563 results about "Single node" patented technology

The invention discloses an adjustable load security access method for a virtual power plant, and relates to the technical field of power system automation, and the method comprises the following steps: in the operation process of a virtual power plant scheduling system, after an upper-layer scheduling center issues a unified adjustment instruction according to an operation demand, all access nodes are monitored in real time, and the adjustment instruction is sent to the upper-layer scheduling center; the method comprises the following steps: receiving a scheduling instruction from an access node, collecting response behavior data of the access node to the scheduling instruction, preprocessing the collected original response data of a single node, and carrying out unified coding and formatted storage on historical and current response behaviors according to node identification and scheduling time sequence information to construct a structured data set. According to the method, accurate identification and dynamic correction of the adjustable load frequency response offset risk in the virtual power plant are realized, the heterogeneous load perception and control capability is improved, frequency staggering resonance and scheduling failure caused by inconsistent response are avoided, the system cooperative adjustment stability and the load safety access reliability are enhanced, and the method has a good application prospect.

The invention relates to the technical field of virtual power plant operation monitoring, and discloses a virtual power plant distributed resource cluster anomaly monitoring system, method and equipment, and the system comprises a resource node data collection module, an anomaly trend score calculation module, an association graph model construction module, a single node influence calculation module and a comprehensive anomaly early warning output module. In the prior art, a single-point alarm mode depends on a fixed threshold value or a rule base, and especially under the conditions that distributed resources in a virtual power plant are complex in type and space coupling and controller sharing exist between nodes, accurate identification and dynamic early warning of trend anomalies, cooperative faults and potential propagation paths are difficult to realize. According to the method and the device, the multi-dimensional parameter modeling and the graph neural network anomaly propagation analysis are fused, so that the anomaly in the distributed resource cluster is identified and dynamically evaluated, and the early warning accuracy and the intelligent operation and maintenance efficiency of the virtual power plant are improved.

The invention relates to a federated learning system based on multi-key homomorphic encryption and adaptive differential privacy, and belongs to the technical field of privacy computing. According to the system, on the premise that no trusted third party exists, a multi-client collaborative key generation and threshold decryption mechanism is achieved, it is ensured that model parameters are always in an encrypted state in the aggregation process, and leakage of a single node is prevented. By introducing a parameter sensitivity analysis and selective encryption strategy, the system only encrypts high-risk parameters, and the encryption burden is effectively reduced. Meanwhile, in combination with an adaptive privacy budget allocation mechanism, the system dynamically adjusts noise intensity according to a model training state, and model performance and convergence speed are maintained while privacy protection capability is improved. According to the method, high robustness and collusion resistance are realized, stable operation under the condition that part of clients are offline is supported, and the method is suitable for application scenes such as medical treatment and finance with high data sensitivity and strict performance requirements.

The embodiment of the invention discloses a collaborative optimization method and device for a distributed micro-grid and a medium, and relates to the technical field of energy management, and the method comprises the steps: carrying out the real-time data collection through a multi-element sensor network disposed at each distributed energy node in advance, so as to obtain the real-time energy data corresponding to each distributed energy node; according to the edge node corresponding to each distributed energy node, carbon emission of the distributed energy nodes is predicted by using the real-time energy data, and node-level predicted carbon emission parameters are determined, so that single-node optimization reference information corresponding to each distributed energy node is determined; through a preset global center node, collecting single node optimization information corresponding to each distributed energy node for aggregation, and determining global model gradient information; and based on the global model gradient information and the single-node model gradient information, carrying out collaborative optimization on the single-node optimization strategy to determine a collaborative optimization strategy corresponding to each edge node.

Embodiments described herein relate to computer systems and methods for digital asset custodian that seamlessly integrates off-chain multi-party computation (MPC) signing with on-chain party identity authentication. The system comprises a service provider node, multiple computation nodes equipped with robust secure hardware, and a Blockchain accessible to all participating nodes. The nodes deliver a threshold signing service with utmost security—ensuring that no single node can recover the private key, while simultaneously recording and mutually authenticating each node's identity on-chain. The system boasts intrinsic support for hierarchical address creation and signing, facilitated by an enhanced protocol. Its scalability, particularly in the quantity of computation nodes, is complemented by efficient communication tailored to the demands of the MPC protocol.

