5839 results about "Network communication" patented technology

The invention relates to the technical field of data security management, and discloses a blockchain-based forestry data security management system and method, and the system comprises a data collection unit which is used for comprehensively obtaining a multi-dimensional information flow of forest ecology and resource states; the data processing unit is used for carrying out deep cleaning, standardized regulation and feature value extraction on the originally collected mass heterogeneous data; the block chain storage unit is used for constructing a permanent, tamper-proof and distributed secure storage infrastructure platform of the forestry core data; a verification unit; the safety control unit is used for constructing a covering data transmission, storage and access full-chain depth defense system structure model; a user interface unit; an auditing unit; and a network communication unit. The method is reasonable in design, and the intelligent analysis module is used for processing to form a forest interannual growth trend prediction function distribution map state visual output result set.

The invention relates to a network real-time synchronization communication system, and relates to the technical field of computer network communication. The system comprises four core modules: a hardware optical IO synchronization module which integrates a multi-wavelength optical transceiver array and an anti-jitter circuit and provides a nanosecond global clock signal, and the synchronization precision is less than or equal to 15ns; the time sequence arrangement module is used for dividing a fixed time window and a dynamic buffer window based on a time sensitive network, supporting a priority preemption mechanism of the SRIO bus and realizing deterministic data transmission; the distributed RTDATA nodes replace a traditional single-board computer, a heterogeneous computing unit and an intelligent storage controller are integrated, and protocol stack processing delay is reduced through the zero copy technology; according to the dynamic multicast routing system, a safely isolated multicast tree is constructed as required, and link load distribution is optimized in combination with machine learning. Through collaborative design of hardware optical synchronization and dynamic data arrangement, the problem of real-time performance reduction caused by multi-node communication concurrence is solved.

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.

A device environment can include a plurality of devices, including an audio device, in communication over a network. An audio device (such as a soundbar) can comprise a speaker, a camera, and other sensors. The audio device can receive information from other devices in the environment including image data from other cameras and physiological data from wearable devices, etc. The audio device can monitor and control aspects of the environment. The audio device can provide information to the user including audible notifications, and can monitor the user including the user's position or physiological condition, alone or in combination with other devices in the environment.

The invention belongs to the field of civil aviation, provides a civil aircraft field service operation scheduling control system, and aims to solve the problem of low cooperative efficiency of multiple links of ground service scheduling. File management is based on an Ali cloud OSS development interface, supports multi-format files, and realizes functions of permission access, encryption and the like; communication adopts an MQ / MQTT architecture to construct an IM system, and supports multi-type message transmission and http network communication; data processing packages a multi-language database interface, and internal and external network secure intercommunication is realized through a gatekeeper agent. Flight functions cover and guarantee node management and control, dynamic updating, cross-department communication, real-time flight data butt joint, task distribution of unified operation according to work types, and support of multi-terminal such as a web terminal and a handheld terminal and nailing access. Ground service multi-scene requirements can be met, and the operation efficiency and the management level are improved.

The invention relates to the technical field of medical rehabilitation, and discloses a lower limb weight-bearing gait rehabilitation training system which comprises a data acquisition module, a data processing and analysis module, a patient individualized modeling module, an intelligent decision and control module, a rehabilitation execution module and a man-machine interaction and medical information interface module which are in communication connection through a network. The data acquisition module is used for acquiring multi-modal data of a patient in real time, and the multi-modal data comprises static sign data, dynamic physiological parameters, kinematics and dynamics parameters and non-motion physiological and psychological state data; and the data processing and analysis module is used for carrying out preprocessing, feature extraction and deep analysis on the original data, and outputting a structured patient individualized feature vector and an evaluation result. According to the invention, a patient three-dimensional skeletal muscle digital twinborn model is constructed through the patient individualized modeling module, and in combination with a continuous learning intelligent model library, body sign differences of different patients can be accurately adapted.

