149 results about "Network partition" patented technology

The invention discloses a low earth orbit satellite Internet of Things communication method and system based on a dynamic block chain, and the method specifically comprises the steps: taking at least one ground station as a consensus node in each network partition, forming a consensus network, and selecting a main node from a plurality of consensus nodes of each consensus network through employing an RBFT algorithm; a satellite transit algorithm is adopted to predict transit information of each low-orbit satellite, and the low-orbit satellites passing through any consensus network are set as accounting nodes of the consensus network according to the transit information; the method comprises the following steps: acquiring a service request of a satellite communication terminal, forwarding the service request to a main node of a consensus network to which the service request belongs through a low-orbit satellite of a transit satellite communication terminal, performing verification and priority ranking on the service request according to the main node, and if the verification is passed, performing broadcast and consensus verification on all nodes of the current consensus network. According to the invention, the communication efficiency and safety of the low-orbit satellite Internet of Things are improved, and reliable technical support is provided for satellite Internet application.

The invention discloses an optimized registration method and system based on a micro-service architecture. The invention relates to the technical field of Nacos systems. The health monitoring center is started and starts to send a health examination request to a downstream service at regular time; the gateway access layer service receives a client request; obtaining a network address of a target service instance through a Nacos service discovery mechanism according to a service name in the request; then forwarding the request to a target service instance for processing; when the configuration information is changed, the Nacos configuration management center pushes an update notification to all subscribed service instances; the service instance pulls the latest configuration information and updates the local cache; according to the method, a secondary hand waving mechanism is implemented in Nacos cluster node, gateway service and downstream service communication, so that the offline condition of the downstream service can be accurately judged, and the problem of data inconsistency caused by node faults or network partition is avoided.

The invention relates to the technical field of water supply pipe network partitioning, in particular to an urban water supply pipe network DMA modeling method based on multi-dimensional data fusion, and the method comprises the steps: analyzing the consistency of node hydraulic data of adjacent pipe network nodes and the actual hydraulic working condition stability of a pipeline, obtaining the hydraulic feature similarity of the pipe network nodes, and constructing a pipe network weighted undirected graph; based on the topological flexibility of the important nodes in the annular pipe network, amplifying the difference of the importance scores of the important nodes on the local water supply pipe network area, constructing a screening index, and screening an initial partition center to obtain the number of partitions; based on the pipe network weighted undirected graph, the initial partition center and the partition number, DMA partition and modeling simulation are carried out in combination with a spectral clustering algorithm and pipe network hydraulic simulation software, the problem that the number of DMA partition nodes is unbalanced due to the fact that a plurality of initial partition centers exist in a local water supply pipe network area is solved, and the stability of DMA partition carried out through the spectral clustering algorithm is improved.

The invention provides an accounting method based on a distributed account book, and the method comprises the steps: enabling a system to obtain a complete log block after a bifurcation point from other nodes according to the position of the bifurcation point, transmitting the complete log block to a bifurcated node, and enabling a log of the bifurcated node to be consistent with other nodes through a log copying mechanism of a Raft consensus algorithm; in the bifurcation recovery process, the system continuously monitors network connection and health conditions of all nodes, if any new exception is detected in the recovery process, the process is temporarily stopped, and when the exception is solved, bifurcation recovery is restarted; and after the bifurcation is recovered, the secondary node receives the log entry again or receives the log entry again, so that the financial bookkeeping record in the cloud environment is recovered, and the account book state of the node generating the network partition problem is synchronized with that of other nodes.

The invention relates to the technical field of distributed data storage, and discloses a database cluster partition operation method and device under a network partition scene and a medium, and the method comprises the steps that a multi-master distributed database cluster is constructed, and each node continuously captures a database native transaction log; obtaining change event data, and performing unified data storage; analyzing the original log into structured data, and executing uniform fragmentation and parallelization processing; processing the block log change record, and arranging change events of the primary key according to a rule; executing conflict processing and data synchronization, and synchronizing all nodes after the conflict is solved; through exception handling and fault tolerance, self-healing is realized and data consistency is maintained. According to the method, millisecond conflict identification and data consistency convergence after network disconnection can be realized, continuous and stable operation of a cluster in a partition state is ensured, and self-healing and continuous availability of a system are realized.

