587 results about "Heterogeneous network" patented technology

A system for adaptively caching network communication protocols enhances efficiency across heterogeneous device environments through a multi-level cache architecture with device-capability-based tiers. The system collects endpoint telemetry data including device capabilities and operational constraints to classify endpoints and generate context-aware protocol variants optimized for specific device types. Protocol optimization opportunities are determined through structural analysis of message patterns and state transitions. The system performs protocol deduplication by identifying functionally equivalent variants and maintaining canonical representations to reduce cache redundancy. Cache synchronization across distributed nodes uses enhanced Merkle tree structures with protocol normalization processing. The system predicts communication needs based on historical patterns, network context, and endpoint constraints, enabling proactive cache management tailored to device capabilities. Integration with event-driven data communication systems enables seamless protocol selection and translation while maintaining compatibility between diverse endpoint types, from high-performance servers to resource-constrained IoT devices.

The invention relates to the technical field of communication, in particular to an underground power distribution room communication system and method based on heterogeneous network and multi-modal fusion, and the system comprises a three-dimensional heterogeneous network cooperation module, a cross-modal feature fusion module, a dynamic routing decision engine module, a self-adaptive interference suppression system and a cross-layer cooperation optimization module. The three-dimensional heterogeneous network cooperation module comprises a 4G / 5G wireless communication sub-layer, a power line carrier communication sub-layer and an edge computing management sub-layer; the cross-modal feature fusion module comprises a multi-modal encoder group, a shared feature projection layer, a twin network structure and a cross-modal attention fusion module; and the dynamic routing decision engine module comprises a state space monitoring unit, a routing optimization unit and a millisecond-level path switching strategy. Through the arrangement, the reliability, the real-time performance and the energy efficiency of communication of the underground power distribution room are systematically improved, and a high-robustness communication infrastructure is provided for an intelligent power grid.

The invention discloses a vehicle-mounted cross-protocol data time sequence cooperative processing method, which comprises the following steps: establishing a unified time reference, and providing an accurate space-time coordinate system for heterogeneous network nodes by electing a global master clock and constructing a clock relation model and a periodic correction mechanism; systematic cognition and management of communication resources are realized, and a verified protocol capability table is generated by automatically identifying protocol types and variants; constructing an automatic mapping system from demand to execution, performing formalized packaging on a target scene by introducing a unified intermediate model, generating a cross-protocol mapping rule based on the model and a protocol capability table, and then forming a global scheduling table in combination with a unified time reference; the cooperative communication of all nodes is finally realized by using the global scheduling table, and the end-to-end delay is constrained within the preset range, so that the problem that the end-to-end time sequence in the vehicle-mounted heterogeneous network is uncontrollable is solved, and the controllability and reliability of the time sequence of the vehicle-mounted network are improved.

The invention relates to the technical field of network communication, and discloses a vehicle-mounted edge computing data recording system and method based on protocol adaptive analysis, and the system comprises a multi-protocol network access controller which is used for capturing an original data frame and extracting a physical feature triple; the identification analysis engine is used for executing hash operation on the triple to generate a physical feature code and retrieving a physical logic address mapping table; the direct memory access controller is used for responding to a target memory address pointer hit by retrieval and directly writing a data load into an input buffer area of the functional operation module, and by constructing a direct addressing mechanism based on Hash mapping, thorough decoupling of vehicle-mounted heterogeneous network physical topology and edge computing logic is achieved.

The invention relates to the technical field of wireless communication, in particular to a wireless communication network system and method for intelligently fusing a multi-mode heterogeneous network. Comprising a multi-mode access unit; a protocol compatibility and conversion unit; the heterogeneous network intelligent fusion unit completes cross-network dynamic flow collaboration and resource optimization decision through cross-layer feature association mining, service-network two-dimensional weight calibration and a double-closed-loop feedback optimization mechanism, generates a resource scheduling instruction and transmits the resource scheduling instruction to the intelligent scheduling and resource control unit; an intelligent scheduling and resource control unit; and a system control and cooperation unit. According to the invention, the service-network two-dimensional dynamic fusion weight is constructed through the intelligent fusion unit of the heterogeneous network, and bandwidth, frequency spectrum and power resources are allocated according to the priority and margin balance principle in combination with the intelligent scheduling unit, so that the problem of insufficient two-dimensional coordination of resource scheduling is solved, the resource scheduling is matched with the service demand and the network load, and the resource scheduling efficiency is improved. And resource waste or incapability of meeting business requirements is avoided.

