29731results about "Input/output to record carriers" patented technology

The invention discloses a geographic information big data-oriented multi-source data processing system, and relates to the technical field of data acquisition and sensors, and the system comprises a data acquisition module which accesses a remote sensing satellite, an unmanned aerial vehicle, an Internet of Things sensor and social media in real time through a multi-source heterogeneous interface, and carries out the adaptive analysis of a data format and metadata marking; the distributed storage module is used for performing partition storage on the geographic information data based on a space-time database and an object storage architecture, and establishing dynamic space-time index and version control; the data fusion module is used for realizing coordinate system conversion, time sequence calibration and semantic knowledge graph matching based on a multi-source data alignment method of dynamic weight distribution; and an intelligent analysis module and a security control module. According to the method, core pain points such as data splitting, low storage efficiency, extensive analysis and compliance risks in the geographic information field are systematically solved, and a full-stack type technical base is provided for scenes such as smart cities, emergency disaster relief and environment monitoring.

The invention discloses an optical fiber data storage management system and method based on big data, and relates to the technical field of storage management. According to the optical fiber data storage management system and method based on big data, the spatial-temporal characteristics of the historical access records are extracted through the LSTM network, the data heat value is calculated in combination with the time decay function, and the thermal distribution diagram of the data blocks is generated. And based on the thermal distribution map, constructing a storage resource allocation model by using a deep reinforcement learning algorithm, and dynamically adjusting the optical path priority and copy distribution. A data prefetching strategy is optimized through the spatio-temporal joint index and the vector similarity index, and a high-frequency data cache index distribution diagram is generated. And comprehensively considering the data access delay, the index hit rate and the copy migration frequency, obtaining an optical fiber storage efficiency index, and adjusting a storage strategy according to the index. According to the method, the dynamic scheduling and utilization efficiency of data storage resources is effectively improved, the data access delay is reduced, the copy management is optimized, and the overall performance of a storage system is remarkably improved.

A data storage system can implement a key-value engine configured for tunable read, write, and space amplification. The key-value engine can support multi-versioning, synchronous and asynchronous key updates, and read snapshots. The key-value engine is highly scalable and can support generalized parallel, in-memory computation. Experimental results demonstrate that a key-value engine consistent with disclosed embodiments can outperform a state-of-the-art production LSM-based key-value store in a wide range of metrics.

Apparatuses, systems, and methods for managing access to metadata stored at a memory. To manage access to metadata, a mode register is configured to receive a metadata enable setting and to provide a metadata enable signal based on the metadata enable setting. A metadata access control circuit configured to receive a column address identifying a particular column to be accessed within a memory array. The metadata access control circuit blocks access to a column corresponding to the column address when the column address matches one of a plurality of particular column addresses designated for storage of metadata and the metadata enable signal has a first value, and permits access to a column corresponding to the column address when the column address is different than every one of the a plurality of particular column addresses designated for storage of metadata or the metadata enable signal has a second value.

Apparatuses, systems, and methods for bounded fault compliant metadata storage. A memory module may be capable of repairing information along a portion of the data terminals of a memory device. To prevent errors in the metadata from propagating across more than the correctable portion, the metadata may be provided along a portion of the data terminals, while the data associated with that metadata is provided along more data terminals. For example, in a 9×2p2 module the data may use two terminals, while the metadata only uses one. In a 5×2p4 module, the metadata may use a pair of terminals, while the data uses four.

Apparatuses, systems, and methods for managing access to metadata stored at a memory. To manage access to metadata, a mode register is configured to receive a metadata enable setting and to provide a metadata enable signal based on the metadata enable setting. A metadata access control circuit configured to receive a column address identifying a particular column to be accessed within a memory array. The metadata access control circuit blocks access to a column corresponding to the column address when the column address matches one of a plurality of particular column addresses designated for storage of metadata and the metadata enable signal has a first value, and permits access to a column corresponding to the column address when the column address is different than every one of the a plurality of particular column addresses designated for storage of metadata or the metadata enable signal has a second value.

Apparatuses, systems, and methods for half-page modes. A memory device may be operated in a full-page mode where all the memory cells along a word line are used for data or a half-page mode where less than all of the memory cells are used for data. In some memory devices, each half of the memory cells may be separately activated by different word line portions. In some half-page modes, data may be stored along a selected portion of the memory cells and additional information such as metadata or module parity may be stored along the non-selected portion of the memory cells. The additional information may be provided along additional data terminals so as not to increase the data burst length.

