1153 results about "Storage management" patented technology

The invention relates to the technical field of data processing and storage management, and discloses a multi-source index data intelligent storage management method and system, and the method comprises the steps: building a unified data integration and processing channel, and forming a standardized index data set; meanwhile, an enterprise-level index unified management system is established, and a credible index data set is generated; the credible index data set is stored through an optimized storage strategy and a data organization model, a data consanguinity association map is constructed based on data full-link processing, and visual and traceable index data assets are obtained; according to the method, a real-time quality evaluation engine is used for carrying out continuous monitoring and intelligent warning on all links of synchronization, processing, storage and service of an index data set so as to construct a data anomaly detection and repair mechanism, and quality controllable supervision is carried out on the whole processing process of the index data set through a data quality billboard and an anomaly processing workflow; therefore, the intelligent management level and the data quality guarantee capability of multi-source index data processing and storage can be improved.

The invention relates to a construction method and device of a network security knowledge graph, equipment and a storage medium, and the method comprises the steps: obtaining multi-source data of a network security application scene, and carrying out distributed processing to obtain a security data set; performing structured storage management and security knowledge extraction on the security data set to obtain an initial knowledge graph; performing zero-day attack prediction construction based on the initial knowledge graph to obtain potential attack data; performing path fusion association on the potential attack data and the initial knowledge graph to obtain attack chain fusion information; and obtaining real-time event data of the network security application scene, and carrying out dynamic iteration updating on the initial knowledge graph by using the real-time event data and the attack chain fusion information to obtain the network security knowledge graph. According to the invention, the timeliness and practicability of the network security knowledge graph can be ensured.

The invention discloses an intelligent data storage method based on a cloud platform, relates to the technical field of data storage management, and is used for solving the problem that cold and hot data identification is lagged. According to the method, the access behavior graph is constructed, the concurrent access coupling weight is calculated, the data object with high access frequency and deep path hierarchy is identified, the structure adjustment instruction is dynamically generated, the access link complexity and index hierarchy redundancy are reduced, the response delay and the popularity prediction error before and after the structure adjustment are combined, and the access efficiency is improved. According to the method, the scheduling efficiency of the hotspot data is improved, the adaptability to the change of a storage access mode is enhanced, the dynamic adjustment capability and the structure response performance are good, and the method can be used for realizing the closed-loop linkage of the access behavior perception, the structure reconstruction and the model optimization. Therefore, the method is more suitable for a large-scale data intelligent management scene under a cloud platform.

The invention discloses an unstructured storage hierarchical strategy optimization method based on machine learning, and relates to the technical field of data storage management, and the method comprises the steps: monitoring a file access event in real time, generating an access log, and extracting a multi-dimensional feature data set; utilizing the trained multi-dimensional decision tree model to distribute a corresponding storage hierarchy for the storage object to obtain a storage hierarchy decision; according to a storage level decision, distributing the storage objects to different storage layers, and carrying out resource configuration and storage operation; monitoring the access condition of the storage object in the new storage hierarchy in real time, and collecting file access performance, storage cost and response time to obtain feedback data; by monitoring the file access event in real time and extracting the multi-dimensional feature data set containing the basic attribute, the access behavior and the context information, efficient response of hotspot data and reasonable utilization of resources are ensured, and the overall performance utilization rate and the cost effectiveness of storage are remarkably improved.

A system and method for implementing a Persistent Cognitive Machine (PCMs) that extends beyond the traditional prompt-response paradigm of artificial intelligence are disclosed. A PCM maintains persistent cognitive processes regardless of external interaction, stores and organizes thoughts in a thought cache, retrieves relevant thoughts based on current stimuli, generates new thoughts through reasoning processes, and curates stored thoughts during periods of reduced external interaction. The PCM includes language and reasoning model components, a thought cache, an executive component, and an embedding system. The PCM remains continuously active, remembers previous experiences, learns from these experiences, creates new thought experiences independently, and initiates interactions without waiting for external prompts. The PCM enters sleep-like states during which it curates its thought cache, generalizes experiences, and performs other memory management functions. Applications may include but are not limited to synthetic cognitive colleagues, strategic war gaming platforms, and personal cognitive assistants.

