1010 results about "Bandwidth allocation" patented technology

The invention discloses an unmanned aerial vehicle cluster control and navigation method based on MAPPO. The method comprises the following steps: extracting basic characteristic data of an unmanned aerial vehicle, calculating a comprehensive capability index of the unmanned aerial vehicle through dynamic characteristic analysis and standardization processing, and constructing a cluster isomerism matrix; calculating a communication quality index according to the real-time communication data, predicting link reliability data, constructing a dynamic communication graph, and generating an optimal communication topological structure; based on the cluster isomerism matrix and the optimal communication topological structure, calculating a task allocation fitness matrix, and constructing a hierarchical strategy model and a hierarchical value function; performing multi-dimensional analysis on the communication data, generating an information importance index, calculating transmission priority data, generating a bandwidth allocation matrix, and constructing a self-adaptive routing strategy; and calculating a strategy uncertainty index, constructing a robustness constraint condition, optimizing a strategy model and realizing distributed execution. According to the invention, the cooperative control efficiency and the system reliability of the heterogeneous unmanned aerial vehicle cluster are improved.

The invention discloses an archive data security integration management system, which relates to the technical field of knowledge maps and comprises an archive data acquisition module, a knowledge intelligent analysis module, a knowledge map dynamic construction module, a security situation evaluation module and a security communication center module. The data acquisition module structurally acquires metadata and operation behaviors, the intelligent analysis module dynamically governs data quality, the map construction module constructs a three-dimensional security model, the situation evaluation module quantifies security influence and generates a strategy, and the communication center module realizes dynamic identity authentication and bandwidth allocation. Through the knowledge graph technology, comprehensive integration and safety management of the archive data are achieved, the data quality and utilization efficiency are improved, dynamic evaluation and coping with safety threats are achieved, and the safety and integrity of the archive data are ensured. Meanwhile, through dynamic identity authentication and bandwidth allocation, the safety and efficiency of cross-domain communication are improved.

The dynamic bandwidth allocation and resource scheduling method based on the 5G network comprises the steps that S1, a base station collects service requests, network loads and channel information of user equipment of the 5G network, and the services are divided into real-time services, big data services, key services and conventional services; s2, the real-time service calculates the bandwidth by using deep learning; the big data service is distributed according to the idle bandwidth and the data volume proportion; key service main and standby links distribute bandwidths; conventional businesses come first and then are subjected to service distribution; s3, the base station maps bandwidth resources by using a multi-carrier and dynamic subcarrier algorithm, and optimizes signal transmission in combination with a beam forming technology; s4, processing service data according to a priority scheduling queue, and verifying signal transmission according to a channel quality adjustment coding mode; and S5, updating the data and evaluating the effect according to the user feedback, and re-optimizing the scheduling strategy as required. Through intelligent dynamic bandwidth allocation and resource scheduling, efficient, flexible and reliable transmission of different types of services is realized, and the network resource utilization rate and the service quality are improved.

The invention provides a bandwidth regulation and control and visitor flow routing optimization method and system for multi-scene live broadcast, and relates to the technical field of intelligent routing, and the method comprises the steps: collecting live broadcast data, constructing a feature vector, and training a scene classification model; analyzing bandwidth requirements by using a time sequence prediction algorithm, and formulating a differentiated bandwidth allocation strategy; and an edge node load monitoring mechanism is established, a multi-target routing optimization model is constructed, and real-time scheduling optimization of visitor flow is realized. The method can effectively improve the bandwidth utilization rate and the user experience quality of the live broadcast platform.

The invention relates to the technical field of traffic management, in particular to a dynamic traffic scheduling method and system based on network configuration, and the method comprises the following steps: based on network configuration data, extracting network index data, network indexes including network delay, packet loss rate and bandwidth size, calculating a network quality score, evaluating a current network state, and obtaining network state information. According to the method, the key network indexes are extracted, the network quality score is calculated, and the current network state is comprehensively evaluated, so that network configuration can respond to network requirements and condition changes, and according to the real-time network quality, the bandwidth resources are dynamically adjusted, and a priority rating mechanism is introduced, the network quality is improved. The time sensitivity of different data contents is evaluated, it is ensured that important data can obtain enough transmission resources, the influence caused by network fluctuation is compensated by monitoring the network fluctuation in the data transmission process and adjusting bandwidth allocation in real time, and the continuity and efficiency of data transmission are ensured.