The invention relates to the technical field of data processing, and discloses a multilevel cloud storage cluster construction and data storage method. The method comprises the steps that S1, multiple levels of storage layers are constructed and comprise a cache layer, a performance layer and a capacity layer, and the storage layers are provided with different storage media which are used for storing hot data, warm data and cold data respectively; s2, determining data popularity by monitoring data access frequency, access time interval and data importance; and S3, dynamically adjusting the storage hierarchy of the data according to the data popularity, and triggering hierarchical migration of the data. By constructing a multi-level storage layer and adopting a hierarchical architecture that the cache layer stores high-frequency data, the performance layer stores intermediate-frequency data and the capacity layer stores low-frequency data, high-heat data is preferentially stored in a high-performance medium, access delay is reduced, and data reading and writing efficiency is improved. Meanwhile, in combination with a dynamic data migration strategy, the storage position can be adjusted in real time according to the data access popularity, and the overall performance of the system is further optimized.

The embodiment of the invention discloses a data distributed storage method and device, and the method comprises the steps: carrying out the fragmentation processing of to-be-stored data, and obtaining an initial fragmentation result; utilizing a reinforcement learning model to perform popularity prediction on the data fragments according to the historical access data to obtain the access popularity of the data fragments; determining the number of copies based on the access popularity and importance of the data fragments, generating fragment copies of the data fragments according to the number of the copies, and storing the data fragments and the fragment copies into storage nodes according to the access popularity and node load state scores; when the loads of the storage nodes are unbalanced, data migration is carried out on the data fragments stored in the storage nodes, and when the node health state of a certain storage node is abnormal or the stored data fragments are lost, data reconstruction is carried out on the data fragments stored in the storage node. According to the method, the problems of non-uniform access load, resource waste, data loss and the like in a distributed storage system can be relieved.

A memory device can be coupled to a host device using a compute express link (CXL) interconnect. The memory device can include a host interface circuit and processing logic circuitry, such as a subsystem manager circuit. The host interface circuit of the memory device can be configured to operate in one of an autonomous mode and a distribution mode. In the autonomous mode, the host interface circuit is configured to maintain a connection between the host device and the memory device while the subsystem manager circuit of the memory device is unavailable, such as when the subsystem manager circuit undergoes a reset routine. In the distribution mode, the host interface circuit is configured to allow communication between the host device and the subsystem manager circuit of the memory device.

Techniques discussed herein relate to improved data recovery techniques within cloud computing environments. The disclosed techniques utilize consistency groups that are identified for volumes corresponding to a compute instance. A plurality of resource identifiers uniquely identifying a respective cloud computing resource of the cloud computing environment can be maintained. A cloud computing instance corresponding to a resource identifier may be identified and volume metadata associated with that resource identifier is obtained. The volume metadata identifying at least one of a block volume or boot volume. A consistency group is generated for the identified volume devices for the computing instance and one or more schedules can be generated with which various snapshots of the volume devices of the group are to be subsequently generated.

The invention relates to the technical field of computer storage, in particular to a multi-level cache management method, system and equipment for solid-state storage equipment and a medium. The method comprises the following steps that multiple layers of caches are configured in the solid-state storage device and comprise a high-speed cache layer, a medium-speed cache layer and a low-speed cache layer, and each layer of cache has different access speeds and capacities and is used for storing data blocks with different priorities and access frequencies; dynamically scheduling the data blocks to a proper cache layer through a cache allocation algorithm according to the real-time access frequency, size, life cycle and importance of the data blocks; establishing a comprehensive data block priority evaluation model, and calculating a priority score of each data block; according to the multi-level cache management method, by configuring the multi-layer cache, the priority evaluation model and the multi-path scheduling mechanism, dynamic scheduling and load balancing of the data blocks among different cache layers are achieved, and the overall efficiency of data access is improved.