The invention relates to the field of heterogeneous data storage, in particular to a heterogeneous data storage method and system for a civil aviation data platform, and the method comprises the steps: collecting metadata of each subsystem in the heterogeneous data storage system in real time, inputting the metadata into a pre-constructed metadata unified model, and carrying out standardization processing to generate a global metadata view; establishing a data traceability tracking mechanism according to the global metadata view, and mapping dispersed metadata items and data entity operation records according to the data traceability tracking mechanism to generate a traceable metadata change track; and a metadata quality label is embedded in the metadata unified model, a metadata knowledge graph is constructed according to the metadata change track and the metadata quality label, and a resource allocation strategy of the heterogeneous data storage system is dynamically optimized according to an analysis result of the metadata knowledge graph. The problem of low storage management efficiency caused by difficulty in integrating and tracing metadata in a heterogeneous data storage system in civil aviation data is solved.

The invention discloses an AI-based distributed big data intelligent storage management method, and relates to the technical field of storage management. The method comprises the steps of generating an initial feature matrix by obtaining observation data of all storage devices in a distributed storage cluster, and inputting the initial feature matrix into a pre-training life prediction model to obtain residual life; equipment with the service life lower than a first safety threshold value is judged as high-risk equipment, and data of the high-risk equipment is included in a to-be-migrated source data set; the devices with the service life higher than a second safety threshold value are included into a to-be-migrated target device set; and generating a migration plan according to the source and target data sets and executing migration. By predicting the residual life of the equipment, advanced identification and active data migration of the high-risk equipment are realized, the data loss risk is reduced, and the utilization rate of the health equipment and the overall cluster storage resource efficiency are improved.

The invention relates to the technical field of system application, and discloses an online document processing method and system based on structured storage, and the method comprises the steps: splitting content elements of an online document into blocks, and carrying out structured storage as independent objects; querying basic information of the document, loading data according to a document block pageBlockId list, creating a component according to the loaded data, constructing a component tree, and performing document rendering by using a lazy loading technology; the method comprises the following steps: abstracting documents and document blocks as objects, synchronizing the objects to a graphic database, modeling a relationship between the documents and the document blocks as an edge in the graphic database, and converting the relationship between the documents into a graphic data structure; when the document content changes, the storage interface is called to store the changed document block, and the online document is automatically stored, the document content is structurally stored in the block form, dynamic updating of the online document is achieved, the reference relation between the documents is stored and managed, and the relation between the documents is visually and clearly displayed.

The invention discloses a simulation data management method based on a servitization integrated architecture, and relates to the technical field of combat simulation and deduction, and the method comprises the steps: building a servitization integrated data management architecture according to a data collection layer, a data storage layer, a data management layer, a data management layer and a data service layer; based on a service integrated data management architecture, data standardization is carried out, a data model is designed, data fusion preprocessing, data integration and data analysis are carried out on collected multi-source heterogeneous data according to a data standard and the data model, data fusion and warehousing management are completed, and meanwhile balance and unification of data security and sharing are guaranteed. According to the invention, a one-stop and all-around data management solution can be provided for simulation application.

The invention discloses a lightweight block chain node consensus mechanism optimization method, and relates to the technical field of block chains. According to the method, the computing power of the lightweight nodes is accurately evaluated through a hierarchical verification aggregation algorithm, efficient participation of the lightweight nodes in a resource-constrained environment is realized, a transaction set is divided into a plurality of subsets by adopting a transaction verification fragmentation strategy, and verification results are aggregated by utilizing a Merkel tree aggregation verification technology; in addition, a dynamic storage management strategy is established, the depth of locally stored historical data is dynamically adjusted according to the node storage capacity, and network storage and retrieval are performed through a distributed hash table; the bottleneck problem of storage and network transmission is effectively solved, and the network bandwidth utilization efficiency and the storage management flexibility are improved.