The invention relates to the technical field of computer networks, in particular to a monitoring method and system based on industrial computer network fault data, and the method comprises the steps: collecting the heterogeneous fault data of each layer of equipment in an industrial control network in real time through distributed probe nodes; performing multi-modal normalization processing on the original fault data; constructing a fault knowledge graph, and dynamically associating an equipment topological relation, a historical fault mode and a current production task context; fault root cause analysis is carried out by adopting a hybrid inference engine, and a potential fault propagation path is predicted in combination with a rule-based expert system and an LSTM-GNN joint model; generating a grading alarm strategy, triggering a self-adaptive fault-tolerant mechanism, and dynamically adjusting network bandwidth allocation or starting redundant equipment switching according to the fault grade; according to the invention, by constructing the industrial knowledge graph and the adaptive fault-tolerant mechanism, efficient, accurate and interpretable fault diagnosis and prediction are realized, and the reliability and operation and maintenance efficiency of an industrial network are improved.

The invention provides a private domain live broadcast bandwidth resource allocation and routing method and system based on reinforcement learning, and relates to the technical field of computer networks, and the method comprises the steps: collecting real-time data such as the number of users, geographical distribution, terminal types, content types, network delay, packet loss rate, bandwidth utilization rate and the like in a live broadcast room, and inputting the real-time data into a pre-trained reinforcement learning model; the model is based on a state space, features are extracted by using a deep neural network, bandwidth resource constraints are combined, and a bandwidth allocation and routing strategy is generated by adopting a strategy gradient algorithm; and according to the strategy, the software defined network controller adjusts bandwidth allocation parameters and routing table configuration in real time to realize differentiated bandwidth allocation and path optimization, establishes nearby access edge nodes based on user geographical distribution, and dynamically adjusts the path during congestion.

The invention relates to the technical field of traffic management, in particular to a video monitoring traffic intelligent optimization system which comprises a time sequence fragment evaluation module, a path priority adjustment module, a traffic scheduling optimization module and a buffer strategy adaptation module. According to the invention, the transmission efficiency and quality of the video monitoring data are improved by analyzing the video stream in real time and adjusting the frame rate and the compression rate, the importance of each time sequence segment in the video stream is evaluated, the frame rate is adjusted according to the importance, more resources are ensured to be obtained by important events, unnecessary data transmission is reduced, network congestion is effectively reduced, and the transmission efficiency of the video monitoring data is improved. The network transmission path is monitored in real time, and the data transmission proportion is adjusted, so that the video stream passes through the network path with higher quality more preferentially, the stability and speed of video transmission are enhanced, the priority and bandwidth allocation are dynamically adjusted, and the video stream with high priority is protected to ensure that the video quality of a key monitoring area is not influenced by network fluctuation.

The invention relates to the technical field of communication data analysis, and discloses a communication network service health degree analysis method, system and device and a medium, and the method comprises the steps: obtaining real-time link state data, carrying out the quantitative analysis, and judging whether the link jitter exceeds a preset threshold value or not; when abnormality is detected, abnormal points can be positioned and the influence range of the abnormal points can be analyzed, so that the influence degree of nodes on the abnormal diffusion path can be identified; calculating a service quality index change value, and determining a starting point and a diffusion direction of chain degradation; by analyzing historical traffic data of the key nodes, a service traffic change trend and traffic dense area distribution characteristics are obtained. According to the method, the bandwidth allocation strategy is dynamically optimized, the bandwidth resources at the junction are reconfigured, and the regional service health degree is evaluated. And if the degradation is not effectively controlled, monitoring and detection mechanism parameters can be adaptively adjusted, and continuous analysis and control of link abnormity are realized, so that the network performance and the service quality are effectively improved.