The invention provides a digital twin hydraulic engineering large language model reasoning method based on tensor parallel processing. The method sequentially comprises the following steps: S1, gradient calculation optimization; s2, carrying out self-attention tensor dimension reduction blocking; s3, normalizing and parallelizing a low-dimensional layer; s4, inter-layer overall weak extension resource scheduling processing is carried out on the low-dimensional layer after middle-layer normalization processing in the step S3; and S5, converting an intermediate tensor result of a decoder into a specific predicted value. According to the method, the parameters and the input data of the large-scale language model are subjected to tensor segmentation and are distributed to the computing nodes for parallel processing, so that the reasoning efficiency of the large-scale model is remarkably improved. By using the method, the calculation efficiency and the real-time performance of the hydraulic engineering large language model can be greatly improved, the calculation nodes can work simultaneously by processing the reasoning task of the large-scale model in parallel, the calculation burden of a single node is remarkably reduced, larger-scale hydraulic engineering data can be processed, and the calculation efficiency and the real-time performance of the hydraulic engineering large language model are improved. And efficient and accurate risk prediction capability can be maintained.

The invention discloses a link state analysis method and device for a broadband ad hoc network, equipment and a medium. The method comprises the following steps: S1, acquiring coordinates and a signal intensity sequence of each node in a monitoring time period; s2, acquiring a link instability coefficient of the single node in the monitoring time period according to the difference of the nearest distances of the single node at different moments and the dispersion degree of the signal intensity sequence of the node; s3, according to the difference of the link instability coefficients of all the detection nodes in each emergency group, the correlation degree of the signal intensity sequences of any two detection nodes, and the dispersion degree of the coordinate distance of any two detection nodes at all moments, obtaining the regional co-variability of each emergency group; s4, the link global stability of the broadband ad hoc network system is obtained according to the mean value of all the link stability indexes; and S5, evaluating the link state according to the global stability of the link. According to the method and the device, the dynamic environment interference is integrally analyzed, so that the link state analysis accuracy is improved.

The invention relates to a heterogeneous cluster-oriented resource allocation method and device and a storage medium, and the method comprises the steps: executing a plurality of iterations of an initial model on a single node of each heterogeneous cluster, and obtaining the performance characteristics of the model; generating a plurality of parallel strategy combinations comprising the first parallelism degree and the second parallelism degree; generating a plurality of assembly line parallel combinations based on the first degree of parallelism, calculating the load imbalance rate of each assembly line parallel combination, and screening out N combinations with the minimum load imbalance rate from the assembly line parallel combinations; traversing the second parallelism degree and the micro-processing batch in each stage corresponding to each parallel combination to generate a plurality of stage strategy combinations; and calculating video memory occupation and execution time under each stage strategy combination, screening out K stage strategy combinations of which the video memories are smaller than or equal to a video memory threshold value and the execution time is shortest, and carrying out resource allocation on the heterogeneous cluster based on the stage strategy combinations. According to the invention, the problems of low training efficiency and low resource utilization rate are solved.

The invention provides a low-altitude pipeline route planning method and device, and the method comprises the steps: building a three-dimensional rectangular map of route planning based on a three-dimensional digital airspace model; taking each three-dimensional grid in the three-dimensional rectangular map as a single node, and determining a low-altitude pipeline route planning optimization scheme through an A * algorithm based on a cost function; wherein the cost function is determined according to the moving cost of the starting point grid reaching the end point grid through any path and the route cost of the starting point grid reaching the end point grid through any path; the route cost comprises distance cost and threat cost. Therefore, aircraft pipeline route planning in a low-altitude environment is realized, effective help is provided for low-altitude airspace management, and low-altitude operation safety is guaranteed.

According to the user sensitive data protection system based on the cloud service and the block chain, an SM3 algorithm is adopted to fuse biological characteristics and dynamic tokens to generate an encryption credential, high-security identity authentication is achieved, differential fragmentation encryption is carried out on data based on semantic classification, Rabin threshold fragmentation and AES + ECC double-layer encryption is adopted for data of the highest security level, and the security level of the data is improved. A dynamic node optimization model is designed; an optimization coefficient is calculated according to the capacity, the transmission rate and the fault rate; the storage efficiency is improved by more than 40% in combination with a time period regulation factor; the node temperature and the vibration frequency are monitored in real time through a sensor; and verifying the validity period of the dynamic token and the fragment permission mark by using an intelligent contract to realize GDPR compliance fine-grained access control. The system remarkably improves the anti-attack capability and storage reliability of data, and is suitable for high-sensitivity scenes such as highway toll collection, finance and medical treatment.