A decentralized mesh-network platform provides real-time governance, supervision, and audit of large-language-model persona agents in regulated environments such as healthcare. Each computing node hosts processor circuitry, memory, a network interface, and an integrated suite comprising a User-Prompt Interface, Metadata Filter & Enrichment Engine, Persona Role Constructor, Policy Constraint Engine, gating logic module, Supervisor Review Interface, Session Memory Governance Module, Audit Logging Subsystem, cryptographically linked audit ledger, and Fallback Control Module. Devices communicate over a peer-to-peer channel, exchange role-switch tokens, and merge local ledgers into a composite audit graph when connectivity returns. The architecture supports continuous compliance and resilient operation across institutional boundaries, network partitions, and device failures, enabling conversational interaction with heterogeneous medical data while maintaining rigorous credential lineage, policy oversight, and forensic traceability.

The invention relates to a dynamic routing and flow balancing method and system for a regionalized network topology, and the method comprises the steps: dividing a satellite network into a plurality of partitions, and distributing a core node for traffic scheduling and routing calculation for each partition; each core satellite node responds to each traffic demand, and bandwidth and traffic distribution in each partition are adjusted through a multi-anchor-segment routing method and a preset linear programming model; and each satellite node dynamically adjusts the route of each traffic demand through a probability forwarding scheduling method based on geometric topology according to the relative position of the satellite node and the target node. According to the method, low delay, high bandwidth utilization rate, load balance and efficient fault recovery of the satellite network are realized through network partitioning, a multi-anchor-segment routing method and probability forwarding based on geometric topology.

The invention relates to a heterogeneous AI computing virtualization architecture and slice enhancement method and system, and the method comprises the steps: evaluating the demands of an AI task for GPU resources through an analytic hierarchy process, and dividing the GPU resources into ultrafine-grained slice units according to an optimization model; predicting a resource demand through an ARIMA model, allocating slice resources through a minimum error sum of squares algorithm, and generating a resource allocation scheme; the method comprises the following steps: dividing a GPU into a plurality of independent hardware isolation units based on a resource allocation scheme and GPU hardware topology, and generating a hardware unit configuration table; establishing an isolation mechanism based on the identity information and the ACL, and establishing a software isolation environment; the method comprises the following steps: dividing network partitions, configuring a firewall rule to control network access authority, monitoring network traffic in real time, processing abnormal traffic, and generating a network partition mapping table; gPU resources are abstracted into a logic resource pool, a resource scheduling platform based on an intelligent scheduling algorithm is constructed, and resource scheduling of heterogeneous slices is carried out.

The invention discloses an Internet of Things equipment linkage control method and system based on cloud computing and a storage medium, and relates to the technical field of intelligent control. The method comprises the following steps: constructing a home coverage network; executing network partition aggregation, establishing a network partition aggregation result, and configuring a distributed computing center; synchronizing monitoring data of the sensor group to a distributed computing center; calling and positioning the home equipment by using the distributed computing center, reading the equipment state of the corresponding home equipment, performing linkage control optimization of the equipment in the region, and establishing a first linkage control result; if the probability evaluation result of the partition linkage meets a preset threshold value, synchronizing the first linkage control result and the monitoring data to a centralized computing center; and performing linkage control on the home equipment by using the second linkage control result. The technical problems of slow response and low efficiency of linkage control of the Internet of Things equipment in the prior art are solved, and the technical effect of improving the real-time performance and efficiency of linkage control of the Internet of Things equipment is achieved.