The invention discloses a big data stream-oriented memory cache storage system, relates to the technical field of memory cache storage, and is used for solving the problem of poor memory cache storage management. According to the method, the access frequency, the timeliness and the service importance of the data are evaluated, the priority ranking model is constructed, the cache strategy is optimized based on the ranking result, the data storage and scheduling efficiency is improved, the write-in and read operation of the memory cache is adjusted in real time in combination with the flow prediction model, memory overload is effectively avoided, and the data storage and scheduling efficiency is improved. According to the method, non-emergency data writing is delayed by adopting a delayed writing and lazy loading strategy, data is loaded as required, meanwhile, a cache elimination mechanism is designed according to data priority, access frequency, survival time and size, data migration is carried out when a cache space is insufficient, reasonable resource allocation is ensured, and through a multi-level and dynamic cache management scheme, the cache management efficiency is improved. Therefore, the system performance, the resource utilization rate and the response speed are remarkably improved, the data processing efficiency is optimized, and cache conflicts are reduced.

Techniques are described for monitoring and analyzing input / output (I / O) messages for patterns indicative of ransomware attacks affecting computer systems of a cloud provider, and for performing various remediation actions to mitigate data loss once a potential ransomware attack is detected. The monitoring of I / O activity for such patterns is performed at least in part by I / O proxy devices coupled to computer systems of a cloud provider network, where an I / O proxy device is interposed in the I / O path between guest operating systems running on a computer system and storage devices to which I / O messages are destined. An I / O proxy device can analyze I / O messages for patterns indicative of potential ransomware attacks by monitoring for anomalous I / O patterns which may, e.g., be indicative of a malicious process attempting to encrypt or otherwise render in accessible a significant portion of one or more storage volumes as part of a ransomware attack.

The invention provides a data all-flash storage optimization method and system based on cloud computing, and the method comprises the steps: receiving a storage operation request stream of a user terminal through collecting a multi-dimensional performance data set of each node of an all-flash storage cluster in real time, wherein the multi-dimensional performance data set comprises a storage space fragmentation rate, an input / output request queue depth and a network link bandwidth utilization rate; analyzing a to-be-stored data block identifier set and an operation mode label, traversing a historical access record library based on to-be-stored data block identifiers, extracting historical access time sequence characteristics and physical storage position proximity of associated data blocks, and combining the multi-dimensional performance data and the historical access time sequence characteristics to obtain a data block identifier set; according to the method, a dynamic access popularity prediction model in a preset time period is constructed, and finally, a cross-node fragmentation storage topological graph and a cache preloading strategy matrix are generated according to the proximity of the dynamic access popularity prediction model and a physical storage position, so that the optimization of all-flash storage is realized, and the data storage performance in a cloud computing environment is improved.

The invention relates to the technical field of big data storage, in particular to a storage control method and device based on big data. The method comprises the following steps: acquiring an original data stream and application demand information; performing data dynamic correlation analysis on the original data flow according to the application demand information to obtain a dynamic update data correlation graph; performing feature vector generation on the dynamic update data association graph to obtain a data feature vector; performing intelligent quality evaluation on the data feature vector to obtain a data quality label; performing timeliness evaluation according to the data feature vector, and performing access popularity evaluation to obtain a timeliness score and an access popularity score; and acquiring system resource load condition information. The storage resource utilization rate, the data access performance and the overall efficiency of the system are improved by solving the limitation of a traditional method in the aspects of static data management and resource allocation.

The invention relates to the technical field of hard disk monitoring, in particular to a health monitoring method and system for a solid state disk. The method comprises the following steps that multi-dimensional monitoring data collection is conducted on a storage unit of the solid state disk, standard multi-dimensional monitoring data are generated, and the standard multi-dimensional monitoring data comprise S.M.A.R.T attribute data, temperature sensor data, programming erasure delay data and power supply voltage ripple data; performing timestamp synchronization on the programming erasure delay data by using the power supply voltage ripple data, and performing electron tunneling current waveform analysis on the programming erasure delay data and the power supply voltage ripple data according to the synchronized timestamp to generate charge trap health index data; extracting the number of bad blocks of the S.M.A.R.T attribute data; through multi-dimensional data acquisition, accurate synchronization, accurate degradation modeling and intelligent self-repairing strategies, the reliability and accuracy of health monitoring of the solid state disk are improved.

