35 results about "Converged storage" patented technology

The invention relates to the technical field of artificial intelligence, in particular to a scene application operation maintenance platform based on an artificial intelligence model, which comprises a reasoning state sensing module, a load balancing scheduling module, an intelligent resource allocation module, a deployment configuration adjustment module and a scene feedback integration module. According to the method, by sensing and reasoning process resource consumption and response time migration trend, abnormal tasks caused by resource fluctuation can be accurately recognized, the state monitoring sensitivity is improved, task allocation records are analyzed to construct conflict structures, the resource conflict recognition and visualization capability is enhanced, the model operation level and the GPU vacancy rate are combined, a task migration path is optimized, and the task migration efficiency is improved. Node resource balance is realized, storage frequency, memory margin and network delay are fused during deployment, migration stability is guaranteed, drift tasks are identified through response logs and call records, an operation and maintenance list is generated, operation and maintenance accuracy and multi-scene matching capability are improved, and reasoning task stability and resource scheduling intelligent level are enhanced.

The invention relates to the field of community old-age care, and discloses a community old-age care-oriented medical-care-and-care-combined data intercommunication and service coordination system, which comprises a sensing module used for acquiring physiological data of old people, old-age care service data, environment data and service demand information to form multi-modal information; the network module is used for carrying out multi-modal information transmission, protocol conversion and edge calculation preprocessing to obtain processed data; and the data module is used for constructing a standardized data lake according to the processed data by adopting a unified data standard and a main data management technology, and carrying out fusion storage, treatment and safety protection to obtain multi-source information. Multi-modal information is collected to provide a data basis for cross-mechanism cooperation, data transmission and preprocessing are performed, and a standardized data lake is constructed through a unified data standard and main data management, so that medical institutions, pension institutions and community grids can share global data such as health states, service records and the like of old people in real time.

The invention discloses a comprehensive monitoring platform for an auxiliary system of an intelligent substation, and the platform comprises a sensing layer which is provided with diversified sensors and is used for collecting the operation state, environmental parameters, security and protection information and fire-fighting information of equipment in the substation in real time, and the sensors have the self-diagnosis and self-calibration functions; the edge computing layer is composed of a plurality of edge computing gateways; the cloud platform is used for carrying out deep fusion, storage, analysis and intelligent decision making on the data uploaded by the edge computing node; and the application layer is used for providing an interactive interface and a functional module for a user, and the user can log in the technology through various terminal devices. Through a multi-level architecture and an intelligent analysis technology, comprehensive perception, intelligent analysis and automatic control of equipment states are realized, faults are predicted in advance, downtime is reduced, and reliability and stability of a power system are improved. The response time is shortened by an intelligent linkage strategy and an edge computing local decision-making mechanism, sudden safety events and equipment faults can be quickly handled, and accident loss is reduced.

The invention belongs to the technical field of databases, and particularly discloses an index column fusion storage method and system.The method comprises the steps that a target column is determined, the target column is a data column configured with a Pstort index in a column storage table, and the character length of the field type of original data of the target column is larger than that of an index position identifier; the column storage table is a data table adopting a column storage mode, and the index position identifier is used for indicating the position of the original data in the index file; and configuring the field type of the target column as an index position identifier type, so that each row in the target column stores an index position identifier. By means of the method and device, high-performance and high-compression index column data fusion is achieved, and the occupation amount of the data files and the index files in the disk space can be reduced under the condition that the query efficiency is considered.

The invention discloses a multi-source document management method and device based on knowledge construction and fusion storage, and relates to the technical field of document management, and the method comprises the steps: receiving a multi-source document to an object storage system, and recognizing the document type; performing document analysis and structure extraction according to the document type; extracting pictures in the image-text mixed content, uploading the pictures to an object storage system, generating a mapping dictionary, and inserting picture marks in a text part of the mapping dictionary; carrying out structured processing on contents of the table key value pairs to extract summaries and abstracts; performing standardization processing and semantic slicing on the processed image-text mixed content, table key value pair content and / or plain text content to generate knowledge fragments; constructing a knowledge extracting questions from knowledge fragments; the knowledge fragments are stored in a first index, and the questions and IDs of the corresponding knowledge fragments are stored in a second index; generating vectors for each knowledge fragment and question, embedding and writing the vectors into a vector database; and performing document management based on the knowledge base. The document management efficiency is improved.