The invention relates to the technical field of thermoelectric pipe network inspection, and discloses a thermoelectric pipe network fault inspection system and method based on deep learning. The system comprises a pipe network partition module, a multi-mode sensing module, a fault prediction module, a grading response module and a dynamic control module. The pipe network partition module is divided into a high-temperature steam pipeline area, a medium-temperature hot water pipeline area, a low-temperature water return pipeline area and a key valve connecting area; the multi-modal sensing module deploys temperature, pressure and sonic sensor arrays in each area; the fault prediction module extracts spatial-temporal characteristics through a deep belief network model and outputs a fault probability value; the hierarchical response module triggers different levels of response instructions according to a comparison result of the fault probability value and a preset threshold interval; and the dynamic control module controls a moving path of the inspection robot and detection equipment parameters according to the response instruction. According to the system, accurate prediction and dynamic response of the thermoelectric pipe network fault can be realized, and the inspection efficiency and the pipe network operation reliability are improved.

Disclosed herein are systems and method for testing distributed systems using injected network partitions. A method may include monitoring communication between a plurality of computing devices in a distributed system to identify each communication link that exists between two respective computing devices in the distributed system. The method may include generating a communications list comprising a plurality of computing device pairs and injecting a network partition in at least one pair of the plurality of computing device pairs. The method may include detecting whether a performance degradation greater than a threshold performance occurs in response to the network partition. In response to detecting the performance degradation greater than the threshold performance, the method may include generating and transmitting a security report indicative of the performance degradation and the at least one pair of the plurality of computing device pairs causing the performance degradation.

The invention discloses a partition network architecture, a routing method, equipment, a medium and a program product, and relates to the technical field of routing, a target network is divided into a plurality of network partitions, first nodes of the network partitions are connected through configured second ports, and therefore interconnection between the network partitions is achieved; when a multicast message needs to be transmitted, transmission between nodes in the same network partition can be realized through the first port and the second port; and meanwhile, the cross-region transmission of the multicast message is realized by using the second port. Each network partition can independently transmit messages in parallel in the partition, cache competition is reduced, the synchronization of multicast routing is optimized, a special multicast message transmission channel between the network partitions is realized by independently arranging a second port for a first node, delay caused by long-distance transmission of the messages is reduced, and the service life of the network partitions is prolonged. The message transmission delay and the blocking risk of the target network are significantly reduced, and the energy efficiency and throughput of the target network are improved.

In one implementation, we propose an unsupervised point cloud primitive learning method based on the principle of analysis by composition. In one example, the method uses a partitioning network and a point cloud autoencoder. The partitioning network partitions the input point cloud into a list of chunks. For each chunk, the encoder network of the autoencoder performs analysis to output a codeword in the feature space, and the decoder network performs synthesis to reconstruct the point cloud chunk. The reconstructed chunks are merged to output a fully reconstructed point cloud frame. The autoencoder discovers primitive shapes in the point cloud data by end-to-end training to minimize the misalignment between the original and reconstructed point clouds. During network training, the parameters of the partitioning network and the autoencoder are updated. The trained modules can be applied to different applications, including segmentation, detection, and compression.

The invention relates to the technical field of intelligent transportation, and discloses a mine intelligent transportation method and system. The method comprises the following steps: performing time sequence filtering and gradient denoising on mine transportation node temperature data acquired by a thermal imaging camera to obtain a temperature characteristic matrix; identifying transportation abnormal information based on the temperature characteristic matrix; executing temperature mode matching according to the transportation abnormal information, and generating a transportation operation instruction set; performing mine channel temperature safety path planning by taking the transportation operation instruction set as a constraint condition to obtain a transportation execution scheme; after the specific position of a mine worker is positioned in real time through a thermal imaging camera, a transportation execution scheme is converted into a standardized voice instruction, the standardized voice instruction is pushed to the corresponding worker through an interphone network partition, and scheduling feedback data containing instruction receiving confirmation and execution progress are obtained in real time. According to the invention, operators are accurately positioned through thermal imaging, and partition pushing is realized in combination with an interphone network, so that the intelligent level and safety of mine transportation are improved.