The invention discloses an unmanned aerial vehicle anti-collision method and system based on LoRa communication, and belongs to the technical field of risk avoidance of multiple unmanned aerial vehicles. The method comprises the following steps: constructing an ad hoc network communication architecture to realize flight state broadcast and synchronization; fusing the multi-source data by adopting a space-time alignment algorithm, and constructing a dynamic airspace situation map taking a local machine as a center; calculating a time window and space overlapping probability of the predicted intersection; a multi-priority dynamic negotiation protocol is considered, and autonomous decision making of the unmanned aerial vehicle cluster in a scene without a central node is supported; and dynamically adjusting the flight path, speed and height through a collaborative obstacle avoidance algorithm. Through a spread spectrum modulation technology and an adaptive power control mechanism, over-the-horizon communication coverage of more than 10km level is realized; through fusion of a kinematics prediction model and a risk quantification algorithm, millisecond identification and hierarchical response of collision threats are realized, a global optimal avoidance strategy is achieved, communication delay and calculation bottleneck brought by centralized decision are effectively avoided, and the real-time collaborative obstacle avoidance capability in a complex airspace is ensured.

The invention provides a network security and data security comprehensive analysis method and system based on a large model, and the method comprises the steps: collecting multi-source heterogeneous security data of a network communication link, a data storage node and an application interaction interface, carrying out the risk behavior atomization association processing, and constructing a dynamic risk association hypergraph; based on a preset security domain knowledge graph, calling the large model to execute multiple rounds of risk attribution reasoning, performing attack chain fragment matching and evidence chain completion on a behavior hyperedge set in the dynamic risk association hypergraph, and generating a risk attribution reasoning chain; and constructing a risk evolution probability model according to the risk attribution reasoning chain and the time sequence constraint set of the dynamic risk association hypergraph, and calculating a short-term diffusion probability and a long-term evolution trend vector of each association risk path based on the risk evolution probability model to obtain a risk evolution path prediction result. The pertinence and the dynamic adaptability of protection measures can be improved, and the problem that a static protection strategy is difficult to deal with the hysteresis quality of dynamic risk changes is solved.

The invention relates to the technical field of distributed learning, in particular to a large model pre-training system based on distributed parallel processing. In the system, a data distribution layer collects a node resource state through a fragmentation module and generates a dynamic scheduling strategy; a computing resource layer configuration model initialization module and a strategy switching module support flexible switching of multiple modes such as tensor parallelism, data parallelism and assembly line parallelism; the network communication management layer is combined with topology perception and gradient compression technologies, so that the communication efficiency is improved; and the model aggregation layer realizes global parameter updating and training tuning under privacy protection through a security aggregation and optimization control mechanism. All layers of the system operate cooperatively, the calculation efficiency, the communication performance and the data security of large model pre-training can be effectively improved, and the method is suitable for model development and deployment in a large-scale heterogeneous calculation environment.

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 discloses a multi-agent collaborative data exchange dynamic routing optimization method and system, and relates to the technical field of network communication, and the method comprises the steps: obtaining the real-time state information of each node in a network, and outputting a node state data set; constructing a historical state sequence of each node, calculating a load change trend, and outputting a routing adjustment signal when the load change trend reaches a load critical value; calculating a collaborative weight according to the network contribution degree of each agent, establishing a task allocation mapping relationship among the agents based on the collaborative weight, and outputting a collaborative scheduling result; determining a candidate path set, performing index evaluation on paths in the candidate path set, and outputting an optimal routing path; and executing data transmission, obtaining a quality difference between an actual transmission effect and an expected effect, and performing parameter correction. According to the invention, active optimization and multi-target balance of network routing are realized, and routing efficiency and system stability in a dynamic network environment are improved.