The invention relates to the technical field of mobile communication transmission, and discloses a heterogeneous network multilink parallel mobile communication transmission method and system. A dynamic link aggregation module of the system collects link state parameters including signal strength, delay jitter and packet loss rate from a plurality of heterogeneous network interfaces in real time; a flow distribution decision module calculates available bandwidth weight of each link according to the data and generates a dynamic flow distribution strategy; the data fragment packaging module splits to-be-transmitted data into a plurality of data fragments according to the strategy, and adds a sequence identifier and a link identifier to each fragment; the multi-channel concurrent transmission module sends corresponding data fragments in parallel through a specified heterogeneous network link; and the receiving recombination verification module sorts the recombination data fragments according to the sequence identifiers, and detects the data integrity through a verification mechanism. According to the system, a set of complete multi-link parallel transmission solution is formed, and the problems existing in a traditional single link and an existing multi-link transmission technology can be effectively solved.

The invention discloses a multi-source heterogeneous network security alarm aggregation noise reduction method, system and device. The method comprises the following steps: step 1, constructing a network security alarm ontology model; step 2, standardization processing of multi-source alarm; 3, performing dynamic alarm aggregation based on an entity relationship; 4, multi-level alarm noise reduction and intelligent study and judgment are carried out; according to the method, deep standardization is carried out on multi-source heterogeneous alarms through the network security alarm ontology model, and a data semantic gap is eliminated; a dynamic aggregation strategy based on a core entity and a relationship is adopted, related alarms surrounding the same core entity in a specific time window are aggregated into aggregated alarms, the order of magnitude of the number of the alarms is reduced, and a complete attack scene description is formed; a three-layer progressive noise reduction mechanism is adopted, false alarms and low-value alarms are eliminated, and high credibility of output safety events is guaranteed; automatic conversion from massive original alarms to a small number of high-value security events is realized, and the security operation response speed and decision quality are improved.

The invention relates to the field of network communication, and discloses a multi-source heterogeneous network data cooperative transmission method based on dynamic multi-dimensional evaluation and intelligent disaster recovery, which comprises the following steps: collecting system network parameters of a 5G network and a long-distance wired network in real time through a software definition interface module; performing weighted evaluation on the acquired system network parameters based on a dynamic link selection engine, the evaluation dimensions including real-time bandwidth, transmission delay and current link traffic, and generating an optimal communication link combination scheme; carrying out fragmentation and protocol adaptation on the data by adopting a general packaging framework and an intelligent label technology; distributing multi-path parallel transmission according to a priority strategy; at a receiving end, data recombination and disaster recovery supplementary transmission are realized through network coding and multi-path cooperation; and the evaluation weight is dynamically optimized in combination with reinforcement learning. According to the invention, the problems of rigid link selection, low protocol conversion efficiency and insufficient disaster tolerance in the prior art are solved.

The invention discloses a BIM building intelligent integrated management system based on Internet of Things control, and relates to the technical field of networking technology and building intelligent management, and the system comprises a sensing layer, a transmission layer, a platform layer and an application layer. The sensing layer comprises a multi-source heterogeneous sensor cluster and is divided into an environment monitoring unit, an equipment state acquisition unit, a personnel positioning unit and a structure health monitoring unit, and each unit is provided with a corresponding sensor; the transmission layer adopts a LoRaWAN and 5G fusion architecture and comprises an edge computing gateway, a TSN switch and a data security encryption unit, and the gateway can perform frequency domain analysis and the like; the platform layer is based on micro-service and is provided with a multi-source data fusion engine and a BIM model dynamic updating module; the application layer provides an equipment fault prediction module, an energy optimization module and a safety risk early warning module, and all the modules adopt corresponding algorithms. According to the invention, a hierarchical collaborative architecture is constructed, a multi-source sensor, a heterogeneous network and the like are integrated, deep integration of multi-dimensional management of a building is realized, and the problems of subsystem independence and data obstruction of a traditional system are solved.

The invention provides a vision-based cross-network interaction method and system, and relates to the technical field of intelligent interaction, and the method comprises the steps: obtaining a visual interaction sequence, constructing multi-modal feature representation, achieving cross-domain semantic alignment, deconstructing visual information into a hierarchical control instruction set, and transmitting the hierarchical control instruction set to a target network environment for execution after security classification. And a bidirectional mapping relation graph is constructed to realize incremental optimization. According to the method, semantic bridging between heterogeneous networks can be established, the cross-domain control precision is improved, and meanwhile safe interaction in a network isolation environment is guaranteed.