The invention discloses a GIS (Geographic Information System)-based DMA (Direct Memory Access) intelligent partitioning method for a water supply network, relates to the field of data processing, and can solve the problem that a virtual partition boundary is misjudged or a boundary at a certain position frequently fluctuates due to the fact that a DMA intelligent partitioning method for the water supply network at the present stage cannot accurately distinguish sudden water taking abnormity and leakage abnormity. The method comprises the following steps: acquiring water flow state monitoring data; determining a water flow abnormal data set according to the water flow state monitoring data; according to the water flow abnormal data set, a water supply pipe network partition preliminary result is determined; wherein the water supply pipe network zoning preliminary result is used for representing a preliminary division range of each area in the water supply pipe network; and determining the DMA partition of the water supply network according to the preliminary partition result of the water supply network and the physical equipment information of the water supply network. The method is used for DMA intelligent partitioning and leakage monitoring of the water supply network.

The invention relates to the technical field of data visualization, in particular to a visual output method and system for an artificial intelligence model, and the method comprises the following steps: analyzing the information of nodes and edges in a network through model structure network data, recognizing the connection number of a plurality of nodes, calculating the weight, partitioning the network according to the connection strength of the nodes, and storing the partitioned network in a database; and generating a model structure mapping graph. According to the method, the network data of the model structure is analyzed, the connection number and the weight of the nodes are calculated, the relevance between the data and the core structure of the network are revealed, the statistical attributes of the nodes are classified, the chart types are matched according to the data characteristics, the visual presentation effect of the data is optimized, and the user interaction behavior is monitored in real time. And the chart layout is adjusted according to the visual focus of the user and the reaction data, so that the cognitive load of information processing is reduced, a decision maker can quickly identify modes, trends and abnormities in the data, and the ability of understanding the output data of the artificial intelligence model is improved.

Disclosed in the present invention are a power transmission network emergency repair and restoration method and device based on a mobile power supply. The present application improves the power transmission network fault restoration efficiency by the method: reading a preset power transmission network black start strategy optimization model and parameter data acquired from a power transmission network to be restored, wherein the power transmission network black start strategy optimization model is constructed by setting an emergency repair resource constraint, a power transmission network operation constraint and a power transmission network partition constraint, with the optimization objective of minimizing power transmission network load loss; initializing the power transmission network black start strategy optimization model on the basis of the parameter data, and solving the power transmission network black start strategy optimization model by means of a solver to obtain a mobile power supply arrangement scheme and a unit restoration scheme of said power transmission network; and performing emergency repair on said power transmission network on the basis of the mobile power supply arrangement scheme and the unit restoration scheme. The present application can improve the power transmission network fault restoration efficiency and reduce power outage costs by allocating fault repair resources.

The invention discloses an underground pipe network partition metering and intelligent regulation and control system which comprises a data collecting and preprocessing module used for collecting and preprocessing multi-source time sequence data; the graph structure construction module is used for constructing a graph structure data set and forming a node set, an edge relation and a feature matrix; the graph neural network modeling module is used for constructing a graph neural network model containing a residual connection structure; the parameter optimization module is used for optimizing structure parameters of the graph neural network; the state prediction and instruction generation module is used for predicting the state of each node and generating a regulation and control instruction; the instruction execution module is used for issuing the regulation and control instruction and carrying out dynamic regulation and control; and the feedback updating module is used for collecting state feedback data, evaluating prediction deviation and updating the graph structure data set and the graph neural network model parameters. According to the method, the graph neural network and the dragonfly optimization algorithm are utilized, accurate prediction of the node state of the underground pipe network and intelligent partition regulation and control are achieved, and the operation efficiency and safety of the system are improved.

