465 results about "Node count" patented technology

The invention provides a real estate full life cycle intelligent management method and system based on Internet of Things perception, and the method comprises the steps: distributing a unique hardware identifier of equipment, combining a lightweight digital certificate with a pre-shared key to achieve two-factor authentication, and storing a root certificate in a cloud end; an access authentication process is optimized, an identity label and a certificate signature request need to be submitted when a node accesses for the first time, a temporary session key is generated after the gateway verifies, and abnormal access is immediately isolated and reported; data integrity verification is implemented, and after a sensor collects data, an abstract is generated and data encryption transmission is carried out; after decryption, the receiving end recalculates the abstract for comparison, and if not, the abstract is discarded and nodes are marked to be abnormal; a data anomaly detection model is constructed, energy consumption fluctuation is determined based on historical data, a frequency baseline is collected, data reasonability is monitored in real time, secondary authentication is triggered when the data is abnormal, and node data access is suspended if the data fails; a hierarchical key system is established, hardware is solidified by a root key, session keys are alternated for 24 hours, and data encryption keys are dynamically derived and distributed through encryption channels.

The invention provides a computing power center resource centralized self-adaptive control scheduling system and method, and the method comprises the steps: S1, a user submits a computing power training task through an API, and sends the task to a DAG task composer, and forms a task list to be scheduled; s2, the intelligent monitoring analysis module is used for continuously collecting node data and calculating real-time CS and HS scores of each node; s3, analyzing the dependency relationship type data by a task composer, and calling a dynamic programming algorithm in an adaptive scheduler to make a decision; s4, the adaptive scheduler performs dynamic task distribution according to the task list of the DAG task orchestrator and the intelligent monitoring analysis module, and S5, the distributed runtime and environment management module is used for uploading the prepared Docker mirror image to the distributed storage; and S6, through the unified communication adaptation layer, the mirror image is pulled from the distributed storage on the target node and the container is started, the user does not need to concern the difference of the operating system in the whole process, and efficient and intelligent adaptive scheduling is realized.

The invention belongs to the technical field of cloud side-end collaborative data processing, and discloses a cloud side-end collaborative heterogeneous data fusion processing system, which establishes dynamic association of data features, resource states and service priorities through a scheduling module, and adopts a reinforcement learning algorithm combining DQN and an attention mechanism to perform fusion processing on heterogeneous data. Task allocation weights are dynamically adjusted with the minimum delay, the highest precision and the maximum business value as targets; the sensing module and the preprocessing module complete lightweight processing such as feature extraction and noise reduction redundancy elimination at the edge end, and the cross-node data transmission amount is reduced. The complex fusion task dispatches cloud computing power support, and reserves resources in advance by means of an LSTM-based task urgency predictor; the cross-modal fusion module designs a double-stage fusion algorithm, in the first stage, cross-modal semantic association is enhanced through multi-head self-attention, and in the second stage, the fusion weight is adjusted according to the reliability coefficient of the sensing module.

The invention relates to the technical field of anti-interference of intelligent monitoring data acquisition of a new energy power station, in particular to a self-adaptive anti-interference system for data acquisition of an intelligent auxiliary monitoring system. A windowing judgment mechanism is formed based on cross-node stage consistency; thirdly, defining participation paths of the data units with different stage attributes in cross-node association analysis, and aligning and screening multi-node data through data consistency management; when the stage consistency window meets a release condition, controlled stage regression processing is performed on the data unit in the unstable stage, so that the data acquisition node gradually enters a unified stage attribute; according to the method, the instantaneous abnormal processing of the interference influence is converted into staged and structured management, and the continuity, consistency and reliability of data acquisition and analysis in a complex power monitoring scene are greatly improved.