The invention relates to the technical field of data storage and processing, in particular to an RAID card static cache management method and device based on data popularity, and the method comprises the steps that the physical position of a data block needing to be accessed in an SSD array is acquired according to a read-write request; historical data access information of the RAID card is collected, a historical data set is generated, and a neural network model is trained by using the historical data set to obtain a cache management model; predicting and outputting data blocks which are possibly accessed in the future and the access probability of the data blocks through the cache management model; the RAID controller dynamically adjusts a cache strategy in combination with an LRU strategy according to a prediction result output by the cache management model and a read-write request of a file system, and optimizes a storage position and an updating mechanism of a data block in a cache space; and when the hit rate or the data access efficiency does not reach the preset value, adjusting the parameters of the cache strategy and updating the cache strategy. According to the method, cache resources can be more effectively distributed, the cache hit rate is improved, the cache replacement overhead is reduced, and therefore the performance of a storage system is optimized.

The present invention relates to a data interaction method, device, equipment and storage medium of a multi-layer stacked memory, comprising the following steps: based on the access frequency clustering result, the target transmission data is mapped to a storage location to obtain a multi-layer storage allocation strategy table; based on the multi-layer storage allocation strategy table, the target transmission data is interactively planned to obtain an optimal interactive path plan; based on the optimal interactive path plan, the target transmission data is hierarchically migrated and scheduled to obtain a data migration execution queue; and the data migration execution queue is transmitted in parallel through an asynchronous pipeline transmission mechanism, which solves the technical problem that the existing data transmission strategies often lack in-depth analysis of the historical access characteristics of the storage hierarchy, resulting in unreasonable data distribution, and frequent cross-level data migration increases system delay and energy consumption.

The invention discloses a multi-level storage control method based on access popularity, and relates to the technical field of information, the method comprises the following steps: building a storage resource monitoring module, and collecting data volume change, read-write frequency and capacity occupation proportion information of each node from a storage system in real time; the method comprises the following steps: collecting original data, carrying out preliminary cleaning and formatting processing on the collected original data to obtain a standardized resource state data set, comparing predicted data with operation parameters of a current storage system, and if a predicted demand exceeds a current capacity limit, automatically generating a capacity expansion scheduling task to obtain a final resource optimization configuration scheme; according to the multi-level storage control method and device based on the access popularity, intelligent monitoring, load balancing and capacity planning of storage resources are achieved, the resource utilization efficiency and expandability of a storage system are improved, and an effective solution is provided for stable operation and performance optimization of a large-scale storage system.

The invention provides an erasure code compatible read-write method and system based on a bidirectional data access agency, and relates to the technical field of distributed storage, and the method comprises the steps: employing multi-agent reinforcement learning to construct a heterogeneous resource portrait and optimize task allocation, combining a space-time graph convolutional network and a federated learning framework to construct a data format conversion model, and constructing an erasure code compatible read-write model; data features are analyzed through an encoder based on an attention mechanism, a fragmentation strategy is generated, self-adaptive encoding is achieved through a capsule neural network, data integrity verification and repairing are conducted through a double-layer space attention network and a graph attention network, the data access efficiency of a heterogeneous storage system is improved, data format compatibility is enhanced, and the data access efficiency is improved. And the data integrity is ensured.

A storage device manages memory use data, such as map data which the storage device manages using a host memory, as journal data in a buffer memory located inside the storage device in a low power mode. The memory use data may be managed by updating journal data during the low power mode, and a command of a host device may be processed by updated journal data after switching from a low power mode to an active mode.

The invention relates to the technical field of data storage, in particular to a dynamic data distribution storage method and system for an RAID (redundant array of independent disks), and the method comprises the following steps: based on the access frequency of data blocks in a disk, recording the access frequency and timestamp of each data block, carrying out heat rating on the data blocks, and determining thresholds of hot data and cold data. According to the method, the dynamic distribution of data storage is effectively optimized by analyzing the access frequency of the data blocks, and the performance and the economic efficiency of a storage system are remarkably improved by migrating the frequently accessed data to the cache disk and migrating the less accessed data to the low-cost storage; according to the method, unnecessary occupation of high-performance storage resources is reduced, the operation cost is also reduced, heat rating is performed on the data blocks, and the storage positions of the data blocks are correspondingly adjusted, so that the data processing speed is higher, meanwhile, the data security is improved, when a hard disk fails, data recovery is faster, and the service continuity is ensured.