The invention relates to an automatic cluster recombination method, a distributed system and computer equipment. Determining a plurality of independent network partitions after the distributed system is subjected to network partitioning; for each independent network partition, determining first existence information of each cluster node in each independent network partition; determining a target local leader node and a target follower node from the cluster nodes of the independent network partitions according to a preset consensus recombination strategy based on the first existence information; establishing a first local consensus cluster corresponding to the independent network partition according to a following relationship between the target local leader node and the target follower node; according to the invention, automatic reorganization of cluster nodes during network partitioning is realized, so that each independent network partition can still maintain local consensus and service availability under the condition that global intercommunication cannot be realized, service is provided to the greatest extent, the availability is ensured, and the service continuity and the overall availability of the system after network partitioning are remarkably improved.

Systems and methods generate requests for encrypted (e.g., secured) credentials and data using one of a plurality of API plugins that are selected based on an access protocol for a network partition at which requested data is determined to be stored. Through the use of the dynamically-selected API plugins, the systems and methods may provide the aforementioned functions while being compatible with the different access protocols that may be encountered when providing central management across a diverse spectrum of user accounts, networks, and / or cloud platforms.

Systems and methods generate requests for encrypted (e.g., secured) credentials and data using one of a plurality of API plugins that are selected based on an access protocol for a network partition at which requested data is determined to be stored. Through the use of the dynamically-selected API plugins, the systems and methods may provide the aforementioned functions while being compatible with the different access protocols that may be encountered when providing central management across a diverse spectrum of user accounts, networks, and / or cloud platforms.

The invention discloses a complex electromagnetic looped network partition optimization planning method based on a Louvain algorithm, and the method comprises the steps: simplifying a receiving-end power grid model into a weighted undirected topological graph, dividing the nodes of the weighted undirected topological graph into a plurality of communities based on the Louvain algorithm, and allocating each node to the community where the adjacent node is located until the modularity of each community is the maximum value. And when the community formed after all the nodes finish moving and the three-phase short-circuit current of each partition meet judgment conditions, outputting partition schemes, performing index evaluation on all the partition schemes, and selecting an optimal partition scheme. According to the method provided by the invention, the operation efficiency and stability of the power grid are improved, and the complexity in planning and operation of the power grid is reduced.

Techniques are disclosed for community-based federated training by leader node representation. An example system includes a memory having instructions, and a processor communicatively coupled to the memory and configured to execute the instructions. The instructions can include: using a community detection (CD) algorithm to partition a network of nodes into a plurality of communities; using graph-based measurements of the network to elect a leader node for each community; and performing federated learning within and between the communities through the elected leader nodes.

The application relates to the technical field of distributed data storage, and discloses a database cluster partition running method in a network partition scenario, equipment and a medium, wherein the method comprises the following steps: constructing a multi-master distributed database cluster, continuously capturing database native transaction logs by each node; obtaining change event data and uniformly storing the data; analyzing the original logs into structured data, performing uniform sharding and parallel processing; processing block log change records, arranging the change events of primary keys according to rules; performing conflict processing and data synchronization, synchronizing all nodes after solving the conflicts; and through abnormal processing and fault tolerance, realizing self-healing and maintaining data consistency. The application can realize millisecond-level conflict identification and data consistency convergence after network disconnection, guarantees the continuous and stable operation of the cluster in a partition state, realizes self-healing and continuous availability of the system.

The invention relates to the technical field of electric power engineering information communication, and discloses a safety protection system of an electric power engineering information communication network, which comprises a network partition module, a regional data acquisition module, a regional data analysis module and a regional alarm module, the network partition module divides a network into a plurality of areas according to a production control area of the electric power engineering, and the area data acquisition module is used for respectively acquiring flow use data, data packet load data, network connection frequency and equipment and memory use data of each area in the plurality of areas; the regional data analysis module calculates a flow use anomaly index, a data packet invalid load index, a connection anomaly frequency and an equipment and memory use anomaly index according to the collected data, then comprehensively calculates a network safety coefficient, and judges whether the network environment is abnormal from multiple aspects; and when the network environment is judged to be in an abnormal state, an abnormal signal is sent to the regional alarm module for alarming, so that the network security is effectively improved.