The invention discloses an unmanned aerial vehicle inspection method and system based on AI visual control, and belongs to the technical field of unmanned aerial vehicle automatic control, and the method comprises the steps: carrying out the feature component extraction and compression according to discontinuous frame image data collected by an airborne camera and preset inertial navigation data, and obtaining a compressed feature flow; performing multi-mode obstacle safety level parameter analysis, generating an obstacle avoidance decision priority map, constructing a safety corridor, and generating a real-time self-correction route; semantic analysis is carried out on the deviation between the real-time flight trajectory and the real-time self-correction route, and target area abnormal mark data is generated; and dynamically adjusting the bandwidth allocation of the dual-channel communication network, and transmitting the abnormal mark data of the target area to a ground control terminal. According to the method, a non-continuous frame image and inertial navigation fusion modeling mechanism is adopted, and a multi-mode obstacle safety grading and double-channel dynamic bandwidth allocation strategy is combined, so that real-time response of dynamic obstacle avoidance, accurate judgment of anomaly detection and efficient transmission of key data can be realized.

The invention discloses an Internet of Vehicles communication resource allocation method based on federal multi-agent deep reinforcement learning, and belongs to the technical field of deep crossing of intelligent transportation, wireless communication and distributed machine learning. According to the technical scheme, in an Internet of Vehicles scene, a vehicle is taken as an agent, and local training is performed through a multi-agent depth deterministic strategy gradient algorithm: each agent decides spectrum access, power control and bandwidth allocation based on a local state; asynchronous federation learning is adopted, each agent uploads local model parameters to a global server, weights are dynamically adjusted based on model updating quality, communication quality and updating frequency, and a global model is generated through weighted aggregation; and issuing the updated global model to an intelligent agent to realize distributed privacy protection and dynamic optimization of communication resources. The method has the beneficial effects that the spectrum efficiency, the transmission success rate and the system adaptability are remarkably improved on the premise of ensuring the data security, and the method has wide application prospects and commercial values.

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

The invention 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 relates to the technical field of data transmission and updating, in particular to a data transmission and updating system and method of a cloud mobile phone. According to the technical scheme, the system comprises an intelligent network monitoring module, a dynamic bandwidth allocation module, a server load balancing module, an intelligent data synchronization module and a cache management module, and the intelligent network monitoring module monitors network conditions, including network bandwidth, network congestion degree and network stability, between a user terminal and a cloud server in real time. Through the synergistic effect of the intelligent network monitoring module, the dynamic bandwidth allocation module, the server load balancing module, the intelligent data synchronization module, the cache management module and the like, the network condition is accurately monitored, the bandwidth is reasonably allocated, the server load is optimized, the data synchronization and completeness are ensured, and the cache efficiency is improved; stable and reliable network connection, preferential key data transmission and rapid data synchronization and loading are brought to users, and the use experience of the cloud mobile phone and the overall performance of the system are greatly improved.

The invention relates to the technical field of vehicle network control, in particular to an efficient vehicle network control system and method based on CAN-FD, and the system comprises a data transmission optimization module, a bandwidth management module, a signal scheduling control module, an encryption security control module and an anomaly detection module. In the invention, the bit rate of a data frame, the length of a data packet and the proportion of filling bytes are optimized, the transmission efficiency is improved, the bandwidth occupied by invalid data is reduced, a priority screening mechanism is called, the stable transmission of high-priority signals is ensured, the bandwidth allocation is adjusted based on the flow state and node frequency monitoring, the burst flow congestion is relieved, and the resource allocation is balanced; in combination with arbitration priority and bus conflict state, non-emergency signal priority is optimized, key data blocking risk is reduced, encryption and integrity verification are adopted, data security is ensured, tampering and leakage are prevented, data abnormity score and detection are introduced, abnormal data are screened, identification capability is improved, and network potential safety hazard is reduced.

The invention provides a disaster recovery data recovery method and system of a disaster recovery system, and the method comprises the steps: adjusting a network bandwidth allocation proportion according to a priority, and if the target timeliness is higher than a preset recovery time threshold, increasing a real-time power grid alarm data bandwidth proportion, and generating a bandwidth allocation scheme; dynamically scheduling computing resource allocation according to a bandwidth allocation scheme, and if the key evaluation characteristic exceeds a set upper limit, increasing a computing resource share of a service key level, and generating a resource allocation decision; and after the priority updating scheme is obtained, monitoring a system load in concurrent request processing through a disaster recovery system, and if the system load exceeds a preset threshold value, triggering rebalance of network bandwidth allocation in combination with timeliness deviation to obtain a resource optimization result.