This disclosure describes a large language model (LLM)-based agent operating system comprising an application layer, a kernel layer, and a hardware layer. The kernel layer comprises an AIOS kernel comprising: LLM core(s), an agent scheduler, a context manager, a memory manager, a storage manager, and a system call interface configured to manage interactions among the agent scheduler, the context manager, the memory manager, and the storage manager.

The invention provides a coal mine multi-source waste heat intelligent utilization system and method based on cross-seasonal heat storage, and relates to the technical field of coal mine waste heat utilization, and the system comprises the steps that a heat prediction module monitors and obtains a plurality of historical redundant heat sequences of a plurality of coal mine waste heat sources, and carries out heat prediction in a preset time window; a heat supply demand prediction module reads the heat use characteristic sequence and the associated heat use characteristic sequence and performs heat supply demand prediction; a heat storage scheme optimization module performs heat storage scheme optimization and outputs an optimal heat storage proportion sequence by taking a heat supply quantity sequence meeting a predicted demand as a conditional constraint, taking the maximum capacity of heat storage equipment as an equipment constraint and taking the minimum heat loss as a target; and the heat storage management and control module executes heat storage management and control in a preset time window according to the optimal heat storage proportion sequence. The technical problem that in the prior art, waste heat cannot be effectively stored can be solved, the technical target of intelligent regulation and control system construction is achieved, and the technical effect of improving the waste heat utilization efficiency is achieved.

The invention provides a storage system for immunofluorescence slide glass and an intelligent temperature and humidity coupling control method thereof. The system comprises a closed sample cabin, a controller, a passive buffer layer and other structures, and the temperature and humidity in the cabin can be stably controlled in a dynamic environment. The temperature and humidity in the cabin and the temperature of the key cold surface are monitored in real time through the sensing unit, the local dew point is calculated, and temperature and humidity control is executed. And the controller executes a layered gradient coupling control algorithm according to the dynamic dew point safety margin to ensure accurate control of temperature and humidity. The passive buffer layer is of a composite structure of a phase change material and a moisture absorption material, and the temperature and humidity are adjusted through solid-liquid phase change and molecular adsorption. The system can effectively improve the storage stability and safety of the immunofluorescence slide, and is suitable for sample storage management in industries such as life science and biological pharmacy.

The invention provides a deep learning communication operator data processing method and system and artificial intelligence computing equipment, and relates to the technical field of deep learning. The method comprises the following steps: under the condition that a processor core is started, distributing a target storage space for a temporary array of a plurality of threads in an on-chip shared memory; under the condition that a plurality of threads execute data processing in parallel, initializing a temporary array data area allocated by each thread in the target storage space; under the condition that a plurality of threads are processed in parallel and distributed to respective input data units, distributed calculation processing is carried out on the temporary array corresponding to each thread according to the input data units, and a temporary array calculation result corresponding to each thread is obtained; and performing reduction processing on the temporary array calculation result to obtain a global statistical result corresponding to the plurality of threads. According to the embodiment of the invention, by optimizing the storage management and parallel processing flow of the temporary array, the execution efficiency of a communication operator and the overall throughput of the system can be remarkably improved.

The invention relates to the technical field of data storage, in particular to an enterprise financial data security storage management system and method based on the Internet of Things. The method comprises the following steps: acquiring an enterprise financial data transmission log based on the Internet of Things, and performing data cache chain node trust anchoring to obtain trust authentication equipment data; according to the data of the trust authentication device, analyzing a hop trust transmission node to obtain a hop trust transmission map; performing structured enhancement by using the trust authentication device data to obtain to-be-encrypted bill data; chain side security consensus packaging is carried out on the to-be-encrypted bill data to obtain a verifiable consensus block; performing multi-label traceability control filing on the verifiable consensus block to obtain a traceability label filing body; and performing jump point transmission on the traceability label archive body to an enterprise private database by using the jump point trust transmission map so as to execute a data archiving task. According to the invention, the stability and security of enterprise financial data storage are significantly enhanced.

