902 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 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.

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 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 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 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 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.

The invention discloses a smart park energy management method and system, and particularly relates to the field of smart park energy distributed storage management, and the method comprises the steps: obtaining state data through collecting the energy state parameters of energy storage equipment, dividing the state data into equal-length time slices according to a time sequence, and storing the equal-length time slices; the power change rate, the load offset and the output difference value are counted in each equal-length time slice, and the statistical result is combined with the charging moment, the discharging moment, the power value and the write-in time to generate an operation record; according to the method, the charging power and the discharging power of the distributed energy storage equipment are uniformly planned according to the equal-length time slices, the scheduling matrix is constructed in combination with the capacity boundary condition, and the operation intentions of the equipment are synchronized before execution so as to quickly identify and eliminate the cross-node conflicts; therefore, the problems of energy exchange bus contention, storage queue blockage and log loss caused by a multi-autonomous-equipment parallel triggering strategy in a traditional scheme are solved.

The invention discloses a distributed medical image retrieval and hierarchical storage management system and method. The system comprises an interface processing module, a distributed image storage cluster, a routing forwarding module, a metadata management module and a storage management module. The interface processing module receives the image retrieval request, generates a routing identifier for positioning the storage position of a target medical image file and sends the routing identifier to the routing forwarding module; and the routing forwarding module queries a mapping relationship between the medical image file and the storage node and / or the storage hierarchy based on the routing identifier, determines a first storage node and forwards the request, so that the first storage node returns a target medical image file. And the storage management module obtains the access statistical information, determines a target storage level and / or a target storage node, migrates the medical image file, and triggers updating of the mapping relation after migration is completed. Therefore, cross-node accurate positioning and unified retrieval are realized, positioning consistency is kept after file migration, and hierarchical storage management based on access conditions is supported.

An illustrative data storage management system comprises a management database that stores administrative preferences and system configurations, as well as results and / or statistics of completed secondary storage operations, i.e., information needed by the system to protect customers' data and to track and recover the protected data, including secondary copies such as backup copies, archive copies, etc. The disclosed data storage management system is configured to protect its own system data subject to a very aggressive (short) Recovery Point Objective (RPO), by using an innovative infrastructure that enables the system's storage manager to fail over to any number of other failover destination storage managers, each one comprising a destination management database. An illustrative database granularly tracks whether each and every transaction log file has been successfully applied to each and every destination management database to synchronize with the source management database.

The invention discloses an AI Agent-assisted enterprise data analysis method and system, and relates to the technical field of data analysis, and the method comprises the steps: connecting an enterprise network switch, deploying an RS-485 management network, and deploying at least two AI Agent computing nodes at the edge side of the enterprise network switch; carrying out storage redundancy analysis to obtain a redundancy label matrix; establishing a distribution relationship; issuing a redundancy processing task according to the distribution relationship, and performing data processing to obtain a plurality of return data sets; and performing overlay storage on a metadatabase of the enterprise storage management center according to the plurality of return data sets. The technical problems that in the prior art, storage redundancy of an enterprise meta-database is difficult to recognize accurately, storage optimization after data processing is insufficient, and consequently enterprise data storage efficiency is low are solved, efficient redundancy processing and optimized storage of the meta-database of the enterprise storage management center are achieved, and the enterprise data storage efficiency is improved. And the technical effect of enterprise data storage efficiency is improved.

The invention relates to the technical field of aircraft health management, and discloses a system and a method for realizing aircraft health management. The method comprises the following steps: acquiring health data of each monitoring point on an aircraft and state information of each ground processing node; processing based on the data and information to obtain a target monitoring point cluster of each ground processing node; then health data sent by the target monitoring point cluster is subjected to preprocessing configuration, and cluster health data of all ground processing nodes are gathered after preprocessing and uploaded to a health database to-be-stored interface; and finally, synchronously acquiring operation data of each storage interface through a to-be-stored interface of the health database for analysis, and performing distributed storage management on the cluster health data. The method can provide a scientific basis for aircraft maintenance, effectively improves the safety, reliability and operation efficiency of the aircraft, reduces the operation cost, and has an important application value in the field of aircraft health management.