The invention relates to the technical field of network switching, in particular to a heterogeneous network dual-mode self-adaptive switching method and system. According to the method, the multi-dimensional environment sensing data and the initial signal intensity are acquired, the signal intensity is calibrated in a dynamic environment, the dynamic response of the network state to real-time change is realized, and the connection state characteristic and the side network consumption index of the dual-mode network are acquired by combining the calibrated signal intensity. The switching demand can be evaluated on the basis of the data, the switching demand can be judged more accurately through the multi-dimensional evaluation mechanism, the limitation that a traditional method only depends on signal strength is avoided, and the switching demand can be evaluated by generating an optimized directed time sequence graph and a network performance data set. According to the technical scheme, the equipment can make a scientific and reasonable switching decision according to the real-time network state snapshot data and the preset optimization time sequence graph, and the connection requirements of the equipment can be dynamically adapted under the variable network conditions, so that the optimal network experience is kept, and the network connection quality is improved.

The invention discloses a wide-area time traceability credible authentication method in a power heterogeneous network environment, and belongs to the technical field of power system informatization and automation. Comprising the following steps: acquiring various high-precision time source information in a power heterogeneous network environment, and acquiring an initial time reference of the power system time synchronization device; generating uniform reference time, and embedding a digital watermark containing time source information and credibility thereof for each timestamp by using the digital watermark embedding module; controlling the power system time synchronization device to sequentially generate time transmission fingerprints at all levels of network nodes; constructing a unique time fingerprint chain covering the whole link; packaging the time fingerprint of each time transmission node and the traceability information thereof, and performing uplink storage; precise prediction and optimal control of time transmission errors are realized; if the overall cumulative time error exceeds a range of + / -10 [mu] s, the predictive correction is maintained until the error is controlled within + / -10 [mu] s.

The invention discloses a rail transit multi-network integration method based on a digital trunking technology, relates to the technical field of communication, and aims to solve the problem that a traditional narrowband trunking system cannot meet the requirements of voice and data comprehensive bearing and vehicle-ground large-bandwidth service real-time transmission. The method comprises the following steps: constructing a time division duplex long-term evolution broadband digital trunking unified bearing platform; an intermediate media access control layer fusion architecture is deployed, and seamless mobility management of the heterogeneous network is realized through unified authentication and multi-link aggregation; an intelligent vertical switching algorithm based on prediction and multi-criterion decision is introduced, a bidirectional long-short-term memory network model is utilized to predict a network state trend, and an improved entropy weight method and an analytic hierarchy process are combined to dynamically select an optimal access network according to service requirements. According to the invention, the network operation efficiency and the user experience can be obviously improved, and high reliability and high service quality of the rail transit communication system are ensured.

The invention relates to the field of low-altitude communication network planning methods, in particular to a 5G three-dimensional coverage and capacity planning design method for low-altitude economy, which comprises the following steps: performing airspace range limitation and application scene division on a target airspace, establishing a mobile model of a low-altitude terminal, and providing dynamic input for simulation; the method comprises the following steps: establishing a dual-frequency heterogeneous network, and determining base station addresses covering targets at different heights and meeting different signal station spacing; performing three-dimensional coverage and quality simulation on the established dual-frequency heterogeneous network, performing network KPI evaluation on the simulation until the standard is reached, and outputting a network deployment planning scheme; deploying according to a network deployment planning scheme, predicting low-altitude service flow, and adjusting a beam direction and a PRB reservation ratio to realize on-demand allocation of resources; and carrying out actual measurement on the deployed network, collecting an air measurement index, comparing a comparison deviation between the air measurement index and a simulation result, and carrying out fine adjustment on the network according to the comparison deviation. According to the invention, diversified communication requirements are met, and the success rate of terminal access is improved.

The invention discloses a multi-layer heterogeneous sequential network feature alignment and clustering method and device based on tensor self-representation. The method comprises the steps that sequential feature matrix sequences {},..., {} of data views in a multi-view heterogeneous network in time windows are obtained; based on the matrix sequence of the first time window, constructing a Laplacian regular term by introducing a self-representation learning mechanism, modeling multiple views by adopting a tensor structure and introducing a Schatten p-norm regularization mode to construct an optimization objective function for optimization, and representing shared feature representation of each data view in the first time window; and solving the function and carrying out clustering processing on the obtained function, wherein the clustering result of each time window is used for carrying out characteristic analysis on nodes in the network. According to the method, on the premise that the original structure and semantics of the network are guaranteed, unified modeling can be carried out on the incomplete multi-view heterogeneous network, and feature expression is aligned.