The invention relates to a building module data interface intelligent monitoring system based on the Internet of Things and a deployment method, and belongs to the technical field of building information monitoring. The system is composed of a distributed sensing unit, an edge computing gateway, a cloud platform and a visual terminal, a self-adaptive filtering algorithm and an abnormal mode recognition model are built in the edge computing gateway, the cloud platform adopts a time sequence database to construct a multi-dimensional data warehouse, and structural health degree evaluation is carried out by fusing an LSTM neural network and a random forest algorithm. The deployment method comprises the steps of optimizing a sensor distribution strategy based on a BIM model, establishing a wireless Mesh ad hoc network communication architecture, and configuring a grading early warning mechanism and a fault tracing function. The innovation point is that a dynamic threshold adjustment algorithm and an interface performance degradation prediction model are provided, and real-time monitoring of the connection state of the building module and life prediction are realized. The system has the advantages of flexible deployment, high detection precision and low maintenance cost, and the intelligent level of building structure safety monitoring is effectively improved.

The invention discloses a distributed model training-oriented routing reconstruction method in a hybrid photoelectric network, and belongs to the field of network communication optimization. The method comprises the following steps: constructing a collaborative routing model based on a current network flow state and topological information, and introducing an adaptive weight mechanism to dynamically adjust the priority of optical channels and electric packet forwarding, thereby realizing efficient collaborative utilization of multi-layer forwarding resources. According to the method, path reconstruction can be rapidly completed according to task characteristics and a network dynamic state, so that the system resource utilization rate is improved, and the maximum task completion time delay is reduced. Compared with a traditional fixed routing and semi-dynamic routing method, the method has the advantages that the average completion time delay and the maximum time delay are improved by more than 45% in the large-flow environment generated by large-scale model training, and the method has good expandability and real-time performance and is particularly suitable for burst flow intensive intelligent computing cluster scenes.

The invention provides a method, a device and a system for switching master and standby control centers of a smart home. In the scheme, real-time operation state data of each control center in the smart home and the number of times of downtime in a first preset time period are acquired, and based on the real-time operation state data and the number of times of downtime, a long-term short-term memory network model is used to score each control center to obtain a final score of each control center; sorting all the final scores from large to small, and determining the control centers corresponding to the final scores ranked in the front preset number as candidate control centers; an improved PBFT protocol is adopted to carry out consensus election on the candidate control hub, a target control hub is elected, the main control hub is switched to the target control hub for operation, and the target control hub meets at least one of the following preset conditions: the highest network communication efficiency, the shortest network delay and the lowest power consumption. The problem that the switching efficiency of the main and standby control centers in the smart home system is low is solved.

The invention discloses an offshore platform anti-collision device and method based on multi-mode BEV perception, and the device comprises a three-dimensional fusion distance measurement module, a UWB distance measurement module, a ship navigation state monitoring module, a platform marine environment monitoring module, and a central processing unit. The three-dimensional fusion ranging module comprises a holder, a laser radar and a camera, and is used for performing 360-degree three-dimensional scanning on the periphery of the offshore platform; the UWB distance measuring modules are installed on the periphery of a ship and pile legs of an offshore platform. The ship navigation state monitoring module is used for acquiring ship position, navigational speed and course information in real time; the platform marine environment monitoring module collects wind wave data and weather data near the offshore platform and route information of passing ships through network communication. The invention discloses an offshore platform anti-collision device with real-time monitoring and collision risk assessment functions, the anti-collision safety of an offshore platform is improved, and the occurrence rate of collision accidents is reduced.

The invention belongs to the technical field of industrial equipment inspection, and particularly discloses and provides an industrial equipment-oriented multi-terminal dynamic task collaborative inspection system, which comprises the steps of collecting equipment real-time operation state data and inspection terminal space position information, generating a dynamic priority queue, and flexibly adjusting the priority of an inspection task; direct communication connection is established between inspection terminals, relay nodes are established by detecting adjacent terminals, and autonomous reconstruction of inspection network communication is realized; a to-be-detected device is split into physical detection units which can be operated independently, and a task fragment combination containing a time window and a space range is allocated, so that multi-terminal cooperative work is realized; the running state data and the historical normal value range are compared in real time, the adjacent inspection terminals are automatically triggered to cooperate with a reinspection instruction, and it is ensured that data are accurate and reliable; and updating the three-dimensional state atlas of the equipment according to the detection result and the load state of the communication network, and synchronizing to all the inspection terminals in the connection state to ensure the consistency of the state views of the equipment.