The invention relates to the technical field of wireless high-definition audio and video transmission, and discloses a plug-and-play wireless high-definition audio and video transmission method and system.The method comprises the steps that foreground space texture features and audio and voice segments are obtained, and an initial feature set containing space and semantic features is obtained through semantic correlation analysis; a unified representation vector is output through multi-modal feature fusion, and a dynamic importance score is obtained by determining time sequence consistency, calculating an importance weight and performing normalization; and when the score exceeds a threshold value, segmenting the video frame in real time to determine an attention focus area and optimize a boundary, thereby generating an attention weight matrix, preferentially allocating bandwidth and forming a partition differentiation compression result. And in combination with a network bandwidth state, protection is enhanced for a key stream, the priority and the bit rate are dynamically adjusted, and high-quality audios and videos are output through decoding and recombination. According to the invention, the bandwidth allocation and compression strategy can be dynamically optimized, the transmission quality of a key area is guaranteed when the bandwidth fluctuates, and the audio and video transmission efficiency and experience are improved.

The invention discloses a dynamic traffic scheduling method and system based on an SD-WAN technology, which can timely discover potential problems in a network by monitoring performance parameters of network links and nodes in real time, and can effectively relieve network congestion and improve the overall network performance based on analysis of the performance parameters and dynamic adjustment of network routing and bandwidth allocation strategies. According to the method, a high-flow time period, a low-flow time period and key service flow are identified, so that the distribution of network resources is more reasonable and efficient, the adjusted network performance is evaluated in real time, the expected effect of each adjustment can be ensured, and if the performance does not reach a preset standard, the scheduling strategy is continuously optimized, and the scheduling efficiency is improved. According to the technical scheme, the method is beneficial to adapting to rapidly changing network environments and service requirements, the stability and reliability of the network are enhanced, the network states, scheduling strategies and performance evaluation results before and after adjustment are recorded in logs, and operation and maintenance personnel can rapidly position network problems by analyzing log data, so that the operation and maintenance efficiency and accuracy are improved.

The invention belongs to the technical field of bandwidth adjustment, and particularly relates to a distributed monitoring bandwidth adjustment method and system capable of self-adaptive scheduling, which can ensure that high-priority nodes can preferentially obtain bandwidth resources by collecting network state data in real time and dynamically adjusting the bandwidth demand priority of each node. And the central scheduling node gathers priority information of all nodes, generates a global bandwidth allocation scheme, and continuously adapts to changes of network loads and monitoring requirements through a closed-loop adjustment process. According to the method, the utilization rate of bandwidth resources is remarkably improved, the stability and reliability of the system are enhanced, the phenomena of data transmission delay and packet loss are reduced, and meanwhile, the key nodes can still obtain sufficient bandwidth support under the condition of high load or emergency, so that the flexibility and the response speed of the whole distributed monitoring system are improved.

The invention discloses a remote medical data acquisition method and system based on a 5G network, and the method comprises the steps: collecting 5G network state information in real time, calculating a network state information monitoring index, can dynamically adjust a data transmission strategy, and guarantees the timely and safe transmission of key medical data under a complex network condition; meanwhile, a cache and bandwidth cooperation factor and an intelligent cache strategy factor are introduced, the cache depth and bandwidth allocation are dynamically adjusted according to the network state and the medical data priority, intelligent cooperation management of bandwidth and cache is achieved, and continuity of medical data transmission is guaranteed; the constructed early warning model can detect network abnormity in time and trigger alarm, important data are processed preferentially according to an alarm level adjustment strategy, and the abnormity processing and data recovery capability is improved.

The invention discloses a federated learning terminal selection and resource scheduling method based on a dynamic priority, and relates to the technical field of user selection and bandwidth allocation of federated learning, and the method comprises the steps: obtaining a model basic structure and resource information parameters exchanged between a federated learning central controller and a user; calculating a priority value of each user according to the resource information parameters, and sorting the users according to the priority values from large to small; selecting a user subset meeting a training delay requirement based on a user priority sequence; for the user subset, calculating the minimum bandwidth allocation proportion required for completing the training task, and calculating and considering the data volume, the calculation capability and the network condition of the user; bandwidth resources are allocated to the user subsets by adopting a dichotomy, and bandwidth allocation is adjusted through iteration by adopting the dichotomy; and judging whether the total energy loss of the user subset exceeds a given energy constraint threshold, and if so, deleting the user with the lowest priority from the user subset. The federal learning performance is improved to the maximum extent.

