549 results about "Block (data storage)" patented technology

The invention discloses a logistics data credible evidence storage and tracing method based on a block chain, and the method comprises the following steps: collecting original logistics data, and executing data standardization processing; constructing a layered Merkle mountain structure, and calculating to obtain a main root commitment of the layered Merkle mountain; dividing a layered Merkle mountain range structure, and calculating to obtain a windowed subtree root set; configuring a revision branch record structure, generating a collision pair by using chameleon hash, and generating a revision proof record; a multi-index root structure is constructed, a cross-root sharing mechanism is established, and a multi-dimensional tracing index set is generated; and based on the hierarchical Merkle mountain range main root commitment, the windowed subtree root set, the multi-dimensional traceability index set and the revision proof record, executing anchoring consistency verification, and outputting a credible evidence storage result and a traceability verification result. According to the invention, the logistics data evidence storage integrity and the multi-dimensional tracing efficiency are improved.

The invention discloses a software development result traceability analysis system based on version control, and relates to the technical field of intelligent software analysis. According to the method, the non-tampering property of code submission records is ensured through a block chain technology, a credible basis is provided for traceability, the code semantic analysis module generates a data set containing semantic association in combination with a clustering algorithm and weighted calculation, and the function influence positioning module constructs a function association graph by applying a graph neural network algorithm, so that the traceability is improved. An influence path of code change on system functions is automatically identified, the time cost of complex project function influence positioning is remarkably reduced, an evolution path generation module analyzes and tracks a code evolution path in combination with a time sequence, and a core module identification module clusters key nodes and positions a core function module. And the time-tracing source data storage module generates a visual relation graph and a queried data set, so that the whole-process management from code submission to result tracing is realized.

The invention provides a hierarchical storage read cache management method and system, a storage medium and a product, and relates to the field of data storage, the method comprises the following steps: dividing all data blocks into three data hierarchies of hot data, warm data and cold data for respective storage according to access popularity, the data storage positions, the storage data proportions and the information recording precision of the three data levels are different; when the cold data is accessed, the accessed target cold data is upgraded to the temperature data, and the temperature data is updated; when the hot data is accessed, the complete metadata information of the accessed target hot data is cached in the memory, and the hot data is sorted and updated again; and when the temperature data is accessed, determining whether to replace the target hot data with the target temperature data or not according to the size relationship between the first historical access time of the accessed target temperature data and the second historical access time of the target hot data with the lowest access heat. By implementing the method, the occupation of memory resources can be reduced when the popularity of mass data is tracked.

The invention discloses a multi-source information fusion safety production risk intelligent early warning and disposal platform, which comprises a multi-source information acquisition module, an information preprocessing module, a multi-source information fusion module, an intelligent risk identification and early warning module, a disposal scheduling module and a data storage and interaction module, heterogeneous data such as sensor monitoring, video monitoring, equipment logs and manual reporting are collected and cleaned and standardized, and then a weighted fusion algorithm and a cross-modal deep learning model are adopted to realize multi-source data fusion; based on a preset risk assessment index system and the trained risk identification model, mapping risk levels by quantizing comprehensive risk scores, generating graded early warning information and pushing the graded early warning information in multiple channels; meanwhile, a disposal scheme is automatically matched, an instruction is issued, a closed loop is tracked, and data security is guaranteed in combination with distributed and block chain storage. Comprehensive perception, accurate identification, intelligent early warning and efficient disposal of safety production risks are achieved, and the intelligent and refined level of safety production management is remarkably improved.

The invention relates to the technical field of block chain data storage and traceability tracking, in particular to a document printing and traceability tracking system based on a block chain. Comprising an off-line certificate generation unit used for generating an off-line cryptographic certificate based on technical parameters analyzed from an external printing request; the dynamic anchoring control unit is used for monitoring system state parameters and carrying out dynamic anchoring strategy calculation based on the system state parameters so as to generate an anchoring triggering decision; the aggregation anchoring unit is used for responding to the anchoring triggering decision, aggregating a plurality of offline cryptographic certificates to generate an aggregation root certificate, and broadcasting a block chain transaction containing the aggregation root certificate; and the verification traceability unit is used for acquiring the aggregation root certification on the block chain and executing cryptographic verification in combination with the offline data to obtain a final verification result. According to the invention, the core pain point that the system is unavailable due to the performance bottleneck of the block chain in a high-concurrency scene in the prior art is solved, and the continuity and reliability of services are ensured.