This invention discloses an intelligent analysis and early warning cloud database system for big data in water conservancy project operation and maintenance, specifically relating to the field of water conservancy project operation and maintenance technology. The system is based on a cloud-native architecture and includes an intelligent data lake warehouse, a time-series graph fusion storage engine, an embedded model computation module, a collaborative early warning and analysis module, and a self-learning optimization module. The intelligent data lake warehouse performs semantic annotation preprocessing on multi-source heterogeneous operation and maintenance data; the time-series graph fusion storage engine deeply integrates domain knowledge graphs with semantically annotated time-series data sequences, logically binding the time-series data sequences to graph nodes through globally unique identifiers to form a time-series-graph hybrid data model; the embedded model computation module deploys dedicated analysis models; the collaborative early warning and analysis module aggregates multimodal evidence chains, schedules model collaborative computation, and performs fusion analysis to generate early warnings; the self-learning optimization module optimizes the model online based on feedback. This invention achieves data fusion storage and intelligent early warning, improving operation and maintenance efficiency and reliability.

The invention discloses a cloud-edge fusion storage system supporting federated learning, and belongs to the field of cloud-edge cooperative control. An edge client comprises a CPU, a GPU, an RAM and a CSD; the RAM and the CSD are organized into a memory pool based on a CXL protocol; in each round of federated learning, the edge client side executes the following steps: acquiring global update data from the central cloud side and storing the global update data into the memory pool; the global update data comprises an updated global model and a global sample accumulative gradient; training the updated global model by using the local data set to obtain an updated local model, and forming local update data by the updated local model and the local sample cumulative gradient; the importance score sequence of the samples in the local data set does not exceed a preset sample quantity threshold value; and uploading the local update data to a central cloud, so that the central cloud aggregates the local update data of each edge client into global update data. According to the invention, the storage efficiency and the I / O performance of the edge client in a stream data federated learning scene can be improved.

The application relates to an ultra-fusion storage system, relates to the technical field of data storage management, and comprises data collection equipment used for collecting monitoring data of a highway toll station, an edge computing device in communication connection with the data collection equipment and used for pre-processing the monitoring data, a network switch in communication connection with the edge computing device and used for transmitting the pre-processed monitoring data, and a computing storage node in communication connection with the network switch and used for receiving the pre-processed monitoring data, analyzing the pre-processed monitoring data and storing the pre-processed monitoring data. The application has the effect of improving data computing storage efficiency.

The application relates to the technical field of network storage, and discloses a data processing method and device of a converged storage system, equipment and a storage medium, which comprises the following steps: acquiring object data uploaded to a converged storage system through a first storage protocol; the converged storage system takes a storage mode supported by a second storage protocol as a data storage base, and the first storage protocol and the second storage protocol are converged and intercommunicated; judging whether a storage directory in the object data contains a multi-level directory level, if yes, the multi-level directory level is segmented to obtain a plurality of target directories; the multi-level directory level in the converged storage system is constructed by creating the target directories in the converged storage system respectively, and target objects in the object data are stored under the multi-level directory level in the converged storage system. The application can guarantee the integrity of the storage protocol after convergence and intercommunication.

The invention relates to a multi-source image data fusion storage management system in the field of data storage management systems, which comprises a system end and an equipment end, the equipment end comprises a data storage module, and the system end comprises a data acquisition module, a front-end synchronization module, an operation and maintenance module, a hierarchical management module and a data unification module; the data storage module comprises a plurality of distributed storage areas, each distributed storage area comprises a distributed cache area and a file storage unit, the operation and maintenance module is used for monitoring a system load and dynamically adjusting a synchronization strategy of the front-end synchronization module according to the system load, and the level-to-level management module is used for setting priorities and association relationships of the distributed storage areas. According to the method, efficient data storage and management are achieved, the timeliness and stability of data synchronization are ensured through fine management of the access frequency, the capacity size and the system load condition of the data files, and meanwhile the utilization efficiency of system resources is improved.

The invention discloses a secure storage synchronization method for cloud edge fusion, and belongs to the field of computer storage, in the method, a synchronization participant initiates a synchronization request when a file needs to be synchronously modified, a cloud center node is responsible for processing the synchronization request and monitoring resources of each edge node, and the cloud center node is responsible for processing the synchronization request; the system performance is prevented from being affected by a large number of requests of malicious users through a token bucket algorithm, current limiting is achieved under coordination of a cloud center node, direct data communication of all edge nodes is coordinated, a safe communication channel between two synchronous parties is established, and the system safety is improved. By adopting the adaptive method provided by the invention, the synchronization mode is adaptively selected for efficient synchronization according to the network state during synchronization and the size of the file needing to be synchronized; by adopting the improved incremental synchronization method provided by the invention, the overhead of the incremental synchronization process can be obviously reduced; the problems of large storage synchronization calculation overhead, high time delay, limited edge device resources, high isomerism and poor reliability in the existing cloud edge fusion storage are solved.