The invention discloses a computer self-check cycle optimization method based on the Internet of Things in the technical field of server maintenance, and relates to the technical field of server maintenance. Server node operation state data is collected in real time, a dynamic load evaluation model is constructed, and a comprehensive load index is calculated; and dynamically dividing performance states based on the threshold values L1 and L2, and adjusting a self-checking period and a module priority. Calculating a single-node risk index Ri by adopting a fault risk model, generating a fault generalization risk factor R1 through a probability graph model in combination with network topology, and triggering a linkage mechanism; dividing and dynamically adjusting a self-checking period according to the early warning level; during advanced early warning, redundant resources are distributed to preferentially process key faults, edge calculation is combined to carry out data cleaning and standardization, distributed management is realized through a consistent Hash algorithm, and finally, a visual interface is used for displaying an optimized scheduling result, so that a closed-loop optimization system of data acquisition, risk prediction and resource scheduling is formed.

The invention relates to the technical field of slope reinforcement, and discloses an anchoring device for preventing landslide geological disasters, the anchoring device is arranged on a slope surface, distributed in a grid shape and formed by splicing a plurality of anchoring units, each anchoring unit comprises an anchor rod support and four frames, the four frames are evenly distributed on the periphery of the anchor rod support, and the anchor rod support is arranged on the periphery of the anchor rod support. The anchor rod support is detachably connected with the frame; a center hole is formed in the anchor rod support, and an anchor rod inserted into a slope body is installed at the center hole. Every two adjacent frames are connected through a set of reinforcing mechanisms. The modular structural design is adopted, specifically, the detachable anchor rod supports and the frame are combined, the weight of a single node is small, carrying is convenient, manual carrying and rapid splicing are facilitated, a latticed splicing system formed by the scheme can adapt to terrains with different slopes, and the construction efficiency can be effectively improved.

The invention relates to the technical field of keyboard pairing, and discloses a keyboard multimode pairing method and device, equipment and a storage medium. The method comprises the following steps: establishing a switching time calculation model of a keyboard according to the reference switching time of keyboard hardware, a protocol node cooperation coefficient, an equipment response weight coefficient and a pre-connection optimization coefficient; calculating the theoretical optimal switching time of the current switching scene; selecting a working mode of single-node direct switching, double-node pre-connection or three-node parallel pre-connection of a keyboard Bluetooth node, a 2.4 GHz node and a USB node; activating a corresponding communication node, sending a connection handshake signal to the target equipment and establishing a communication link pre-connection state; and switching keyboard input and output from the current equipment to the target equipment to finish quick connection switching between the equipment. According to the invention, a pre-connection mechanism is adopted, the target equipment connection is established in advance before the user completes the switching instruction, passive response switching is converted into active prediction switching, and instantaneous equipment switching is realized.

The embodiment of the invention provides a data processing method and device based on a block chain network and a storage medium. The method relates to the technical field of data processing in the technical field of block chains. According to the method, a target standby node calls a system contract of a block chain network to generate first transaction information when detecting that a target master node has a fault, and under the condition that a consensus result of a first proposal block corresponding to the first transaction information indicates that the main node of the target node cluster is sponsored to be switched from the target main node to the target standby node, switching the main node in the target node cluster from the target main node to the target standby node. And the first proposal block is added to the block chain of the target standby node, so that the availability and fault-tolerant capability of the single node of the block chain can be improved, and the block confirmation delay is reduced, thereby improving the stability and performance of the whole block chain system.