The invention relates to the technical field of distributed storage, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a data storage method, device, equipment and medium based on partition identifier mapping, and the method comprises the following steps: receiving a file and dividing the file into data blocks to generate block identifiers; generating a partition identifier based on the file identifier and the block identifier through hash mapping; creating a partition disk pack mapping table and writing an initial relationship; querying the mapping table to obtain a disk group, and writing the data block into a physical disk to generate a copy; monitoring the health of the disk, keeping the partition identifier and the block identifier unchanged when a fault occurs, and updating the mapping relation to a new disk group; and receiving a read-write request of the target partition identifier, querying the mapping table to obtain the target disk pack, and executing access. According to the method, the partition identification and the block identification are kept unchanged, fast fault tolerance is achieved only by updating the mapping relation, metadata updating expenditure is reduced, bottom layer change is shielded through partition identification routing, and access transparency and high availability are achieved.

The invention discloses a network data distribution method and system based on big data and a storage medium, and relates to the technical field of big data storage. The big data-based network data distribution method and system and the storage medium comprise the following steps of S1, collecting synchronous data in a machine tool data synchronization process, and performing data cleaning and standardization processing on the synchronous data; s2, dividing original machine tool data into a plurality of original blocks, calculating an estimated value of the number of redundant blocks, adding metadata attached to the redundant blocks to the original blocks, and then asynchronously sending the original blocks; s3, receiving and caching the synchronous data block, recovering original data through decoding and verification, calculating a synchronous reliability evaluation value, and adjusting a redundancy strategy based on the synchronous reliability evaluation value; and S4, calculating a synchronization abnormity evaluation value according to the synchronization data and the synchronization reliability evaluation value, performing abnormity grading according to the synchronization abnormity evaluation value, and adjusting a synchronization strategy. The problem that data consistency is seriously influenced by packet loss when edge nodes synchronize data is solved.

The invention discloses a distributed data storage and access control method based on a block chain, and relates to the technical field of data security. The method comprises the following steps: fragmenting user data, encrypting the fragmented user data by using an encryption algorithm, and storing the encrypted user data in a plurality of distributed nodes; taking the hash value and the storage position of the data fragment as metadata to be recorded in a block chain, and performing integrity verification through a smart contract; when a user accesses, user attributes are verified based on an attribute-based encryption technology, and an access control strategy is dynamically executed through an intelligent contract; and an erasure code technology is adopted to carry out redundancy storage so as to realize data recovery and fault tolerance. The method effectively solves the problems of single-point failure, privacy disclosure and inflexible access control in traditional centralized storage, has the beneficial effects of improving data security, guaranteeing integrity, realizing fine-grained dynamic access control and enhancing system reliability, and is suitable for data security management in cloud computing, Internet of Things and big data environments.

The invention relates to the technical field of block chains, and discloses a power load prediction system based on artificial intelligence, and the system comprises a data collection module which is used for collecting historical load data, real-time meteorological data, calendar information, and power grid event data; the data storage module is used for performing partition storage on the historical load data, the real-time meteorological data, the calendar information and the power grid event data in the parallel chain to obtain a partition storage result; the feature fusion module is used for performing federal feature extraction on the partition storage result in the parallel chain to obtain federal features and fusing all the federal features; the load prediction module is used for outputting a predicted power load corresponding to the space-time fusion feature through a hybrid expert model; and the load calibration module is used for generating an attribution auxiliary index of the predicted power load and calibrating the predicted power load into the final power load by using the attribution auxiliary index. According to the invention, a new-generation prediction framework considering data security, feature fusion and interpretability can be provided.

The invention relates to the technical field of data storage, and discloses a memory particle test method, which comprises the following steps that: 32-bit memory particles relate to a first channel (16-bit) and a second channel (16-bit), the first channel (16-bit) and the second channel (16-bit) of the 32-bit memory particles correspond to physical blocks in the 32-bit memory particles, the 16-bit memory particles only relate to the first channel, and the second channel (16-bit) corresponds to physical blocks in the 32-bit memory particles. The first channel corresponds to a physical block in the 16-bit memory particle; all memory spaces of the 16-bit memory particles are scanned through a program of the 32-bit test system, if errors occur in the program, it is judged that the corresponding program relates to the second channel, codes related to the second channel in the test system are found, and the codes corresponding to the second channel are shielded. By means of channel shielding, code modification, address mapping and the like, compatibility of the 32-bit test system to two kinds of particles is achieved.