The application discloses a method, device, file system and storage medium for storage space allocation, and belongs to the technical field of file systems. The method comprises the following steps: receiving a data write request corresponding to a first file; determining a to-be-added data amount of the first file according to a to-be-written data amount, a current data amount of the first file and a current operation pointer of the first file; determining that the to-be-added data amount meets a new storage space allocation condition, and determining that a storage space meets a low residual capacity condition; selecting at least one to-be-fused storage file meeting a low usage condition of a storage page; selecting at least one idle storage page as a to-be-used storage page; and writing data stored in a terminal storage page corresponding to the first file, to-be-written data of the first file and data stored in a terminal storage page corresponding to the to-be-fused storage file into the to-be-used storage page. The application can provide storage space utilization.

The present application relates to a kind of multi-source data processing method, device, electronic equipment and storage medium.The method comprises: obtaining initial multi-source data;After the initial multi-source data is preprocessed, first type data is temporarily stored in distributed cache queue;Based on the identity of each data in the first type data, the first type data is associated and fused, to obtain second type data;According to the preset multi-dimensional hierarchical strategy, each fusion data of the second type data is distributed to the storage layer corresponding to the storage module, and the storage module includes at least two storage layers.The present application realizes the automatic linkage of multi-source data accurate fusion and hierarchical storage by the core design of "fusion-storage automation linkage" and "multi-dimensional hierarchical rule".

This application discloses a data storage method, apparatus, electronic device, and readable storage medium, relating to the field of data storage technology. The method includes: in response to a converged storage instruction, acquiring source data in a first format; on the transmission path where the source data is written to target memory, converting the source data into target data in a second format using an accompanying processing module configured on the transmission path, and packaging multiple target data sets into combined data matching the access granularity of the target memory; and writing the combined data into the target memory. This application has the effects of reducing the computational load on the EU (Entity Memory), improving the utilization rate of core computing resources, optimizing the data processing pipeline, and achieving deep task pipeline parallelism.

The application discloses an intelligent substation auxiliary system comprehensive monitoring platform, which comprises: a sensing layer: diversified sensors are arranged for collecting the running state of equipment in a substation, environmental parameters, security information and fire-fighting information in real time, and the sensors are provided with self-diagnosis and self-calibration functions; an edge computing layer: composed of multiple edge computing gateways; a cloud platform: used for deep fusion, storage, analysis and intelligent decision of data uploaded by the edge computing nodes; an application layer: providing an interactive interface and functional modules for users, and the users can log in the technology through various terminal devices. Through the multi-level architecture and intelligent analysis technology, the equipment state is comprehensively sensed, intelligent analysis and automatic control are realized, faults are predicted in advance, downtime is reduced, and the reliability and stability of the power system are improved. The intelligent linkage strategy and the edge computing local decision mechanism shorten the response time, can quickly dispose of sudden safety events and equipment faults, and reduce the accident loss.

The invention discloses a data optimization storage method based on artificial intelligence and a big data system, and relates to the technical field of data storage, and the method comprises the steps: obtaining files, classifying the files into pictures, documents and videos, and extracting the features of the files through different methods; through a multi-modal learning technology, mining semantic association among the pictures, the documents and the videos, and constructing an association graph; performing compression, hierarchical storage and index optimization on the data according to the semantic association and the association graph; according to the method, the data is stored, the storage state is monitored in real time, the storage performance indexes are collected, the model is optimized according to the performance indexes, fusion storage of pictures, documents and videos is achieved, and subsequent file query is facilitated by intelligently analyzing data features and mining semantic association among the data.

The invention discloses a digital port data storage and analysis method and device. The method comprises a data modeling step, a unified storage step, a dynamic expansion step and a query optimization step. According to the method, data of a plurality of traditional discrete business tables are fused and stored in a unified physical table according to a time main line, the association relation between the tables is internalized into a structured format of the data, and dynamic seamless expansion of a data mode and qualitative leap of query performance are achieved through an innovative index strategy and a storage optimization technology. The structure that hundreds of tables are stored in the database is simplified into the structure that only one to three tables are stored, and the maintenance work of the table structure in the database is greatly reduced.

The present disclosure relates to the technical field of converged storage, and particularly relates to a data processing method and device, equipment and a computer readable storage medium. The present disclosure dynamically adjusts the heat value of a data block based on the access condition of the data block, and when the first storage space meets a preset data fall condition, determines a target migration data block according to the dynamically adjusted heat value, and migrates the target migration data block to a second storage space. The heat value is used to dynamically manage the data block, which reduces the increase of read-write delay and the slow response of requests caused by the division of fixed areas in the first storage space, and improves the flexibility of data storage in the converged storage system.