The invention relates to the technical field of key distribution, in particular to a multi-cloud architecture-oriented dynamic key fragmentation storage management method and system, which comprises the following steps of: dividing a manufacturing process of the manufacturing industry into a plurality of time sequence stages corresponding to different data access authority levels and security requirements, and constructing corresponding quantum state evolution operators; driving the key state to evolve among different time sequence stages through a quantum state evolution operator according to the progress of the manufacturing process, and adjusting the access authority of the key; quantum entanglement connection is established between supply chain nodes, the trust degree between the nodes is measured and quantized through the association of the quantum entanglement state, and the distribution weight of the key fragments is adjusted based on the change of the trust degree; collecting constraint parameters of production takt, equipment state, logistics delay and quality index in the manufacturing process, and converting the constraint parameters into quantum state constraint conditions; and when it is detected that the constraint condition changes, recalculating the key fragment distribution scheme based on the quantum state constraint condition and the credibility, and synchronously distributing the key fragment distribution scheme to each supply chain node.

The invention provides an authority management device and method adaptive to a heterogeneous access controller. The device consists of the heterogeneous access controller, an access management system and a user terminal, the heterogeneous access controller is provided with a calculation main control module, a communication module, an identity verification module, a permission execution module, a state acquisition module, a storage module and a power supply module; the access control management system is provided with a protocol adaptation management module, an authority engine detection module, a data storage management module and a user authentication management module; the user terminal is provided with a man-machine interaction module, an authority configuration module, an access control state monitoring display module and an alarm receiving module; the use method of the device comprises the following steps: installing the heterogeneous access controller, accessing other access controllers, performing authority configuration, communication debugging, controlling and managing the heterogeneous access controller and displaying and checking the working state of the heterogeneous access controller through the user terminal, so that the requirement of unified and centralized management of various different access controllers is met, and the system integration and maintenance cost is reduced.

The invention discloses an automatic control method and system for battery management, and belongs to the technical field of new energy storage management. The method comprises the following steps: firstly, obtaining state information of each battery of a battery pack, a park load and a current electricity price, and judging whether a charging or discharging starting condition is met; if the photovoltaic power is sufficient and the battery is not fully charged, starting photovoltaic charging, dynamically regulating and controlling the charging power, and stopping charging when the charging end standard is reached; and if the discharge starting condition is met, performing power dynamic distribution and real-time adjustment on the battery pack until the discharge ending standard is met, thereby realizing safe and efficient management of charge and discharge. According to the scheme, charging or discharging is automatically judged, photovoltaic charging is preferentially adopted when conditions are met, and the charging is stopped when the conditions reach the standard. And then judging whether to discharge according to the new state, and dynamically distributing power as required until the discharge is finished, thereby realizing automatic energy management of the battery pack.

The invention belongs to the technical field of big data processing and artificial intelligence, and particularly relates to a distributed efficient processing and intelligent analysis service system and method for mass big data. Comprising a distributed storage management layer, an intelligent metadata index layer, a task semantic analysis layer, an affinity perception scheduler, a multi-mode execution engine and a credible feedback control unit. High-affinity matching of tasks and data is realized by fusing data distribution perception, task semantic understanding and resource collaborative scheduling. According to the scheme, remote data pulling can be remarkably reduced, the scheduling efficiency and the resource utilization rate are improved, and collaborative efficient execution of multi-modal tasks such as streaming, graph calculation and AI reasoning is supported.