The invention discloses a hospital internal network security isolation method based on an all-optical network architecture. The method comprises the following steps: S1, dividing a hospital internal network into a plurality of virtual optical slices by using an all-optical network slicing technology; s2, performing time domain isolation by using an optical time domain multiplexing technology, and transmitting data on different optical wavelengths by using a wavelength selective switching technology; s3, monitoring and managing bandwidth allocation through a software defined network control platform; s4, traffic prediction and resource optimization are carried out based on a decision tree integration algorithm; s5, detecting potential anomalies and security threats by using the graph neural network; s6, abnormal behaviors are detected through an isolation forest algorithm, and abnormal traffic is marked and isolated; s7, recording a network traffic log through a block chain technology; and S8, when a network fault occurs, using an intelligent self-healing mechanism to automatically switch redundant optical path resources and recover the optical path. According to the invention, all-optical network slicing and artificial intelligence technologies are fully utilized, and security isolation and resource optimization of a hospital internal network are realized.

The invention relates to the related technical field of information transmission processing, in particular to a docking station adaptive data transmission optimization system and method, and the method comprises the steps: multi-module collaborative optimization docking station transmission: dynamically collecting port data, intelligently analyzing a configuration strategy, correcting cache congestion in real time, generating a control instruction, and feeding back an adjustment protocol; the technical problems that the bandwidth allocation strategy cannot adapt to the connection state of the port equipment and the sudden change of the data transmission requirement, the power distribution of the power supply is not matched with the equipment load, and the stability and reliability of the data transmission are limited are solved, the bandwidth allocation proportion of each port is dynamically adjusted, the bandwidth waste and congestion phenomena are reduced, and the data transmission efficiency is improved. The technical effects of improving the smoothness and the real-time performance of data transmission, improving the energy efficiency by cooperatively adjusting the distribution of power supply power based on a power supply power distribution strategy of an equipment compatibility thermodynamic diagram, reducing data packet loss and transmission errors by adopting a congestion risk control and cache management strategy, and improving the stability and the reliability of data transmission are achieved.

The invention discloses a bandwidth allocation method and device and electronic equipment. The method comprises the following steps: detecting a plurality of network flows respectively corresponding to a plurality of interfaces connected with a transformer substation in network equipment; analyzing the plurality of network flows and the time information of the first statistical period by using a flow prediction model to obtain flow prediction results corresponding to the plurality of network flows in a second statistical period; determining the change trend of the traffic indicated by the traffic prediction results corresponding to the plurality of cameras; for each camera of the plurality of cameras, adjusting a bandwidth allocation weight corresponding to the camera at least according to the change trend; and carrying out bandwidth allocation on the traffic of the camera according to the bandwidth allocation weight. According to the method and the device, the technical problems of complicated operation and low efficiency due to the fact that manual adjustment of hardware equipment and hardware parameters is mainly depended on when the problem of image retrieval abnormity of cameras deployed on a large scale in a transformer substation is solved in related technologies are solved.

The invention discloses an industrial internet trusted data communication method and system, and relates to the technical field of data communication, and the method comprises the steps: taking an equipment end and an employee end as data collection points, building an initial trust value for each data collection node, and obtaining a dynamically adjusted trust value for each data collection node according to the historical performance and real-time state of the data collection node; classifying and aggregating the collected data according to the data type and the trust value; dynamically allocating bandwidth resources according to the trust value and the data type; after data transmission is completed, a bidirectional confirmation mechanism is started, a sender and a receiver confirm whether the data is successfully sent and received through a feedback mechanism, and if the sender does not receive a confirmation message within a specified time, a timeout mechanism is triggered, and a data packet is sent again until the data packet is confirmed to be received; and calculating an average transmission success rate, and dynamically adjusting strategies of data acquisition, compression and bandwidth allocation.