Methods, systems, and devices for programmable metadata and related operations are described. A method may include receiving signaling that indicates a set of rules for transitions of states of metadata at a memory device storing the metadata. The memory device may receive a command from a host device associated with a set of data after receiving the set of rules. The memory device may transition metadata associated with the set of data stored at the memory device from a first state to a second state based in part on the set of rules and the command. The memory device may execute the command received from the host device.

Methods, systems, and devices for programmable metadata and related operations are described. A method may include receiving signaling that indicates a set of rules for transitions of states of metadata at a memory device storing the metadata. The memory device may receive a command from a host device associated with a set of data after receiving the set of rules. The memory device may transition metadata associated with the set of data stored at the memory device from a first state to a second state based in part on the set of rules and the command. The memory device may execute the command received from the host device.

The invention relates to the technical field of solid state disks, and discloses a load collaborative scheduling method and system for a solid state disk, and the method comprises the steps: carrying out the data collection of a main controller of the solid state disk, and obtaining the original feature data; a Kolmogorov-Arnold neural network is input to carry out nonlinear feature transformation and linear combination operation, and a load prediction result is obtained; performing hierarchical processing to obtain a hierarchical scheduling model; constructing a multi-objective optimization function and carrying out constraint setting to obtain a constraint optimization equation set; performing convex difference function decomposition and augmented Lagrange function construction on the constraint optimization equation set, and solving through an alternating direction iteration method to obtain a scheduling decision scheme; according to the scheduling decision scheme, load balancing control is carried out on data write-in physical address allocation, data read cache scheduling and multi-channel parallel transmission, a real-time performance monitoring index is obtained, and the method realizes load collaborative scheduling of the solid state disk.

The invention relates to the technical field of edge calculation application and partial discharge detection, in particular to a partial discharge multichannel signal real-time synchronous acquisition method based on edge calculation. According to the method, the functions of multi-channel signal acquisition, time synchronization, feature analysis, hierarchical storage and the like are integrated at edge nodes, asynchronous acquisition, unified timestamp marking and data synchronous fusion of multiple types of partial discharge signals are realized, and extraction of multi-dimensional feature parameters such as time domain, frequency domain and energy and intelligent event discrimination are locally completed. For abnormal signals, the system realizes classified storage and remote uploading after encryption and compression processing; and for normal signals, dynamic management is carried out through circular caching. According to the method, the accuracy and efficiency of multichannel signal synchronous acquisition are remarkably improved, the data safety and the system adaptive capacity are enhanced, and the method is suitable for real-time online monitoring and intelligent diagnosis of partial discharge of power equipment.

A system includes a memory device and a processing device, operatively coupled with the memory device, to perform operations including: receiving a request to perform a read operation on a set of memory cells of the memory device; identifying a wordline group coupled to the set of memory cells of the memory device; identifying a threshold voltage offset bin associated with the set of memory cells; determining a current temperature associated with the set of memory cells; determining, based on the threshold voltage offset bin and the current temperature, a read mask identifier associated with the set of memory cells; determining, based on the read mask identifier and the wordline group, a set of threshold voltage offsets associated with the set of memory cells; and performing the read operation using the set of threshold voltage offsets.

This disclosure provides techniques for managing writes of data useful for storage systems that do not permit overwrite of a logical address. One implementation provides a nonvolatile memory storage drive, such as a flash memory drive, that provides support for zoned drive and / or Open Channel-compliant architectures. Circuitry on the storage drive tracks storage location release metadata for addressable memory space, optionally providing to a host system information upon which maintenance decisions or related scheduling can be based. The storage drive can also provide buffering support for accommodating receipt of out-of-order writes and unentanglement and performance of out of order writes, with buffering resources being configurable according to any one of a number of parameters. The disclosed storage drive facilitates reduced error rates and lower request traffic in a manner consistent with newer memory standards that mandate that writes to logical addresses be sequential.

Apparatuses and methods aggressor queue mitigation based threshold. A memory device detects aggressor rows by changing a count value associated with the row when it is accessed and comparing the count value to a mitigation threshold. Identified aggressor rows are stored in an aggressor queue. The value of the mitigation threshold is set based on a number of addresses which are stored in the aggressor queue. For example the threshold may increase as the number of addresses in the queue increases.