The invention relates to the technical field of new energy intelligent decentralized control, and discloses a distributed photovoltaic power station intelligent monitoring method and system, and the method comprises the steps: collecting electrical state parameters, and carrying out the normalization processing; performing anomaly detection and island detection based on a multi-dimensional deviation fusion mechanism; generating a power support parameter through a self-adaptive reactive power injection mechanism; under the island mode, loading voltage frequency double-droop combined control; and after the main network is recovered, grid-connected reconnection is realized based on a phase progressive phase locking mechanism. Compared with the prior art that multi-dependence centralized master station judgment and scheduling cannot realize fault isolation and independent operation in time especially under the condition that main network communication is abnormal or frequency fluctuation occurs in a far-end island edge node, the technical problem that fault isolation and independent operation cannot be realized in time in the prior art is solved. Autonomous monitoring of an individual power station level and stable operation of an island are realized, and the stability of the system in a weak network or island operation scene is improved.

The invention belongs to the technical field of intelligent hardware control methods, and discloses a low-power-consumption intelligent hardware control method which comprises the following steps: acquiring working state parameters and user interaction information of intelligent hardware, and generating an equipment state feature vector; judging whether a dormancy condition is met or not according to the equipment state feature vector; when the sleep condition is satisfied, sending a network communication agent instruction; the coprocessor configures an internal timer and awakens signal output after receiving the instruction; the master control stores a system operation state, configures a wake-up source and then enters a deep sleep state; the coprocessor cuts off the power supply of the inactive module; when a timer of the coprocessor reaches a preset network heartbeat cycle, a wake-up signal is sent to the master controller; and the master control recovers the system state, updates the feature vector and re-decides whether to sleep or not. And through multi-dimensional state perception and a master-slave cooperation architecture, and through refined power management and a dynamic reevaluation mechanism, the equipment power consumption is obviously reduced on the premise of ensuring the user experience.

The invention discloses a network communication dynamic optimization method based on multi-module collaboration, and relates to the technical field of network communication, a dual-mode communication module is deployed at each network node, and the network communication dynamic optimization method comprises the following steps: each network node broadcasts own existence information and power line channel characteristics through an HPLC (High Performance Liquid Chromatography) channel of the dual-mode communication module; each network node scans surrounding wireless networks through an HRF channel of the dual-mode communication module and reports own wireless channel quality information to the gateway; the global state sensing module collects all information and constructs a global network view containing physical topology and a channel quality map. A dual-mode cooperation mechanism, a machine learning prediction model and a dynamic decision strategy can adapt to complex dynamic environments such as power line noise fluctuation and wireless interference change, and communication parameters can be autonomously optimized without manual intervention; and meanwhile, the modular design is convenient to expand to a multi-mode communication scene, and has a wide application prospect.

The invention relates to the technical field of Internet of Things equipment, in particular to an Internet of Things equipment management method, computing platform and system, and the method comprises the steps: obtaining the state data of the Internet of Things equipment, carrying out the health scoring of the equipment periodically through a neural network model, and detecting the potential fault risk; constructing a task allocation strategy based on the equipment health score, and dynamically transferring a task to health equipment when the equipment has a potential fault risk; detecting the communication state of the potential fault risk equipment; potential fault risk equipment in a normal communication state is degraded into temporary communication equipment, and the health equipment is assisted to complete communication; and optimizing network topology and communication load by using temporary communication equipment based on a dynamic topology optimization algorithm driven by a graph model. According to the method, the reliability, the task completion rate and the network communication performance of the Internet of Things equipment can be effectively improved.