The invention relates to a distributed compensation control system and method for a power distribution network, and the system comprises a distributed multi-source module which is used for collecting the node data, equipment operation state data and system global operation data of each key node in real time; the edge decision-making module is used for acquiring local node data of the local key node and generating a plurality of corresponding initial compensation instructions of the distributed compensation equipment according to the local node data; the collaborative optimization module is used for receiving and fusing all the preliminary compensation instructions, the equipment operation state data and the system global operation data, calculating through a unified nonlinear comprehensive evaluation function to obtain a system comprehensive operation index, and generating a global collaborative optimization instruction; and the control execution module is used for distributing the global collaborative optimization instruction to the corresponding edge decision module so as to drive the plurality of distributed compensation devices to execute collaborative compensation operation. Preventive maintenance and fault early warning are achieved, the service life of equipment is effectively prolonged, and the overall reliability of the system is improved.

The invention relates to the technical field of document management, and relates to a legal document key point automatic extraction and association method and system.The new legal document data of a target case is obtained, a preset document fingerprint algorithm is used for automatically comparing the new legal document data with a historical reference document, differential text data fragments are extracted, and the text data fragments are extracted; the method comprises the following steps of: performing deep semantic analysis on different text data fragments to generate candidate triple data containing entities and relationships, intelligently mapping the candidate triple data into a pre-constructed case knowledge graph, quickly positioning graph anchor nodes with data change, and then, performing data change on the basis of change types of the different text data fragments. And executing atomic updating operation on the map anchor node, including updating the dynamic mark of the node state attribute, and finally generating the change source node data with the latest state identifier. The problems that the current legal case data updating depends on manpower, is low in efficiency and is easy to make mistakes are effectively solved.

The invention relates to the field of distributed storage, and discloses a distributed memory system based on erasure codes and a dynamic repair mechanism. Comprising a data node cluster, a metadata management cluster, a bandwidth token management module, a dynamic repair composer and a repair agent node. And the data node cluster divides the object into strip generation data fragments and verification fragments and dispersedly stores the data fragments and the verification fragments according to a placement rule. And the metadata management cluster maintains object stripe mapping, a fragment position set, erasure code protection configuration and a version epoch, and records a repair intention log. And the bandwidth token management module grants repair execution permission according to the fault domain budget. The dynamic repair composer generates availability repair and durability repair tasks, the temporary check fragments are written in when the number of the available check fragments is lower than a threshold value in the availability stage, and the configuration fragments are recovered and the temporary fragments are recovered in the durability stage. And the consistency of version epochs is verified before the agent node is repaired and written back, and if not, recalculation is carried out.

The invention discloses a service agent evaluation method and device, equipment, a storage medium and a program product, and relates to the technical field of agents, and the method comprises the steps: obtaining node data generated by each function node of a service agent when the service agent executes a task; extracting industry features from the node data, and determining an industry field to which the business agent belongs when executing the task based on a matching result of the industry features and a preset industry feature library; screening from a preset evaluation index library to obtain an evaluation index set matched with the industry field; and evaluating the business agent according to the evaluation index set to obtain an evaluation result of the business agent in the industry field. According to the invention, the problems of lack of industry pertinence and inaccurate evaluation in the prior art are effectively solved.

The invention discloses a block chain technology and big data-based data synchronous scheduling management and control system, and relates to the technical field of data synchronous scheduling management and control. Comprising a cross-level dynamic observation module, a causal coherent decomposition module, an anti-fact playback construction module, a double-mirror-image time scale rearrangement module, a time-varying virtual impedance regulation and control module and a time reversal phase traction module. And the cross-level dynamic observation module constructs a cross-level cache link dynamic observation layer, collects cache pressure fluctuation data and link delay pulsation data of each node in the block chain network in real time, and generates a coupling feature baseline for representing a relationship between cache pressure and link delay. According to the invention, through multi-layer time sequence observation and time baseline correction, accurate control of cross-node data synchronization is realized, and repeated confirmation and account book bifurcation are prevented; and resonance energy is absorbed through the time-varying virtual impedance and the energy buffer zone, so that self-balancing and self-repairing of the system are realized, and global consistency and scheduling stability of the block chain are ensured.