The invention relates to the technical field of wireless communication, in particular to a multi-orbit elastic communication method and system, and the method comprises the steps: monitoring the performance parameters of a multi-orbit satellite link in real time, and calculating the comprehensive score of each satellite link of the multi-orbit satellite link based on a preset scoring function; dynamically adjusting a configuration strategy of the main backhaul link according to the comprehensive score and a reinforcement learning model; when a network fault or congestion is detected, activating an alternative backhaul path to complete flow redirection and breakpoint resume, and executing a corresponding disaster recovery strategy according to a fault level; and dynamically adjusting bandwidth allocation according to the authorization level of the user equipment. According to the invention, the elastic communication service with wide-area coverage, low time delay and high reliability can be realized through multi-orbit satellite cooperation, efficient disaster recovery switching and priority resource guarantee in a complex scene.

The invention relates to an end-side cloud collaborative intelligent optimization and resource scheduling method and system for an industrial Internet of Things. The method comprises the steps that sparse processing and quantization are conducted on model parameters on end equipment through accelerator hardware, the storage and transmission requirements of a model are reduced, and meanwhile the accuracy of the model is kept; through the knowledge extraction technology, the end equipment can extract key information in the data, and high-quality input is provided for subsequent data processing and model training; by deploying the lightweight reasoning model and the routing model in the edge device, the uploaded data can be preliminarily classified, and only the data which is difficult to process is sent to the cloud, so that the overall delay is reduced to the greatest extent while the accuracy is kept; performance monitoring, bandwidth allocation and task segmentation are carried out on end equipment and edge equipment in real time through a cloud end, and global model optimization and resource scheduling are responsible for realizing optimal performance.

Techniques for performing distributed rate limiting in networks in a cloud environment are described for determining an amount of network bandwidth available to be processed by flow control nodes within a cloud network for a first time period, determining a bandwidth allocation for traffic classes for the first time period, determining, a portion of the bandwidth allocation for the flow control nodes, providing, data to the flow control nodes, where the data indicates the portion of the bandwidth allocation for the traffic classes, and receiving, second data that indicates an amount of network traffic routed during the first time period by individual ones of the flow control nodes.

The invention relates to an FTTR bandwidth management method based on a PON, and the method comprises the steps: dividing a to-be-managed region into a plurality of sub-regions according to the demands, distributing independent IP sub-networks, predicting the service of each IP sub-network, carrying out the pre-distribution, collecting the ONU flow data in real time, carrying out the feature extraction, obtaining the flow change features, dynamically adjusting the bandwidth distribution strategies of different slices, and constructing a double-layer dynamic weight model. Each network slice corresponds to an independent weight adjustment strategy, a dynamic time slot distribution field is inserted in an MPCP protocol, time slot distribution is carried out according to weight values of different network slices, burst traffic is preprocessed, demand prediction values are reported according to network slice classification, burst traffic information and traffic feature data are integrated, and the data are distributed according to the burst traffic information and the traffic feature data. And dynamically allocating bandwidth to each terminal device in the FTTR network. FTTR network bandwidth fine and dynamic management is achieved through multi-dimensional data processing, the network resource utilization rate and the user service quality are effectively improved, and the transmission requirements of diversified services are met.

The invention discloses a link bandwidth allocation method and system for multilink aggregation of a multimodal mobile network. The method comprises the following steps: acquiring a mobile network base station, an equipment position and real-time environment data; an intelligent power control algorithm is adopted, and transmission power is dynamically adjusted according to environment data and network loads; acquiring real-time signal intensity data and historical data from the network equipment to the base station; predicting a minimum transmission point of signal transmission based on real-time and historical data; adjusting the direction and position of an antenna according to the position of the base station, and designing connection by adopting a beam forming antenna; setting a threshold value according to the real-time weather and the minimum transmission point data, and deploying a signal enhancer; according to the link bandwidth allocation method and system for multi-link aggregation of the multi-modal mobile network, the link quality is monitored in real time, the network is dynamically adjusted, the network load is balanced through an intelligent algorithm, the signal transmission environment is evaluated in combination with real-time weather data, the signal enhancer is deployed, and the signal coverage range is expanded.