The invention provides a drug-disease association prediction method and system, computer equipment and a medium, and belongs to the technical field of computers. The method comprises the following steps: constructing a drug-protein-disease heterogeneous network, and extracting a plurality of element path sub-graphs; inputting the meta-path sub-graph into a multi-scale diffusion graph convolution module, executing learnable multi-step graph diffusion on the basis of graph convolution, synchronously capturing local adjacency and high-order topological information, and generating node embedding; and performing dynamic weighted fusion by utilizing meta-path attention to obtain unified representation. In order to relieve imbalance of positive and negative samples, implementing difficult negative sampling in the embedding space, and constructing a balance training set with the positive samples; medicine-disease features are spliced, a regularization XGBoost classifier is trained, and unknown correlation accurate prediction is achieved. By adopting the method, the drug-disease association prediction precision and efficiency are improved, multi-scale topology and priori knowledge are fused, and a powerful calculation tool is provided for drug relocation.

The invention relates to the technical field of telecommunication. By providing the multi-domain strategy collaborative dynamic decision optimization method, system, equipment and medium, the method comprises the following steps: extracting cross-domain common characteristics of network layer topology, equipment state and alarm information, retaining differential characteristics of a transmission network and a data network, and generating a uniform resource data set; on the basis of the unified data set, a global optimization strategy is generated through linkage decision making of a three-level collaboration module; matching the strategy into an atomic instruction set executable by a heterogeneous network manager by utilizing semantic ontology mapping and syntax tree matching; and according to the instruction execution feedback data, dynamically adjusting the strategy weight and carrying out iterative optimization, and generating an updated global strategy, so as to achieve the technical effects of improving the cross-domain resource perception precision, enhancing the hierarchical decision collaborative efficiency and reducing the multi-manufacturer instruction conversion error rate.

The invention provides a satellite-ground heterogeneous network dynamic switching method and system and electronic equipment, and relates to the technical field of wireless communication, and the method comprises the steps: carrying out the collection of core state parameters from a network side, a user side and a service side, and obtaining the state parameters, related to network switching, of the network side, the user side and the service side; performing dynamic association processing on the state parameters respectively corresponding to the network side, the user side and the service side to generate a unified state vector; performing dynamic decision optimization according to the unified state vector through a reinforcement learning model to obtain a satellite-ground switching decision weight; according to the satellite-to-ground switching decision weight, generating a satellite-to-ground network comprehensive score difference, and according to the satellite-to-ground network comprehensive score difference, determining a network switching target and a decision confidence coefficient of the network switching target; and determining an execution parameter of the network switching target according to the decision confidence through a Bayesian execution engine, and performing network switching according to the execution parameter. According to the invention, the switching effect of the satellite-ground heterogeneous network is improved.

The invention discloses a heterogeneous network converged communication control method and system for a vehicle-mounted terminal, and relates to the related technical field of communication control, and the method comprises the steps: determining a plurality of original signal fragments transmitted to a receiving end by a plurality of heterogeneous networks based on the vehicle-mounted terminal; a vehicle-mounted terminal is provided with an intermediate fusion node, and the intermediate fusion node is provided with an interference detection module and a differential processing module; carrying out adaptive signal differential coding processing according to a synchronous receiving constraint condition of a receiving end and the plurality of link interference detection signals, and outputting a plurality of differential signal fragments; and respectively sending to a receiving end for signal restoration. The technical problem that in the prior art, when a vehicle-mounted heterogeneous network sends the same or fragmented signals at the same time, due to dynamic variation of network link interference and transmission delay difference of all paths, signals at a receiving end are out of step and quality is deteriorated is solved. The technical effects that the receiving end efficiently and synchronously restores the signal, and the anti-interference performance of signal transmission and the reliability of heterogeneous network converged communication are improved are achieved.

The invention discloses a multi-level network threat dynamic identification method based on a graph neural network, and the method comprises the following steps: collecting multi-source heterogeneous network security data, and carrying out the preprocessing; constructing a multi-level network threat graph; inputting the multi-level network threat graph into an improved GraphSAGE network to carry out graph embedding modeling; identifying an attack propagation path, and extracting a risk sub-graph region serving as a candidate attack chain; performing threat level evaluation on the risk sub-graph region, and calculating an overall threat score of the risk sub-graph region; and comparing the overall threat score with a preset threshold value, if the overall threat score exceeds the threshold value, determining that the threat is a high-risk threat, and outputting an early warning result. The multi-level threat graph is modeled through the graph neural network, attack chain recognition and threat evaluation are achieved, and the method has the advantages of being high in expressive power, accurate in recognition and fast in response.