The embodiment of the invention provides an inference acceleration method and system based on a large language model. The method comprises the following steps of: firstly, reading a query vector, a key vector and a value vector which are calculated by a matrix processing kernel and are subjected to offset addition and quantization operation from a shared cache by virtue of a multi-head attention kernel in a system, respectively calculating an attention score and target key value data, and outputting data to be decoded; the single-node calculation efficiency is guaranteed through customized hardware pipeline design; then, the query vector is recalculated in the decoding stage, the target key value data stored in the high-bandwidth storage key value cache region in the pre-filling stage are directly reused, and resource waste caused by repeated weight loading is avoided; finally, a model parallel strategy is adopted, calculation tasks of the large language model are distributed to all accelerator nodes, distributed execution of large-scale matrix operation among multiple nodes is achieved, the node number can be flexibly expanded according to the model scale in the scheme, and the expansibility of the reasoning acceleration scheme is remarkably improved while reasoning efficiency is guaranteed.

The invention discloses a blockchain-driven server data encryption storage system and method, and relates to the technical field of distributed data security storage. After original data are encrypted and fragmented, a dynamic signature group is established for each fragment, and a search token is generated by using a searchable encryption engine; dynamically calculating a node number threshold value required by signature through an intelligent contract deployed on a block chain, and realizing authorized signature of a search token; the storage node executes search based on authorization, returns a result, generates an operation fingerprint composed of search token hash, result set hash, a timestamp and a participation node identifier, and stores the operation fingerprint to the block chain to realize operation full-link audit; the intelligent contract continuously monitors node behaviors, updates reputation scores and dynamically adjusts signature group composition and threshold values, dynamic self-adaptive access control and non-tampering operation auditing can be achieved, the safety and controllability of a system in a node dynamic change environment are improved, and the safety and reliability of the system are improved. And meanwhile, the search security and the operation efficiency are enhanced through blind processing and lightweight verification.

The invention relates to a practical consensus algorithm for file resource sharing, which comprises reputation-driven task allocation: according to reputation values calculated in real time, nodes with high reputation values are preferentially selected by the algorithm to form a core consensus group to execute the most critical consensus task, and the number of nodes participating in core communication is remarkably reduced. And protocol flow optimization: fundamentally reducing the communication complexity to O (n) level by limiting the scale of the core consensus group and reconstructing a message transmission path. And node state dynamic autonomy: the algorithm has real-time evaluation and dynamic adjustment capabilities on node types. The reputation model continuously monitors node behaviors, can automatically perform degradation processing on low-reputation or fault nodes, and can timely discover and safely isolate or delete bad nodes through a specific mechanism without restarting the system. Through test verification, the reliability, safety, higher throughput and lower delay of the consensus algorithm are verified.

The invention relates to a power fault diagnosis method and system based on large model retrieval enhancement. The method comprises the following steps: firstly, initializing a federated network, and locally vectorizing multi-modal heterogeneous power data at each node to generate a private vector index; performing federated collaborative retrieval by combining the fault diagnosis request, the private vector index and the public key infrastructure to obtain a globally sorted knowledge fragment list; and finally, constructing a retrieval enhancement prompt according to the knowledge fragment list and the diagnosis request, and generating a fault diagnosis conclusion text by utilizing large language model reasoning. By adopting the method, dispersed multi-source knowledge can be effectively fused on the premise of ensuring the data privacy security of each node, so that the accuracy and reliability of fault diagnosis are improved.

Apparatus and method for prefetching node data. For example, one embodiment of an apparatus comprises: ray tracing acceleration hardware to manage active ray tracing stack allocations within a traversal stack; and stack management hardware logic to issue a prefetch operation comprising an indication of bounding volume hierarchy (BVH) node data to be prefetched and an indication of a cache level, wherein responsive to performing the prefetch operation, the BVH node data is to be prefetched to the indicated cache level.