The invention relates to the technical field of distributed storage verification, and discloses a storage information verification system based on a consensus mechanism. The system comprises a consensus network communication module, a storage feature analysis module, a verification decision core module, a time sequence prediction module, a decision compensation module and a verification execution engine module. The consensus network communication module is connected with a distributed storage node and receives a storage verification request; the storage feature analysis module extracts multi-dimensional feature vectors of the target data to form a feature descriptor set; the verification decision core module is combined with an embedded consensus verification space and dynamic confidence coefficient constraint condition operation to output an initial verification decision scheme; the time sequence prediction module divides a time window and generates a prediction feature descriptor set; the decision compensation module carries out deviation compensation according to the result to obtain an optimization scheme; and the verification execution engine module sends an instruction to trigger the distributed nodes to execute verification operation. A dynamic verification system constructed by the system adapts to dynamic characteristics and heterogeneous environments of distributed storage.

The invention discloses a power equipment fault diagnosis system and method based on edge cloud cooperation. The system comprises an edge end module and a cloud end module. The edge end module is deployed in a power equipment site, is embedded with a lightweight diagnosis model, collects power equipment operation state parameters in real time, executes localized preliminary fault identification and alarm judgment, extracts key characteristic quantities, and uploads a processing result to the cloud end module through a network communication protocol; the cloud module is deployed in a data center or a control platform, and performs complex model reasoning, cross-device historical data comparison, fault depth research and judgment and model updating and distribution according to the characteristic quantity data uploaded by the edge module; the edge end module and the cloud end module perform data interaction through an FTP, MQTT or 5G protocol, a model trained by the cloud end can be automatically distributed to an edge end to realize rapid deployment and switching, and equipment fault diagnosis is realized. According to the invention, through a task division cooperation and data interaction mechanism, an efficient and low-delay fault diagnosis process is realized.

Various approaches for Multi-access Edge Computing (MEC) Dual Edge App Registration, including registration performed on behalf of edge computing platforms operating as dual deployments in a MEC and 3GPP infrastructure, are discussed. An example first computing platform may be communicatively coupled, via a network, to a second computing platform, and perform operations that: receive a dual application registration request from an application of the first computing platform; map a first application profile of the application at the first computing platform to a second application profile at the second computing platform; redirect the dual application registration request to the second computing platform; receive, in response to the redirect of the dual application registration request, an application registration acknowledgment; and provide, to the application, the application registration acknowledgment.

The invention discloses a video stream concurrent access front-end dynamic scheduling control system and method based on a digital twinborn scene, and relates to the technical field of computer software and network communication, the system comprises three core modules: a self-adaptive request queue module manages UE rendering resources based on a session token pool, distributes tokens through preemptive scheduling, and sends the tokens to a server; in combination with a GPU frame rate feedback dynamic adjustment strategy, queuing through a Promise asynchronous queue when the request fails; the front-end fusing and backoff retry module monitors the connection failure rate, when the connection failure rate reaches a threshold value, fusing is triggered, retry is delayed by adopting an exponential backoff strategy, and a semi-open state tends to recover; and the local cache collaboration module intercepts the request through Service Worker, caches the latest video clip, pushes the local content when the request is delayed, and ensures the freshness through ETag verification. The method and the device are used for efficiently managing loading and interaction of multiple users on real-time rendering pictures at a browser end.

The invention discloses a malicious encrypted traffic decryption method and system based on memory data analysis, and the method comprises the steps: reading process activity data of a target computer; determining a target malicious process, and obtaining a target malicious process identifier; reading the memory space of the target malicious process to obtain memory data; capturing a network communication data packet of the target malicious process; determining candidate memory data; sequentially moving and extracting byte sequences; calculating an information entropy value and a hash value of each byte sequence; selecting byte sequences of which the information entropy values are greater than a preset threshold value and the hash values are not repeated in all byte sequences, and generating a key candidate set; and performing decryption operation on the network communication data packet by using each byte sequence in the key candidate set as a decryption key to obtain an effective decryption key and decrypted data content. According to the invention, decryption and analysis of malicious encrypted traffic are realized.