An improved architecture is provided which enables significant convergence of the components of a system to implement virtualization. The infrastructure is VM-aware, and permits scaled out converged storage provisioning to allow storage on a per-VM basis, while identifying I / O coming from each VM. The current approach can scale out from a few nodes to a large number of nodes. In addition, the inventive approach has ground-up integration with all types of storage, including solid-state drives. The architecture of the invention provides high availability against any type of failure, including disk or node failures. In addition, the invention provides high performance by making I / O access local, leveraging solid-state drives and employing a series of patent-pending performance optimizations.

The invention provides a multi-page lookup table cache fusion method and device based on a many-core system. The CPU in the many-core unit issues instructions and data, the GPU, the ALU, the SFU and the FPU respectively execute corresponding operations and generate results, and the many-core unit transmits the operation data and the results to the Cluster; the ClusterControl of the Cluster generates a hash value corresponding to the data, and transmits the data, the result and the hash value to the Group; the Group sends the data, the result and the hash value to a multi-page index module, and the multi-page index module presets paired index pages according to the number of the Group in advance; the multi-page index module buffers data and Hash values, extracts Tag information, indexes to paired index pages corresponding to Group through the Hash values, writes in the Tag information and data in an alternating mode, and then eliminates the instruction competition problem; and transmitting the processed data to the L3Cache according to an index page registration sequence to complete cache fusion storage. According to the scheme of the invention, the consistency of the cache can be maintained, the overlarge overhead is avoided, and the transmission of repeated data is reduced for the data transmission.

The application discloses an ophthalmic multi-source heterogeneous data fusion storage and cross-platform transmission method and device, computer equipment and a storage medium, and relates to the technical field of ophthalmic data processing. The ophthalmic multi-source heterogeneous data fusion storage and cross-platform transmission method and device, computer equipment and storage medium can collect data of different structures from various ophthalmic data sources, build a storage model and an interface, and realize the fusion storage of ophthalmic multi-source heterogeneous data. The seamless data transmission between different operating systems and various devices can be guaranteed. The ophthalmic data can be subjected to encryption processing, access permission setting and backup and recovery operation. The data flow and quality can be monitored in real time, and the system log can be effectively managed. The application can be integrated with a related big data analysis platform and an enterprise information system, solves the problems in the fusion storage and cross-platform transmission of ophthalmic multi-source heterogeneous data, and effectively improves the comprehensive utilization value of ophthalmic data.

The invention discloses an integrated acquisition system and an integrated acquisition method for a slowly-varying parameter and a rapidly-varying parameter, and solves the problems that when an existing Dewei acquisition system is used for acquiring the slowly-varying parameter and the rapidly-varying parameter in a rocket engine test scene, the acquisition efficiency is high; the technical problems of insufficient time synchronization precision of a slowly varying parameter and a rapidly varying parameter, low manual data fusion efficiency, easy introduction of human errors, tedious operation process and weak ability to adapt to a complex aerospace scene exist in the prior art. A parameter classification configuration module, a synchronous trigger control module, a time-sharing processing algorithm module and a fusion storage module are arranged in an upper computer carrying OXYGEN software, synchronous control of a DEWE3-RM16 master control unit and a DEWE3-RM16 slave control unit by adopting a clock can be realized, and the time deviation of a slowly varying parameter and a rapidly varying parameter is controlled within 1ms; and multi-parameter correlation analysis requirements of scenes such as airspace engine test run and spacecraft attitude control are completely met.

This invention provides a multi-source heterogeneous data fusion and storage system, including a control module, a data evaluation module electrically connected to the control module, a data analysis module electrically connected to the data evaluation module, a data integration module electrically connected to the data integration module, a data processing module electrically connected to the data processing module, a communication module electrically connected to the communication module, and a storage module electrically connected to the control module. This invention uses the data integration module to fuse and process data information, decompose the data information, determine its validity, and repair it. It also fuses data information based on data features, maps storage addresses, enabling the data to be queried through multiple methods and preventing storage redundancy.