The application is suitable for the technical field of data storage, and provides a data disaster recovery method and device, comprising the following steps: determining a fault type in a distributed cluster system and a range of data to be recovered; acquiring state parameters of multiple normal nodes in the distributed cluster system, and service sensitivity features and data block access features of the data to be recovered; performing data preprocessing operations; respectively adopting a service sensitivity evaluation model and a node state evaluation model to determine a data recovery priority list and a node priority list; determining a fault processing strategy according to the data recovery priority list and the node priority list; and executing the fault processing strategy. Through the above method, the real-time evaluation algorithm of the heterogeneous big data node is increased on the basis of dynamically updating the data recovery priority based on the service sensitivity evaluation model, and compared with the traditional technology, the fault perception of the business system can be reduced while the data disaster recovery efficiency is improved.

The invention belongs to the field of data security, and particularly relates to a time sequence encrypted storage and expired crushing method for monitoring data of external equipment, which comprises the following steps: acquiring a monitoring data stream of the external equipment, segmenting the monitoring data stream according to a preset time window, and deriving a unique encryption key for each segment; encrypting and storing the corresponding window data by using the key to obtain a time sequence encrypted data block; when the conjoint analysis request is responded, a specified window secret key is distributed to a calculation party according to a preset authorization strategy, so that the calculation party executes secure multi-party calculation on the window data block; meanwhile, the life cycle of the data block is monitored in real time, data is automatically erased when the data block expires, a corresponding secret key is destroyed, and a shredded verifiable evidence is generated and uploaded to a storage chain constructed by combining a root secret key of the general data platform and secret keys of all calculation parties with a block chain; according to the application, data storage security and conjoint analysis compliance are guaranteed, the risk of residual keys is avoided, the traceability of crushing operation is ensured, and the credibility of cooperation of multiple participants is improved.

A data storage device includes a bad block management system. The bad block management system detects a grown bad block of the data storage device. When a grown bad block is detected, the bad block management system initiates a manual block write process on the wordlines associated with the grown bad block. The manual block write process includes programming the wordlines of the grown bad block in a particular state and with a voltage that closes a leakage path between a bit line associated with the grown bad block and a ground line or a ground path associated with the grown bad block.

The embodiment of the invention provides a data auditing method and device, equipment, a storage medium and a program product, relates to the technical field of data processing, and can be applied to the field of financial science and technology. According to the method, a hash value of an operation log is stored in a private block chain network, then a digital fingerprint corresponding to the operation log is determined based on the hash value, then abnormity auditing is performed on the operation log based on the hash value of the operation log in the private block chain network and an auditing contract, and when it is determined that a target operation log is abnormal, the operation log is subjected to abnormal auditing. And verifying the target operation log based on the target digital fingerprint corresponding to the target operation log in the public block chain network, and generating an audit report of the target operation log when the verification is passed. According to the method, the hash value of the operation log and the auditing contract are stored in the public chain, on the basis that the compliance requirement of the financial industry for data storage is met and auditing credibility is ensured, automatic auditing is achieved, and the storage cost is reduced.

The invention relates to the technical field of intelligent voice data processing, and discloses an intelligent voice interface data calling method. The method comprises the following steps: receiving a voice instruction stream input by a user, and converting the voice instruction stream into a structured semantic unit set through a multi-level semantic analysis engine; and dynamically layering the instruction intention according to the semantic association degree in the structured semantic unit set to generate an intention sequence with priority marks. And based on the priority mark of the intention sequence, extracting a candidate data block set matched with the intention of each level from a distributed data storage cluster. And performing cross-modal feature alignment on the candidate data block set, and calculating the semantic coverage degree of each data block and the corresponding intention hierarchy. And screening out target data blocks according to a semantic coverage threshold, and recombining the data blocks according to a priority sequence of the intention sequence. And loading the recombined target data block set to a real-time processing channel of the voice interface to generate an interactive voice response data stream.

The present disclosure is directed to key-value data storage systems using content addressable memory. A memory system includes a memory device comprising a content addressable memory (CAM) block storing a plurality of stored search keys and a value data block. The memory system additionally includes a processing device that receives an input search key and identifies one of the plurality of stored search keys that matches the input search key, the one of the plurality of stored search keys having an associated matching orientation in the CAM block. The processing device further determines a corresponding value orientation in the value data block using the associated matching orientation and retrieves data representing a value associated with the input search key from the value orientation in the value data block.

The application provides a mapping method and an accelerator architecture for realizing deep fusion of complex operators, relates to the field of convolutional neural networks, and comprises the following steps: acquiring input feature map information, dividing a PE array, and determining an optimal division result of the PE array; determining configuration information based on the execution flow of the PE array and the optimal division result; and realizing target execution of the PE array according to the configuration information. By dividing the PE array of the architecture into a first array and a second array, parallel computation of two convolutional operator data blocks in a subgraph can be realized, intermediate data storage access can be completely eliminated, each convolutional operator data block in the subgraph can be evenly calculated in parallel, the execution efficiency of the subgraph of this type is improved, and by adding new hard connection lines to the PE array, the overall execution time of the subgraph is further reduced, and the performance of the subgraph is improved.