The invention relates to the technical field of data management, in particular to a data management method and system.The method comprises the steps that a distributed monitoring system is used for collecting the transaction operation state of a multi-node database in real time, and dynamic visibility range calibration data is obtained; performing transaction consanguinity tracking algorithm processing on the original transaction operation state data based on the dynamic visibility range calibration data to obtain transaction consanguinity tracking data; performing cross-node data dependence path identification according to the transaction blood relationship tracking data to obtain cross-node data dependence path data; performing dirty reading risk quantitative evaluation to finally obtain a dirty reading risk quantitative evaluation value; obtaining self-adaptive transaction isolation level adjustment data; and a data basis is provided for subsequent targeted treatment. The system can realize collaborative optimization of storage efficiency, execution performance and resource utilization rate on the premise of ensuring data consistency, and provides core technical support for stable operation of a large-scale distributed database.

A search agent training system includes a trainer device. The trainer device includes a trainer network simulation of variable size, which further includes at least one selectable action, at least one selectable node, and a trainer knowledge base, which further includes at least one selectable action outcome probability value. The trainer knowledge base is populated by a quantification system. The trainer device receives an incoming action message from a search agent device including a selected action and a selected node. Next, based upon: a resulting action outcome probability value, the selected action, and the selected node, a resulting observation and a resulting reward is sent to the search agent device. The trainer device blocks node count report messages to the search agent device from the trainer device.

The invention discloses a distributed relay verification rapid transaction system, and belongs to the technical field of data analysis. The system comprises a transaction control module, a safety management module, a data acquisition module, a region management module, a model training analysis module and a dynamic selection calculation module. The transaction control module is used for transmitting transaction data to different nodes for transaction; the security management module is used for dividing importance levels of transaction data; the data acquisition module is used for acquiring node data and network data; the area management module is used for calculating a network risk value in an area; the model training analysis module is used for analyzing the data transmission quality of transaction data under different node numbers and network risk values; the dynamic selection calculation module is used for generating transaction instructions of different transaction data transmission paths; according to the invention, the transaction data transmission path is adjusted in real time, so that the adaptive capability and the anti-interference capability of the system to a complex network environment are improved.

The application discloses a simulation processing method for CCFL phenomenon of a downcomer based on RELAP5, and specifically comprises the following steps: S1, obtaining geometric parameters and operation condition parameters of the downcomer, making a node division scheme, and obtaining node information, wherein the node information comprises a number of circumferential nodes, a number of axial nodes, and a number of single pipe nodes between multiple pipes; S2, writing a RELAP5 program on an Input card, performing a thermal hydraulic calculation, and obtaining a first parameter which changes in real time; S3, extracting a second parameter through a strip card to obtain a third parameter, wherein the third parameter comprises gas-liquid phase flow, pressure and velocity; S4, importing the third parameter into a processing software MATLAB, reading a fourth parameter of the gas-liquid phase according to the node information set in S1; and S5, performing two-dimensional cloud chart drawing on the fourth parameter in S4. The application can quickly obtain required results under different node division schemes and different geometric parameters and operation parameters, and improve analysis efficiency.

The application discloses a path planning method, system, device and medium based on an improved A-star algorithm, relates to the technical field of path planning, and solves the technical problems of poor path planning safety and low efficiency in a warehouse robot system. Technical solution points estimate the area openness degree through a cost function based on obstacle density, so that the planned path is more inclined to the open area. The node expansion is performed through the optimized node expansion strategy, the nodes adjacent to the current node up and down or left and right are preferentially processed, the expansion of internal obstacle nodes is skipped, the number of expanded nodes is greatly reduced, and the nodes that may cause path collision or insecurity are effectively excluded to avoid meaningless path search. The final expanded node array is subjected to path optimization through a bidirectional path preprocessing optimization algorithm, so that the path is more concise and smooth, and the overall time consumption is reduced.