A honeycomb-shaped active power distribution network topological structure selection and optimization method based on a graph theory comprises the following steps: taking line impedance and rated apparent power as constraints, constructing a multi-target weight factor, adopting an improved spectral clustering algorithm to cluster and distribute power grid nodes, and transiting a micro-grid group after cluster division into a honeycomb-shaped active power distribution network; abstracting each micro-grid as a honeycomb distribution network single node, constructing a connection relation mathematical representation of the HSPH and the micro-grid, and realizing sparse matrix method modeling of the honeycomb active power distribution network; optimizing a site selection strategy of the HSPH by taking a maximized HSPH return on investment index and a system stability index as a target function; and optimizing the energy storage capacity of the HSPH based on the net load time sequence data of the micro-grid group, and finally generating an optimal topological structure of the honeycomb-shaped active power distribution network. And through honeycomb topology and HSPH addressing and sizing optimization, the new energy consumption capability of the power distribution network is improved, and the economy, reliability and flexibility of the power distribution network are improved.

The invention relates to the technical field of automatic feeding, in particular to special automatic feeding equipment for Plasma, which comprises a fixing frame, a first plate feeding device, a second plate feeding device, a plugging and unplugging device, a transmission device and a distributed cooperative control system are arranged on the fixing frame, and the devices are electrically connected with a central controller; the first plate feeding device and the second plate feeding device are arranged side by side, the plugging and unplugging device is located on one side of the second plate feeding device, and the conveying device passes through the lower portion of the plugging and unplugging device. The distributed cooperative control system comprises a distributed control node triggered by a dynamic event, a digital twin cooperative optimization platform and a fault-tolerant self-healing module. And the distributed control node optimizes an actuator action strategy through a reinforcement learning algorithm. Plugging positioning precision of a clamping plate frame reaches + / -0.02 mm, the dislocation rate of a PCB is smaller than or equal to 0.1%, efficiency is optimized, production changing time is shortened by 83%, productivity is improved by 25%, reliability is enhanced, single-node fault recovery time is smaller than or equal to 5 s, and system availability is larger than or equal to 99.99%.

The invention provides a model training method, device and system based on federated learning and safety protection, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the current training of a target model based on local training data, and obtaining a current model parameter; the local training data is obtained by performing quantum encryption on the original training data; performing homomorphic encryption on the current model parameter to obtain a current encrypted model parameter; uploading the current encryption model parameter to an aggregation node; and receiving global model parameters distributed by the aggregation nodes, and carrying out next training on the target model based on the global model parameters. According to the method, the device and the system provided by the invention, quantum encryption is adopted in an acquisition stage, and homomorphic encryption is adopted in an interaction stage, so that the privacy of an aggregation process is ensured, and a potential attacker cannot obtain model updating details of any single node; in the collaborative training process, it is ensured that data privacy is strictly protected, data are not attacked or tampered, and the efficiency of multi-party collaborative training is improved.

The present disclosure relates to a liquid cooling server cabinet, including a cabinet body, a liquid cooling module, and a pluggable assembly. The cabinet body is provided with a receiving cavity, and the pluggable assembly is arranged in the receiving cavity. The pluggable assembly includes at least one pluggable portion. The liquid cooling module includes at least one liquid cooling unit corresponding to the at least one pluggable portion. The pluggable portion is configured for a plugging and mounting of a single-node server that defines a cooling cavity. When the pluggable portion is mounted with the single-node server, the liquid cooling unit is communicated with the cooling cavity of the corresponding single-node server.

The invention relates to the technical field of data processing and storage, in particular to an asynchronous verification and batch storage system and method for high-concurrency voucher data. Certificate verification is executed based on the memory snapshot, and verification time consumption is improved from the millisecond level of database IO to the microsecond level of memory calculation; a batch persistence mechanism enables the throughput of the system to be improved by dozens of times, and a concurrent storage scene of ten thousand-level TPS can be easily supported; the voucher storage response time is reduced from a hundred millisecond level to a millisecond level; the response is immediately returned to the user after the verification is passed, the user almost does not need to wait, and the operation experience is smooth; the introduction of the message queue enables the system to have peak clipping and valley filling capabilities, and can deal with burst traffic leisurely; the multi-node cluster deployment supports horizontal capacity expansion, the fault of a single node does not influence the overall service availability, and the system reliability is improved.