The invention provides a storage device, a storage method and a storage access method based on lake and warehouse integration. The storage device comprises a storage management unit, a unified metadata management unit and a federal query engine unit, the storage management unit is used for realizing hybrid storage and dynamic hierarchical storage; the unified metadata management unit is used for metadata atlas construction, concurrency control and GDPR compliance support; the federal query engine is used for intelligent routing decision, SQL dialect unification and intelligent push-down optimization; based on a lake and warehouse integrated storage device and an access technology thereof, unified management of structured and unstructured data is supported, the problem of data islands is avoided, and cross-engine data visibility is realized through unified metadata management; according to the lake and warehouse integrated storage device and the access method, technologies such as a dynamic hierarchical storage strategy, intelligent routing decision, intelligent push-down optimization and the like are fused, and the storage and access efficiency and the robustness of the system are greatly improved.

The invention relates to the technical field of file storage management, and discloses a Lustre architecture-based high-performance file storage and processing method and system, the method comprises the following steps: obtaining spatio-temporal characteristics of file access; predicting a popularity value of the file based on the spatial-temporal characteristics; determining a storage strategy of the file based on the popularity value of the file; carrying out distributed storage on the file based on the storage strategy, and continuously detecting a node state; if it is detected that the node load is unstable, adaptive data migration is carried out on the node with the unstable load; if the node is detected to have a fault, generating a data recovery path based on the three-dimensional topological coordinates of the node, and migrating a file stored in the node having the fault based on the data recovery path; according to the method, the storage strategy is determined through the file popularity value, and the abnormal condition of the node is efficiently processed, so that the file storage and processing performance and efficiency are comprehensively improved.

The embodiment of the invention provides a storage strategy optimization method and device based on data popularity and data consanguinity, and dynamic optimization of a storage strategy is realized through innovatively designing a multi-dimensional popularity calculation model and through node attribute analysis and a graph attention network. A directed graph structure is constructed, and a reliable dependency relationship management system is established in combination with blood relationship analysis. A hierarchical storage strategy is introduced, and the storage efficiency is ensured through heat division and dependency relationship optimization. According to the method, the defects of the traditional technology in the aspects of popularity evaluation, blood relationship analysis, storage optimization and the like are effectively overcome, and a technical guarantee is provided for software system storage management.

The invention discloses a storage management method, system and device of a goods frame and a medium. The method comprises the steps of obtaining first product data of a first waste electronic product in a to-be-stored goods frame, second product data of a second waste electronic product in a target goods frame on a target goods shelf, environment data of the target goods shelf and to-be-stored position data of each to-be-stored position in the target goods shelf; generating a first risk category label based on the first product data, and generating a second risk category label based on the second product data; determining a storage conflict index of the to-be-stored goods frame and the target goods frame; calculating a storage adaptation score of the to-be-stored goods frame at each to-be-stored position and determining a to-be-stored position set; determining a storage and transportation path set of each to-be-stored position; determining an electrostatic induction interference intensity distribution sequence and a magnetic interference intensity distribution sequence of each storage transportation path; and determining a target storage and transportation path of the to-be-stored goods frame. The reliability of goods frame storage can be improved.

The invention discloses a fruit and vegetable storage and fresh-keeping control management system and method based on full-period detection, and relates to the technical field of fruit and vegetable storage management, and the method comprises the following steps: dividing a fruit and vegetable storage period into an initial fruit and vegetable storage period, a stable storage period and a later fruit and vegetable storage period; setting a storage environment fluctuation detection mechanism for judging whether storage environment leakage occurs or not according to the environment fluctuation degree; setting a storage environment leakage risk analysis mechanism for dynamically adjusting the time interval of data detection; setting a fruit and vegetable storage and detection period adjusting mechanism for adaptively adjusting the period duration of a stable storage period and the time interval of storage environment detection; the timeliness and accuracy of abnormal fluctuation detection are improved, so that the damage of storage environment fluctuation to the physiological state of fruits and vegetables is reduced; the duration of the stable storage period and the time interval of storage environment detection are adaptively shortened, and the problem that the rotting rate of fruits and vegetables in the later period is too high due to the fact that a fixed storage period is selected is solved.

