelligence deep reinforcement learning model. According to the method, the service cache module and the task unloading module are established, so that task processing time delay and energy consumption are minimized; the state space of the MEC server and the state space of the user terminal equipment are respectively considered, the task unloading success rate is improved, the task processing time delay and energy consumption are remarkably reduced, and the accuracy of task unloading and resource allocation is further improved.

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.