The invention relates to the field of intelligent equipment control, and provides a smart home cooperative control method based on the Internet of Things. The method comprises the following steps: analyzing historical state data of a smart home environment through machine learning to obtain an equipment association map, and encoding collected real-time state data to obtain a global state vector; clustering by combining the global state vector and the equipment association map to obtain a life scene mode set, extracting a trigger condition to form a library, and inputting the global state vector into a neural network to predict scene occurrence probability distribution; determining standard equipment state configuration corresponding to a target scene in the trigger condition formation library according to scene occurrence probability distribution, and performing multi-target optimization on standard equipment state control to obtain a cooperative control strategy list; and executing instructions in groups on the cooperative control strategy list according to the equipment network partitions, and performing monitoring compensation in the execution process. According to the invention, the scene intelligent control accuracy of the intelligent equipment is improved.

The present invention addresses the problem of premature node death caused by uneven energy consumption among nodes in a wireless sensor network. From the perspective of grid partitioning, the present invention considers the clustering and cluster head election of wireless sensor nodes, and proposes a method for clustering and cluster head election of wireless sensor nodes based on grid partitioning with energy load balancing. The sensor nodes are divided into different grid regions for clustering, and a dynamic cluster head election mechanism is adopted to reduce the collection of duplicate data. Moreover, the cluster head nodes are evenly distributed through the uniform distribution of the grids, thereby solving the problems of unreasonable clustering and uneven energy consumption of network nodes.

This invention provides a distributed transaction processing method for BOM data in a PLM system, belonging to the technical field of PLM systems. When initiating a BOM data modification transaction, this invention sends a preparation request to participating nodes and performs field-level lock acquisition. A majority vote determines whether the transaction should be committed or rolled back. Transaction logs are batch-aggregated into group commit log blocks according to time windows and copied to persistent memory via RDMA. A closure table is established for the BOM tree structure to store ancestor-descendant relationships. An artificial intelligence model is used to monitor node response latency and log write rate to dynamically adjust parameters. When a network partition is detected, nodes holding a majority lease continue processing the transaction. After partition recovery, data merging is performed using version vector conflict detection and a compensation transaction mode. This solves the problem of data consistency being difficult to guarantee due to network partitions when processing BOM data modification transactions in a distributed PLM system.

This invention provides a method and system for optimizing downhole communication links based on self-organizing networks, relating to the field of communication link technology. The method includes acquiring communication node information, constructing a network topology, and determining network characteristic parameters; constructing a link quality prediction model to evaluate link quality; performing dynamic network partitioning and establishing a node priority ranking table to select the optimal transmission path; and real-time monitoring of link status, triggering node self-organizing reconfiguration when necessary. This invention can improve the connectivity, stability, and transmission efficiency of downhole communication networks, reduce communication latency, and enhance the safety of downhole operations.

This invention discloses an IoT-based underground pipe network zonal metering monitoring and control system, comprising the following modules: a zonal monitoring module for collecting zonal flow, pressure, water quality, and valve status data, and for collecting upstream flow and pressure data; a data preprocessing module for preprocessing the zonal monitoring data; a time-series feature modeling module for outputting zonal prediction data using an improved TimesNet model; an anomaly detection module for generating zonal anomaly detection results; a control distribution generation module for outputting zonal control distribution based on an improved generative flow network reinforcement learning model; a control parameter generation module for obtaining zonal control parameters and updating model parameters; and a control execution module for adjusting valve opening, water supply distribution ratio, and pressure setpoint. This invention integrates time-series feature modeling and generative flow network reinforcement learning to achieve refined monitoring and intelligent control of underground pipe network zonal areas.