The invention relates to the technical field of storage space dynamic management, in particular to a storage space dynamic management system based on multi-source data fusion and intelligent optimization. Comprising a real-time data acquisition and fusion module, a dynamic demand prediction and visualization module, a multi-target dynamic optimization decision module, a scheme decision and instruction execution module and a closed-loop feedback and model updating module, the dynamic demand prediction and visualization module predicts demands based on the data set and generates a dynamic demand thermodynamic diagram, the multi-target dynamic optimization decision module constructs a multi-target goods allocation model and adaptively adjusts the weight to solve an optimal scheme set, and the scheme decision and instruction execution module selects a scheme and analyzes the scheme into an operation instruction; and the closed-loop feedback and model updating module forms a closed loop and updates the prediction model. According to the invention, dynamic intelligent optimization of the storage space is realized, the operation efficiency is improved, the management cost is reduced, and modern storage management requirements are met.

The invention provides a unified context and multi-level memory cooperation system and method for an LLM agent, and belongs to the field of artificial intelligence. The system comprises a unified context module which is used for aggregating and structuring all input information required for organizing agent operation, and providing an integrated context view for an LLM agent core; the LLM agent core is used for executing task planning, tool calling, result evaluation and response generation based on the context provided by the unified context module; and the multi-level memory system is connected with the unified context module and the LLM agent core and is used for hierarchically storing, managing and feeding back experience and knowledge of the agents. According to the method, the problems that an existing LLM intelligent agent is limited in context, low in memory efficiency and lack of self-correction capacity are solved, and the intelligent level and reliability of complex task processing are remarkably improved.

The embodiment of the invention provides a big data storage optimization method based on a zero-copy collaboration technology and related equipment, and belongs to the technical field of big data storage. The method comprises a zero-copy data transmission module used for directly writing a data stream into a front-end buffer area of an annular structure through a direct memory access technology, and adopting a zero-copy algorithm based on pointer offset to parallelly separate data of each channel in a multi-thread environment; the intelligent data reduction module is used for deleting duplicated data from the data and then compressing the duplicated data; and the hybrid storage management module is used for managing the hybrid partition storage architecture and dynamically adjusting the distribution of the data in the hybrid partition storage architecture according to the data access mode. The CPU copy frequency is reduced through the zero copy technology, the data transmission efficiency is remarkably improved by combining the data reduction and intelligent layering strategies, the occupied storage space is reduced, and meanwhile the data safety and compliance are guaranteed.

The invention discloses a multi-modal heterogeneous data management method and system, and the method comprises the steps: carrying out the preprocessing of multi-modal heterogeneous data, obtaining the preprocessing data, extracting the data information of the preprocessing data, carrying out the analysis, and determining the key data features of all data; evaluating the importance of each data based on the key data features to obtain an initial importance evaluation value; determining an association relationship among data in the preprocessed data from the data information, and constructing a knowledge graph of each data based on the association relationship; determining the position of each piece of data in the preprocessed data in the knowledge graph, and determining an evaluation value adjustment coefficient based on the position; and adjusting the importance initial evaluation value of each piece of data based on the evaluation value adjustment coefficient to obtain an importance evaluation value, and determining the storage position of each piece of data based on the importance evaluation value. According to the method, the final storage position is determined by carrying out importance evaluation on the data features of the multi-modal heterogeneous data, the data analysis and processing flow is optimized, and the efficiency and safety of data storage management are improved.

The invention discloses a vehicle software upgrading information management method and device, equipment and a program product, and relates to the technical field of information management. The method comprises the following steps: acquiring upgrading information of various types of vehicle software, the system comprises a software upgrading management system file, a software upgrading project process recording file, software upgrading configuration information and software upgrading compliance information. Vehicle type authentication information and first information sharing activity data generated inside a vehicle management party and second information sharing activity data generated between the vehicle management party and an external software upgrade related party in a vehicle software upgrade life cycle; carrying out storage management on the various types of vehicle software upgrading information; and in response to the consulting request for the at least one type of vehicle software upgrading information, generating a consulting record for the at least one type of vehicle software upgrading information. The management comprehensiveness of the vehicle software upgrading information can be improved.