The application provides an early warning customized service system based on cloud and local end cooperation, the system comprises: a basic resource layer for integrating cloud computing resources and local hardware resources; a data exchange layer for accessing multi-source heterogeneous meteorological data of satellite broadcast, international meteorological exchange system and local observation system; a digital base layer for cleaning, fusing, storing and managing the gathered data; an algorithm processing layer for identifying meteorological risks and generating early warning decision results; an integrated platform layer for encapsulating computing, data and algorithm capabilities as unified services; a business application layer for realizing comprehensive monitoring, forecast analysis and early warning information release based on the services. The application has the beneficial effects that through the cooperation and deep customization design of the cloud and the edge, the data transmission minimization, the on-demand utilization of computing resources and the efficient, flexible and accurate improvement of early warning capability are realized while ensuring the business continuity in extreme scenarios.

The application discloses a kind of deep learning dynamic weight adjustment methods applied to super-converged storage pool, belong to deep learning technical field, including the following steps: S1, create super-converged cluster, S2, create corresponding data pool according to proportion, S3, the use of each data pool in a period of time is collected, S4, the feature collected is trained and predicted using time series three-layer convolutional neural network.Utilize time series convolutional neural network in deep learning as the deep learning dynamic weight of super-converged storage pool provides adjustment scheme, weight adjustment is added to the storage cluster of super-convergence, while guaranteeing performance in controlling cost and diversity, through the prediction means of deep learning, data pool weight is dynamically adjusted in real time, data balance is strengthened, avoid weight excessive adjustment, standardized means is used to handle and obtain adjustment weight parameter, real-time prediction of user demand for different storage types is realized, meet the intelligent storage scheme.

The invention discloses a community cognitive weakness risk intelligent intervention system based on multi-source data fusion. The system comprises an intelligent data gateway layer which collects multi-source data through a household patient end APP, community screening equipment and a hospital medical system; the ontology and standardization mapping layer is used for mapping the intermediate data into a standardization concept entity defined in the domain ontology; the knowledge graph construction and fusion storage layer is used for constructing and storing a panoramic knowledge graph of the cognitive decline patient; the risk early warning module is used for calculating a risk level based on the standardized feature vector and triggering an alarm when the risk level reaches an early warning threshold value; the intelligent intervention module is used for carrying out unsupervised clustering analysis and outputting a crowd classification label, and a scheme generation engine carries out reasoning, matching and combination of standardized intervention components in a classification-intervention rule knowledge graph according to the crowd classification label and a risk level to generate a personalized intervention scheme; and the three-level joint control platform comprises a hospital end, a community end and a household patient end and is used for data sharing, feedback and early warning.

The application belongs to the technical field of databases, and specifically discloses an index column fusion storage method and system, which comprises the following steps: determining a target column, the target column being a data column in a column storage table configured with a PSort index, and the character length of the field type of the original data of the target column being greater than the character length of an index position identifier, the column storage table being a data table adopting a column storage mode, and the index position identifier being used for indicating the position of the original data in an index file; and configuring the field type of the target column as an index position identifier type, so that the index position identifier is stored in each row of the target column. Through the application, high-performance high-compression index column data fusion is achieved, and the disk space occupied by the data file and the index file can be reduced while the query efficiency is taken into account.

1. The name of the design product: super-converged storage management graphical user interface of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the present graphical user interface is used for the display of the super-converged storage management page, and the user can realize the corresponding function by clicking the corresponding control. 6. Other circumstances that need to be explained: "XX" in the interface represents replaceable text and / or numbers and / or letters and / or symbols.

The present application relates to the technical field of space launch monitoring, and in particular to a space launch data online acquisition monitoring system and method supporting multiple protocols, the monitoring system comprising a multiple protocol acquisition module, an address configuration module, a data preprocessing module, a real-time historical database storage module, and a process breakpoint monitoring module, the present application being applied to data acquisition monitoring of space launch processes, and capable of realizing real-time acquisition monitoring of data in various control systems and monitoring systems of space launches, solving the problems of heterogeneous data acquisition fusion, storage, processing, calculation and monitoring, being conducive to overall data analysis and early warning of tasks, realizing automatic start and stop of the whole process of the launch site, providing data support for subsequent intelligent unmanned operation of the launch site, and ensuring safe and reliable completion of tasks.

The application is suitable for the field of data storage, and provides an artificial intelligence-based data optimization storage method and system.The method comprises collecting and fusing real-time performance data of storage nodes and logical relationship data of a storage system to form multidimensional monitoring data flow; a candidate fault device presenting early degradation characteristics is identified through a pre-trained fault prediction model to generate a fault early warning signal; a physical topology and a logical dependency graph are constructed to deduce a data availability risk chain and an associated service influence chain caused by the fault; and an active defense strategy of data migration and access path adjustment is formulated and executed according to the risk chain.The application realizes early prediction and full-link risk prevention and control of storage faults, improves data availability and stability of the storage system, and promotes intelligent and active transformation of storage operation and maintenance.