The invention belongs to the technical field of network communication, and particularly relates to an operation and maintenance network fault solving system and method.The operation and maintenance network fault solving method comprises the steps that a data collection module collects multi-source original network data of target network equipment and preprocesses the multi-source original network data to obtain multi-source standard network data; a semantic reconstruction module identifies non-business purpose fields in the multi-source standard network data and performs semantic reconstruction processing on the non-business purpose fields to obtain a target state set; the fault diagnosis module carries out fault analysis on the target state set and determines a fault type and a root position; and the execution module generates and executes a predictive isolation strategy according to the fault type and the root position, records a fault processing process and updates a dynamic coding rule and a diagnosis weight distribution strategy. According to the invention, the problems of low efficiency and insufficient accuracy caused by dependence on artificial experience and rule analysis in a network fault diagnosis method can be solved.

Apparatus and methods are provided for sidelink relay-based UE-to-network communication. The disclosure describes the relay UE performing delayed relay forwarding upon determining the remote UE is in the DRX cycle based on the PC5 configuration. The relay UE buffers the relay traffic and / or sends a suspending indication to the base station to request the base station to suspend the relay traffic to the remote UE. The disclosure describes the relay UE monitoring paging occasions configured for itself and receives paging message from the network intended for the remote UE in one non-connected RRC state. The relay UE sends a PC5 paging message to the remote UE that is in the non-connected RRC state through the established SL based on the received paging message. The disclosure describes the network storing the SL association between the relay UE and the remote UE to the network.

The invention discloses a building heating, ventilating and air conditioning control method with dynamic energy efficiency optimization, and belongs to the technical field of heating, ventilating and air conditioning control. The method comprises the following steps: step 1, acquiring temperature, humidity, carbon dioxide concentration and personnel distribution data in real time, and performing preliminary data processing through an edge computing node; step 2, realizing accurate prediction of future load change of the building; step 3, generating an optimal control strategy by using a reinforcement learning algorithm, and realizing dynamic optimization control of equipment operation; 4, the compliance of equipment operation, network communication and control instructions is monitored in real time, and a closed-loop dynamic tuning mechanism is constructed to continuously optimize control strategy parameters; step 5, dividing a control task into a group control layer, a region layer and a terminal layer, and establishing communication among the layers through a standardized interface so as to realize accurate transmission and execution of an instruction; and step 6, designing a friendly human-computer interaction interface, displaying a building operation state, energy consumption analysis and a control strategy, and supporting multi-terminal access and remote monitoring.

The invention relates to the technical field of satellite network communication, and discloses a multi-source multi-path scheduling method for remote sensing data transmission, which comprises the following steps of: firstly, establishing an index table for remote sensing data by using a space-time name formed by a service type, an acquisition area, acquisition time, a node identifier and a data category; and the controller analyzes time and space constraints in the request, selects a plurality of source nodes meeting conditions from an index table, calculates priorities according to parameters such as residual bandwidth, round-trip delay and packet loss rate, and selects a plurality of non-overlapping high-quality paths. And then adding a service type, a path number, a path state report and a flow proportion field in the interest packet and the data packet, so that the source node sends segmented data in parallel according to a preset proportion. And the forwarding node reports the link change in real time, and the controller dynamically adjusts the path set and the shunt weight, thereby ensuring that the high-bandwidth and low-delay data transmission performance is continuously obtained in a topology and load rapid change scene.

The invention provides an optical network communication method and a communication device, the method is applied to an optical fiber network, the optical fiber network comprises a master device and at least one slave device, and the at least one slave device comprises a first slave device. Wherein in the initialization phase, after receiving the authentication encryption capability of the slave device, the master device can indicate a determined authentication encryption mode (e.g., a first authentication encryption mode) to the slave device, so that the authentication encryption capability of the slave device is enhanced in a subsequent process (e.g., a roaming parameter configuration process). The master device does not need to configure security-related parameters such as an authentication encryption mode for the slave device, so that the configuration efficiency is improved, and the configuration overhead is saved.