The invention discloses a fault diagnosis method under an imperfect information condition based on orthogonal space heterogeneous mapping, and relates to the technical field of power system key component fault diagnosis. A hierarchical fusion multi-dimensional fault feature extraction network based on a cross domain attention mechanism is provided and is used for extracting features of a complete data set in a fault set, and a multi-dimensional feature vector encoder is formed. For incomplete and missing data, an enhanced orthogonal spatial heterogeneous network embedded with a multi-dimensional feature vector is provided, a data reconstruction process is optimized by introducing a multi-dimensional feature vector encoder and an identical mapping residual block and integrating a fault feature frequency and a generative adversarial reconstruction loss function, and the integrity of the data is enhanced. For missing and wrong labels, a label self-correction strategy based on space differentiation is provided, the strategy not only considers space information feature matching between different fault types and different sensors, but also provides space differentiation feature frequency projection, and therefore the accuracy of data labels is improved.

The invention discloses a drug relocation model construction method for simultaneously predicting drug-target interaction and drug-disease incidence relation, and belongs to the field of drug research and development, and the method comprises the following steps: integrating heterogeneous networks and attribute characteristics of drugs, targets and diseases, learning multi-relation node embedding by using RGCN, and constructing a drug relocation model for simultaneously predicting drug-target interaction and drug-disease incidence relation; a Gelato algorithm is combined to enhance a network structure, an auto-covariance is introduced to calculate a potential association score, and drug-target interaction and drug-disease association are synchronously predicted; the weighted cross entropy and N-pair loss joint optimization is adopted, unbiased training is realized, the problems of class imbalance and network sparseness are solved, and the model generalization ability and prediction precision are improved.

The invention discloses an acoustic-electric cross-medium heterogeneous network end-to-end time delay analysis method based on random network calculation. The method comprises the following steps: firstly, constructing a heterogeneous protocol service model of an underwater acoustic (UWA) link and a radio (RF) link, and modeling an FC-ARQ mechanism and a CSMA / CA access behavior by adopting a Markov process; secondly, realizing cross-medium service coupling modeling by unifying time slot scale and introducing protocol conversion, time slot alignment and fragmentation recombination overhead; furthermore, the arrival and service yoke process is constructed based on the yoke theory, and a closed upper bound expression of the end-to-end time delay violation probability is deduced by using the stop time theorem. The method can accurately reflect time delay behaviors caused by non-conservation, asynchronization and protocol switching in a multi-medium system, and is suitable for performance evaluation and resource scheduling optimization scenes in an underwater wireless and air wireless fusion network.

The invention discloses a multi-level and multi-mode target identification and dynamic tracking method based on an unmanned aerial vehicle, and relates to the technical field of target identification and tracking, and the method comprises the steps: obtaining target information in the tracking process of the unmanned aerial vehicle, processing visual features and semantic features through a double-flow heterogeneous network, and generating a fusion feature map; recognizing a search object in the fused feature map, locking a tracking target based on a target evaluation and motion prediction result, and starting real-time dynamic tracking of the unmanned aerial vehicle; and periodically calculating the coordinate position of the tracking target relative to the unmanned aerial vehicle, adaptively adjusting the calculation frequency through regional warning monitoring, and continuously tracking the tracking target. According to the method, different levels of target identification are established, the object range is defined through the target contour, the target to be tracked is determined through the color, the vehicle mark, the animal hair color, the dressing and vehicle color and the like, effective combination of target identification and a dynamic tracking technology is realized, and automatic searching and automatic tracking of the target needing to be searched can be completed.

The invention relates to the technical field of network security, and particularly discloses a heterogeneous network security defense system and method based on artificial intelligence, and the system comprises a full-dimensional perception layer which is used for obtaining original data of heterogeneous network security through a hardware-level data collection and protocol self-adaption technology; the cognitive enhancement layer is used for undertaking the output of the full-dimensional perception layer and optimizing the threat identification precision through four-dimensional spatial-temporal feature fusion and antagonism feature purification; the intelligent decision-making layer is used for accurately depicting a complex attack mode through hypergraph modeling and causal reasoning based on output of the cognitive enhancement layer; according to the method, through integration of four-dimensional spatial-temporal feature fusion and antagonistic feature purification technologies, the identification precision of complex and variable threats in a heterogeneous network is remarkably improved, especially for unknown or variable attack means; by means of hypergraph modeling and causal reasoning technologies, a complex attack mode is accurately described, an optimal defense action sequence is automatically generated, and conversion from passive defense to active defense is achieved.