The invention discloses an intelligent computing center data security protection method and system based on a computer network, and relates to the technical field of network data security protection. Comprising a data classification identification module, a data encryption and fragmentation module, a distributed storage management module, a network attack detection and defense module, a data integrity verification and recovery module, a security policy optimization module, a security situation awareness module and a central control module. The distributed storage management module records storage positions, hash values and access permissions of data fragments based on the block chain technology, the distributed storage management module dynamically adjusts the access permissions of storage nodes, node access is only allowed to be achieved through multi-factor authentication of fingerprints and digital certificates, the data streams are fragmented and then encrypted, and therefore the data streams are encrypted, the data streams are encrypted, and the access permission of the storage nodes is dynamically adjusted. And the data is obtained by reading the storage position, the hash value and the access permission, and the access permission of the storage node is dynamically adjusted, so that the data security can be ensured while the data can be conveniently accessed.

The invention provides an intelligent storage location optimization method and system, and belongs to the technical field of storage management, and the method comprises the steps: obtaining the data information of commodities in a storage system, constructing a storage location optimization model, comprising a comprehensive objective function taking maximization of space utilization rate and sorting efficiency and minimization of storage cost as objectives and constraint conditions based on physical rules and business rules; solving the storage location optimization model by using an optimization algorithm, and generating a storage location distribution scheme and prediction performance data; executing the storage location allocation scheme, and collecting actual storage location data and actual operation performance data; comparing the actual storage location data with the storage location allocation scheme to obtain a scheme execution coincidence rate; comparing the actual operation performance data with the predicted performance data to obtain a performance deviation rate; and based on the scheme execution coincidence rate and the performance deviation rate, adjusting the constraint condition of the storage location optimization model and / or the weight coefficient of the comprehensive objective function to obtain an updated storage location optimization model, and carrying out storage location allocation.

The invention belongs to the field of computer system structures and artificial intelligence accelerators, and discloses a software and hardware collaborative heterogeneous storage computing accelerator oriented to full-chip DLRM reasoning. A control domain composed of a static random access memory and an embedded dynamic random access memory, an on-chip storage domain, an in-memory computing domain and an on-chip computing domain are integrated in the same chip, an embedded table is compressed by introducing a hierarchical clustering quantization frame, and a dynamic storage management strategy of access frequency perception is combined. The embedded access path is shortened, and the bandwidth requirement is reduced. According to the method, the reasoning process of the whole set of DLRM can be independently completed, and the memory access overhead in a traditional terminal SoC is remarkably reduced by reducing cross-domain data migration between the calculation unit and the storage unit, so that the model reasoning performance and energy efficiency are improved.

The invention relates to the technical field of industrial robot data acquisition and transmission, in particular to a welding robot behavior recording system integrating edge acquisition and cloud management, which comprises the following modules: an edge end data acquisition module for acquiring the state of a welding robot and sensor data in real time, and performing time alignment and validity processing, generating edge end data; the data preprocessing module is used for optimizing the edge end data and unifying the data format to form preprocessed data; and the local storage management module is used for carrying out hierarchical storage and index management on the preprocessed data according to the data access frequency and importance. According to the invention, through a breakpoint continuous transmission mechanism of cooperation of the edge end and the cloud end, fragmentation and recording of the transmission progress in the data transmission process are realized, continuous transmission is only performed on the uncompleted fragmentation after the network is interrupted, meanwhile, sorting and integrity verification are performed on the received fragmentation at the cloud end, and reliable uploading of large-capacity data in a complex network environment is realized.

The described technology pertains to a distributed computing environment, specifically implementing a streaming protocol on a scalable object storage service. The technical problem addressed is the high computing resource demand of distributed streaming platforms. The solution involves separating content from location metadata, allowing centralized, scalable storage of metadata. Brokers store content in object storage services based on specific metrics, such as fast read / write times or greater storage capacity. A background platform remaps metadata sequences based on logical timestamps, optimizing data retrieval. This system enhances the efficiency of computing resources by reducing the load on brokers and improving data access speeds. A use can be in cloud computing systems for efficient content streaming and storage management.

A system and method for privilege assurance protection of computer networks that remedies the deficiencies of the current directory service structure. The system uses a software agent to collect and store snapshots of all network resources on a computer network by identifying network domains, searching the directory service of each domain for network resources, and periodically querying the network resources for changes. The software agent communicates with a backend server which provides searching, querying, storage, administrative and other functionality to the agent via remote procedure calls.