This invention relates to the fields of machine learning and edge computing technology, specifically to a blockchain-based trusted distributed hybrid expert model edge computing system. The system includes a task publisher for publishing learning tasks, which may be training or inference tasks; a blockchain network for receiving learning tasks and evaluating expert weights to obtain sparse activation expert index results; a blockchain network for receiving learning task processing results from the edge layer and achieving consensus; a gating network deployed within the blockchain network; an edge layer for downloading the corresponding expert model from the storage layer based on the sparse activation expert index results to process the learning tasks and uploading the processing results to the blockchain network; and a storage layer for storing all expert networks, each with a CID. This invention significantly improves the defense capability of the distributed MoE network against malicious edge node data tampering attacks, thereby ensuring the learning performance of the MoE system.

To provide a data tampering detection device that can accurately detect alterations to the original data. [Solution] The system includes: a source data acquisition unit 91 that acquires source data from source data DB22; a source data match determination unit 92 that calculates a hash value from the source data acquired by the source data acquisition unit 91 and determines whether the calculated hash value matches the source data hash value corresponding to the source data; a third-node data acquisition unit 93 that acquires source data hash values ​​corresponding to the source data from other nodes 30B and 30C; a hash value verification unit 94 that verifies whether the source data hash value that has been determined to match the source data has not been tampered with, based on the source data hash value recorded in the local node 30A that corresponds to the source data and the source data hash value acquired from other nodes; and a tampering determination unit 95 that determines whether the source data has been tampered with, based on the determination result of the source data match determination unit 92 and the verification result of the hash value verification unit 94.

The invention discloses a computer fault rapid positioning method, and relates to the technical field of intelligent operation and maintenance, and the method comprises the steps: firstly, obtaining global monitoring data of a target computer, carrying out the hierarchical topology modeling of the target computer, and constructing a candidate monitoring point set and node data according to a hierarchical topology model; secondly, performing optimization positioning calculation on the monitoring point set and the node data by using an RCO algorithm to obtain a monitoring point subset; constructing a hierarchical fault positioning model based on the hierarchical topology model and the monitoring point subset, and performing backtracking hierarchical positioning on global monitoring data to obtain the fault probability of each component of the computer; and finally, constructing a diagnosis scheduler, issuing the diagnosis scheduler to each monitoring point in a distributed manner, and generating a fault priority scheduling queue in a closed-loop manner, thereby remarkably improving the positioning fault-tolerant rate in a complex fault scene, and reducing the resource occupancy rate.

This invention discloses a task scheduling method and system based on an ITSM platform, belonging to the field of IT service management technology. The method includes the following steps: acquiring an available execution node cluster; collecting task execution records of nodes within a second scheduling set to generate a true performance baseline; performing periodic node rotation operations between the first and second scheduling sets based on historical execution data and the true performance baseline; calibrating the historical execution data of the first scheduling set; monitoring the real-time load distribution of the first scheduling set to trigger emergency node rotation operations; performing emergency node rotation operations and resetting historical data for nodes that have undergone rotation; and updating the initial node quantity ratio. This invention solves the problems of hotspot solidification, self-fulfilling oracle, and cluster resource utilization imbalance caused by historical affinity bias in existing technologies by dividing execution nodes into a first scheduling set and a second scheduling set.

The invention discloses a network resource abnormal allocation scheduling processing method and system and a storage medium, and the method comprises the following operation steps: collecting transmission data in a dynamic network environment in real time, and carrying out the preprocessing of the transmission data in the dynamic network environment, and obtaining the data of each network node; analyzing behavior data of the network node data, and clustering the network node data with the same behavior data by using a clustering algorithm to obtain abnormal network nodes; analyzing the abnormal network node according to a pre-collected historical database, and calculating a load score of the abnormal network node; and performing node data resource allocation on each node according to the load score of each network node data. The load condition of the network nodes is identified through clustering or combination of roughness, time, similarity and final confliction on the network nodes through various types of collected data in transmission, so that the abnormal distribution of the network nodes is adjusted.