The invention relates to a configuration implementation method and system for a large-scale FPGA (Field Programmable Gate Array) interconnection system-on-chip. The system comprises 32 data interconnection FPGA core particles and a control FPGA core particle, the control FPGA is connected with the data FPGA through 32 groups of independent Slave Serial interfaces to realize parallel configuration, and state monitoring is carried out through 32 groups of UART (Universal Asynchronous Receiver / Transmitter) interfaces; configuration data are received externally by adopting an RGMII interface, and an upper computer is connected through a system UART. The method comprises the following steps that: after the FPGA is controlled to be self-started from the Flash, an upper computer issues a configuration data packet through the RGMII; the FPGA is controlled to synchronously drive 32 groups of Slave Serial time sequences to complete parallel configuration; the state is fed back in real time through a dual-mode monitoring mechanism, and timeout fault-tolerant logic is implanted. According to the configuration implementation method and system, the configuration efficiency is improved, interface signals are optimized and reduced, single-node fault isolation is supported, and the system availability is improved.

The invention discloses a two-dimensional code data security detection method and system based on a block chain, relates to the technical field of data security detection, and is used for solving the problems that in the prior art, no fine dynamic management of storage hierarchy and access frequency exists, data compliance and integrity verification generally depends on a single-node or centralized mode, and data security is influenced. The dynamic adaptive capacity to data access frequency and risk is lacked, and anomaly detection and response mechanisms of most systems are passive; through a block chain consensus mechanism and Hash verification, the non-tampering and consistency of data are ensured, the layered storage architecture and the intelligent contract are dynamically adjusted, and the real-time detection and automatic response ability to potential threats is improved by using the combination of an isolated forest algorithm and the intelligent contract. And the system can dynamically adjust the strategy according to the access frequency and risk of the data to adapt to different demand changes.

The invention relates to the technical field of communication, in particular to an intelligent chemical single-process optimization design method and system based on dynamic decision, work order state change is carried out through a process engine according to a rule result, and when a rule engine returns a single node, a state field of a current work order record is updated as a target node name; the method has the beneficial effects that the flexibility and the automation degree of the process are improved, automatic adjustment of the process path is realized through a dynamic decision mechanism, manual intervention is reduced, and the processing efficiency is improved; multi-system integration and cooperative processing are supported, and seamless connection with a third-party system is realized due to an open interface and an integration capability, so that the cooperative efficiency of a business process is improved; the mobile terminal is adapted, so that the service linkage efficiency is improved; the process is imported and exported in a one-button mode, the traceability and stability of process configuration are ensured through a process management and version control mechanism, and maintenance and optimization of the process are facilitated.

The invention relates to the technical field of power systems and energy management, and discloses an energy-carbon integrated virtual power plant multi-agent collaborative management and control method and system, and the method comprises the steps: S1, constructing a three-layer control architecture comprising a resource sensing layer, a region coordination layer and a global optimization layer; s2, establishing an energy-carbon coupling state space model, and outputting a target optimization result by taking photovoltaic output, energy storage charging and discharging power, a load demand elastic coefficient and a carbon emission right transaction volume as input variables; s3, generating a scheduling instruction by adopting a rolling optimization strategy; and S4, realizing multi-agent collaboration through a distributed consistency algorithm, exchanging power deviation information by each node based on a local constraint condition, and carrying out iterative calculation until the power deviation of all nodes is less than 1%. A three-layer control architecture is constructed, scheduling lag is shortened through decision making and stage processing of the global optimization layer after preprocessing of the regional coordination layer, the limitation of a single node is broken through through cross-regional coordination, and the overall operation efficiency of the virtual power plant is enhanced.

The invention discloses a clock synchronization method and device, electronic equipment and a medium, and relates to the technical field of communication. And then one or more clock maintenance nodes can be determined by using the time delay between the target node corresponding to the global clock information and each other node except the target node. And if the target node or the clock maintenance node receives the clock synchronization request of the to-be-synchronized node, responding to the clock synchronization request, and pushing the global clock information to the to-be-synchronized node. Both the target node and the clock maintenance node in the distributed system have the global clock information, so that high availability of the global clock information in the distributed system is ensured, and the problem of unreliability caused by clock synchronization depending on a single node in the distributed system is solved.

The invention provides an unmanned system cluster remote co-location and global map construction method and system. Firstly, a remote server determines an initial relative pose of a node according to point cloud data of each node and performs initial global point cloud map splicing; each node obtains a speedometer pose and transmits the speedometer pose to the remote server in real time, and then the global pose P1 of each node is updated in a global point cloud map of the remote server; each node calculates self displacement change according to the speedometer pose, and when the displacement change is greater than a set distance threshold value, a local point cloud d1 is extracted and transmitted to the remote server; the remote server locally extracts a local point cloud D1; and performing registration on the d1 and the D1 to realize updating of the global map by the local point cloud. By using the method, the matching efficiency and the collaborative mapping efficiency can be improved; and meanwhile, the single-node resource consumption is reduced, and the single-node cruising ability is improved.