The invention discloses a stereoscopic warehouse goods allocation intelligent binding system and method, and relates to the technical field of stereoscopic warehouse storage management. Comprising the following steps: S1, creating a two-dimensional electronic map of a warehouse, establishing a two-dimensional coordinate system of the warehouse, and based on the two-dimensional coordinate system and shelf positions, establishing coordinates of each shelf by taking a warehouse-out station position as a coordinate origin; s2, the RFID tag is installed at the preset position of the first layer of storage location of each goods shelf, and the coordinates of the goods shelf where the RFID tag is located are pre-stored in each RFID tag; by integrating the advanced navigation technology, the AI intelligent decision-making system and the multi-mode interaction unit, accurate and efficient binding of the goods locations of the stereoscopic warehouse is achieved. The system not only fully considers the three-dimensional space characteristics of the warehouse, but also combines the multi-dimensional factors such as dynamic heat and seasonal demand change of the goods, so that the goods allocation is more scientific and reasonable, and compared with the prior art, the system can dynamically adjust the goods allocation strategy according to the real-time demand.

The invention provides a geoscience specimen digital acquisition and management system, and relates to the technical field of geoscience specimen acquisition, and the system comprises a data acquisition module which collects specimen attribute fields, specimen photos and process metadata; the data quality evaluation module is used for performing bidirectional modulation on the basic weight based on the dependency relationship set of the fields to obtain an effective weight, and calculating an integrity score based on the effective weight; calculating an accuracy score, a specification degree score and a timeliness degree score; calculating to obtain a comprehensive quality score; the data optimization suggestion module is used for generating an optimization suggestion according to the score of each dimension and the score of the comprehensive quality; and the data storage management module is used for storing specimen attribute fields, specimen photos, process metadata, quality evaluation results and optimization suggestions. According to the method, the quality problem can be recognized in time, targeted optimization suggestions can be automatically generated, and intelligent priority recommendation is provided for field acquisition based on historical quality statistical data, so that the quality and efficiency of geoscience specimen data acquisition are improved.

The invention discloses a lightweight spliced bridge vibration monitoring system for cooperative work performance intelligent perception, and belongs to the technical field of bridge structure health monitoring, and the lightweight spliced bridge vibration monitoring system comprises a lightweight targeted sensing subsystem which comprises a plurality of perception assemblies arranged in a targeted manner; the intelligent edge acquisition and transmission subsystem has an independent addressing function and a time synchronization function and is used for preprocessing and lightweight processing; the cloud edge collaborative storage management subsystem performs hierarchical storage, security control and efficient retrieval on the data to form monitoring data; and the cooperative performance perception early warning subsystem realizes state evaluation and graded early warning of the cooperative work performance of the spliced bridge through multi-index fusion. By adopting the lightweight spliced bridge vibration monitoring system for cooperative work performance intelligent perception, the problems of insufficient lightweight and targeting performance, low data processing, transmission and storage efficiency, and inaccurate cooperative performance evaluation, damage positioning and early warning of traditional spliced bridge vibration monitoring are solved.

The invention relates to the technical field of energy storage Internet of Things and digital twinning, in particular to a digital twinning model data processing method applied to the energy storage Internet of Things, which performs multi-modal data synchronous acquisition through a three-in-one sensor, optimizes storage management through a dynamic cache allocation mechanism, and improves the reliability of data acquisition through the three-in-one sensor. Micro short circuit and voltage unbalance detection is completed through high-frequency harmonic extraction and difference frequency voltage scanning, the event cross trigger establishes a bidirectional feedback mechanism, and the lightweight decision tree verifier outputs a fault code. According to the digital twinborn model data processing method applied to the energy storage Internet of Things, the early detection sensitivity of micro short circuit and voltage imbalance is high, outdated redundant calculation is avoided, parameter configuration is optimized through a periodic diagnosis report, different conditions are flexibly adapted, and support is provided for an intelligent health management system of energy storage equipment.