The invention relates to a multi-area data migration method based on association perception and a storage system, and the method comprises the following steps: each storage node records data access information, and periodically uploads the data access information to a central control node, the data access information comprises a source area, time and target data of each access request, the heat of the nodes and the data volume of the nodes; hotness data processing is carried out at the central processing node to obtain hotspot data, and correlation analysis is carried out to obtain the correlation between the hotspot data and the area and the correlation between the hotspot data; and performing a data migration decision based on the data access information and the relevance, the data migration decision including determining nodes migrating data and migrated data in the nodes, and determining an area receiving the data and nodes receiving the data in the area. Compared with the prior art, the method has the advantages of reducing cross-regional access times, relieving generation of hotspots and the like.

The application discloses a method and device for correcting node data, electronic equipment and medium. The method can include: determining an incorrect trace in a common shot gather, determining a receiver point corresponding to the incorrect trace; determining correct trace data according to the receiver point; replacing the data of the incorrect trace with the correct trace data, and outputting a correct common shot gather. The application is characterized by a large amount of node data, and the production efficiency is improved by accurately correcting the incorrect single trace data in the single shot gather data.

This disclosure provides a resource management method, apparatus, electronic device, and medium, relating to the field of computer technology, and particularly to the field of equipment management and application management technology. The specific implementation scheme is as follows: First, determine whether it is necessary to expand or shrink the node set. If expansion is required, select nodes from the node inventory in ascending order of price, add these selected nodes as idle dynamic nodes to the node set, and continue this process until the number of idle dynamic nodes in the node set reaches a preset quantity. Neither the nodes in the node inventory nor the idle dynamic nodes are running any business applications. Second, if shrinking is required, delete nodes from the idle dynamic nodes in the node set in descending order of price, and continue this process until the number of idle dynamic nodes in the node set reaches the preset quantity. This allows for more targeted node expansion and shrinking.

The embodiment of the invention provides a node graph rendering method and related equipment. The node graph rendering method comprises the following steps: monitoring the number of nodes contained in a node graph; if the number of the nodes does not exceed a preset node number threshold value, using a real-time rendering mode to render the node graph; and if the number of the nodes exceeds a preset node number threshold value, rendering the node graph by using a background rendering mode. According to the technical scheme, the number of the nodes in the node graph is monitored, real-time rendering is forbidden when the number of the nodes exceeds the preset node number threshold value, background rendering is used instead, the final layout of all the nodes is calculated through a background program, and after calculation is completed, the layouts of all the nodes are rendered into the page at a time, so that the layout of all the nodes is rendered into the page at a time. According to the method, frequent calculation and rendering are reduced, and the performance bottleneck of real-time rendering is avoided, so that the page loading speed and the user experience are remarkably improved.

The invention discloses an intelligent report generation method, system and device based on a multi-agent workflow and a medium, belongs to the technical field of artificial intelligence and natural language processing, and aims to solve the technical problem of how to improve report generation efficiency while ensuring professional report content. According to the technical scheme, the method comprises the steps of intelligent template analysis, wherein a template is analyzed, and paragraph structures and data category demand information are extracted; intelligent data matching: integrating a fuzzy character string matching algorithm and a context semantic understanding technology, and performing intelligent semantic mapping on the CSV structured data and a template placeholder; workflow arrangement: constructing a multi-agent cooperation framework based on LangGraph, adopting a TypeDict type to restrain and manage a workflow state, defining a complete state space including input information, an intermediate processing result and final output, and realizing an end-to-end automatic process of report generation; wherein the workflow arrangement comprises a template analysis node, a data processing node, a paragraph generation node and a report formatting node.

The disclosure provides a method for determining a correlation relationship, which can be applied to the technical field of computers. The method comprises: obtaining a to-be-processed data table from a configuration management system, obtaining a first model list, a second model list and a third model list according to a preset division rule based on the to-be-processed data table; obtaining determined node data, first relationship type data and second relationship type data based on the first model list, the second model list and the third model list, and storing the determined node data, the first relationship type data and the second relationship type data in a graph database; obtaining third relationship type data based on production data and calling data obtained from a server and an application connected to the server, and storing the third relationship type data in the graph database; and determining a correlation relationship topology graph based on the node data, the first relationship type data, the second relationship type data and the third relationship type data. The disclosure also provides a data processing device, a computing device and a medium.