The invention discloses an Internet of Vehicles double-layer block chain fragmentation method, and relates to the field of intelligent transportation systems.The Internet of Vehicles double-layer block chain fragmentation method is characterized in that consensus tasks are processed in a labor division mode through an'mining-packaging 'double-layer fragmentation structure, parallel transaction processing is achieved, single-node load is reduced, and the overall processing capacity is improved; a node reputation evaluation mechanism is used for dynamically evaluating and screening consensus nodes, low-reputation even malicious nodes are effectively eliminated, the Byzantine risk is reduced, and safe operation of the block chain is guaranteed.

Systems and methods are disclosed to revolutionize blockchain consensus mechanisms by introducing a novel, inclusive framework that enhances efficiency, scalability, and environmental sustainability. Central to this breakthrough are a cluster-based scoring system and a multi-queue dynamic scheduling mechanism, designed to replace resource-intensive consensus models like Proof of Work and Proof of Stake. This approach allows nodes to participate based on merit, determined through an iterative scoring process within clusters, democratizing access, and participation across the blockchain network. The system dynamically adjusts mining complexity as the blockchain evolves, ensuring scalability and reducing energy consumption. A key innovation is the introduction of cooldown periods to prevent dominance by any single node, promoting fairness and security. This decentralized, efficient, and scalable solution paves the way for broader blockchain adoption, maintaining the technology's foundational principles while addressing its traditional limitations.

The invention relates to an openGauss database mirror image backup recovery method and an openGauss database mirror image backup recovery device. The method comprises the following steps: executing full backup, and backing up a dependency item of database service, a data file and a WAL file; incremental backup is executed, and only the data pages and the WAL files which are changed since the last backup are backed up; and executing recovery operation: executing full-amount recovery and specified time point recovery, and supporting single-node recovery and cluster recovery. According to the openGauss database mirror image backup and recovery method based on the CDM technology flow, the backup and recovery efficiency is remarkably improved through the functions of original format backup, incremental backup, specified time point recovery and the like; the method is high in flexibility, supports full backup, incremental backup and specified time point recovery, and can meet backup requirements in different scenes; according to the method, the backup data is kept in a native format, additional processing is not needed during recovery, and data integrity and availability are ensured.

The embodiment of the invention provides a database upgrading method, electronic equipment, a storage medium and a program product, and is applied to the technical field of computers. The method comprises the steps of obtaining configuration parameters of a target database in response to an upgrading operation for the target database; the target database is a database which is providing service; judging whether the parameter value of the configuration parameter is the same as the parameter value of a corresponding preset configuration parameter or not, and if not, judging whether an effective mode of the configuration parameter during upgrading is an effective mode after reloading or not; if yes, reloading the configuration parameters based on the parameter values of the corresponding preset configuration parameters, and upgrading the target database into a single-node database cluster based on a reloading result; according to the method, the current load state is determined, and when the current load state is the low load state, the single-node database cluster is upgraded to the multi-node database cluster, so that services are continuously provided for the user in the upgrading process, the service efficiency and quality are improved, and the user experience effect is improved.

The application relates to a service scheduling and deployment method for Internet of Things edge computing node resources, which is realized based on an Internet of Things edge computing system. The system comprises a cloud data center, a convergence layer core network and a plurality of access layer switch networks connected in sequence. Each access layer switch network is in communication connection with a plurality of edge computing nodes, and each edge computing node is in communication connection with a plurality of data acquisition terminals. The application comprehensively considers the current running state of the edge computing system, network delay problems and running results after deployment, and performs service scheduling and deployment of Internet of Things edge computing node resources on each real-time data stream computing application. The application is suitable for the decision environment of the real-time computing task load and bandwidth dynamic change of the Internet of Things edge computing node, realizes global optimization from the system level, takes into account the single node load capacity, and realizes the optimal scheme and application planning and deployment decision suggestion of the long-period stable operation and real-time task flexible scheduling strategy.