The invention provides a remote control method and device for intelligent multimedia interaction equipment, equipment and a medium, which are used for improving the real-time performance and the execution success rate of remote control and enabling complex multimedia interaction to be reliably operated on a heterogeneous network and heterogeneous equipment. The method comprises the following steps: carrying out hierarchical analysis processing on interaction data input by a user to generate perception command data, and carrying out execution planning and resource allocation on the perception command data according to equipment performance characteristics to generate an executable operation sequence, and performing transmission quality evaluation and path selection on the propagation path network according to the executable operation sequence to obtain a target transmission path, and performing protocol encapsulation on the executable operation sequence according to the target transmission path to obtain a remote control instruction data stream.

The invention discloses a heterogeneous network embedding method based on dynamic heterogeneous network decomposition and a hierarchical space-time attention mechanism. The method comprises the following steps: dynamic network decomposition: decomposing a heterogeneous network sequence into independent subgraph sets according to edge types; multi-order node attention aggregation: for each sub-graph, fusing information of nodes and different edge types; semantic level attention is embedded, wherein global semantic embedding is generated in combination with global relation type weight and meta-path long-short-term memory network coding; time dynamic modeling: respectively calculating a time attention weight and a Monte Carlo sampling approximate Horkes intensity, and then aggregating and splicing results of the time attention weight and the Monte Carlo sampling approximate Horkes intensity to obtain a final embedding result. According to the method, through cross-granularity semantic modeling and efficient time sequence dependence learning, an innovative solution is provided for node representation of the dynamic heterogeneous network.

The invention provides an end-network cooperative transmission system and method for a multi-mode network. The system comprises a terminal service demand layer which is used for identifying the service type of a terminal in a multi-mode network, generating structured service demand information and transmitting the service demand information to a network collaborative decision-making layer; the network cooperation decision-making layer is used for fusing the service demand information and the link state information, generating a transmission optimization strategy including path selection, priority mapping, bandwidth allocation and rate control, and transmitting the transmission optimization strategy to the transmission optimization strategy execution layer; and the transmission optimization strategy execution layer is used for executing a transmission optimization strategy, collecting link state information in the multi-mode network in real time through INT, and transmitting the link state information to the network cooperation decision layer. According to the method, efficient scheduling of heterogeneous network resources and high-reliability transmission guarantee of differentiated services are achieved, and the method is suitable for key service scenes sensitive to time delay and reliability, such as Internet of Vehicles and ultra-high-definition video transmission.

The invention discloses a resource allocation and configuration method and device and electronic equipment. The method comprises the following steps: converting network resources in a private network into programmable objects, and constructing a resource label model according to attribute information of the programmable objects and the network resources; receiving service demand information, extracting a service intention in the service demand information, and converting the service intention into a standardized intermediate instruction; generating a resource allocation scheme according to the standardized intermediate instruction and the network resource use state information, and evaluating the resource allocation scheme in a digital twin environment of the private network; and under the condition that the evaluation result of the resource allocation scheme in the digital twin environment meets a preset requirement, converting the resource allocation scheme into a control instruction, and sending the control instruction to the network resource. The technical problems of low network resource allocation efficiency and slow service response speed caused by non-uniform resource description and high service demand analysis difficulty in a multi-manufacturer heterogeneous network environment are solved.

The invention discloses a dynamic optimization system and method for a heterogeneous network communication protocol, and particularly relates to the technical field of communication network automation, and the system comprises a unified time base and multi-source state modeling module, a quick change detection and shadow section risk assessment module, a risk gating and hierarchical low-disturbance execution module and a closed-loop feedback and evolution management module. According to the method, a standard recording unit is constructed through unified time base and observation delay compensation, and multi-source communication state alignment is realized; a shadow section joint risk index is calculated based on online filtering and geographical priori, hierarchical low-disturbance strategy arrangement is implemented under the constraint of risk gating and comprehensive cost, and closed-loop feedback and anti-fact evaluation are utilized to drive parameter evolution governance. According to the method, the problems that short-time fading is smoothly masked in a high-speed or strong-shielding environment and unified risk assessment and low-disturbance execution are lacked are solved, the tail time delay, the disorder rate and the packet loss rate are reduced, the communication reliability is improved, and interpretable tradeoff between energy consumption and tariff is achieved.