The invention discloses a multi-cloud data possession proving method, and relates to the field of cloud computing and data security. The method aims at solving the problems that in the multi-cloud storage environment, the data integrity verification efficiency is low, abnormity positioning is difficult, and damaged data is difficult to automatically repair. According to the method, a plurality of storage positions are intelligently distributed for data blocks through a dynamic weight model, and data fingerprints associated with multiple clouds are constructed; during verification, data block risk scores and random selection are fused to generate a challenge set, and each cloud service party calculates local response based on stored data blocks and fingerprints; the verifier aggregates all the responses, compares the responses with an expected value through a consistency verification function, and outputs a comprehensive verification result; if it is judged that the data are not completely held, an exception positioning and repairing mechanism is triggered. According to the method, efficient verification, accurate positioning and autonomous recovery of the integrity of the multi-cloud data are realized, and the reliability and security of cross-cloud storage of the data are remarkably improved.

Disclosed in the embodiments of the present application are a data storage method and apparatus, a device, and a non-transitory readable storage medium. According to the embodiments of the present application, F parity blocks occupying blank storage areas are added to a RAID system, which not only increases error tolerance but also eliminates the need for additional parity disks. During data storage, corresponding original check codes are solved according to an original encoding method, and additional check codes located on the parity blocks are solved simultaneously. Thus, it is possible to recover more erroneous data based on the original check codes and the additional check codes. When an error occurs in a disk in which any block in a stripe is located and data loss occurs in other blocks of the same stripe, the corresponding data can still be recovered.

The utility model discloses a static off-line seismic data memory protection device which comprises a storage medium body, the outer wall of the storage medium body is connected with a plurality of buffer springs, the outer wall of the storage medium body is connected with a plurality of protection corners in a sliding mode, and each buffer spring is connected with each protection corner in a one-to-one correspondence mode. Each protection corner is rotationally connected with a transmission rod, the four transmission rods are jointly and rotationally connected with a rotating disc, the upper end face of the rotating disc is fixedly connected with a clamping block, the clamping block is slidably connected with a protection plate, the two end faces of the protection plate are connected with push springs correspondingly, and the push springs are connected to the outer walls of the corresponding storage medium bodies correspondingly. According to the static off-line seismic data memory protection device provided by the utility model, through the arrangement of the protection corners and the protection plates, the corners of the storage medium body are protected when the storage medium body is influenced by external force, and the storage medium body is prevented from being secondarily damaged under the cooperation of the push springs.

The invention discloses a data management platform based on a block chain. The data management platform comprises a traceability data storage module and a data consistency management module. Through the traceability data storage module, the traceability data fingerprint of the traceability data is generated, only the traceability data fingerprint is stored in the blockchain account book, a non-tampering evidence is formed, and the storage overhead of the blockchain is reduced. And real traceability data is stored in a central database for subsequent query and review. Through the data consistency management module, the traceability data fingerprints in the blockchain account book and the traceability data in the central database are subjected to consistency management, the data consistency between the on-chain data and the off-chain central database is ensured, and the traceability data is ensured to be credible.

The invention relates to the field of block chains, and discloses a government affair approval data credibility method and system based on a block chain technology, and the method comprises the steps: S11, receiving an application; s12, dividing the data; s13, performing hierarchical encryption; s14, under the data storage chain, generating a root hash; s15, the first block is linked in a consensus mode; in the examination and approval stage, S21, data are verified, and operation is received; s22, updating the data, and generating a new root hash; s23, a second block is linked in a consensus mode; the system comprises a data interface module, a data processing module, a composite tree construction module and a consensus writing module. By adopting an on-chain and off-chain collaborative architecture and constructing an MRBT composite tree data structure to aggregate and identify off-chain data, the technical effects of efficiently verifying data integrity and effectively preventing data from being tampered are achieved, non-tampering and traceability of government affair approval full-process data are realized, the authenticity and credibility of approval data are ensured, and the method and the device have the advantages of being high in practicability and easy to popularize and use. And the final credibility of the approval result is improved.

The application discloses a real asset fair and safe transaction processing method and system based on a trusted execution environment, and relates to the technical field of digital transaction. The method comprises the following steps: in response to a connection request of a client, transaction data is acquired; the transaction data types include: conventional real asset transaction data and sealed transaction data containing a bid; a session key is generated by negotiation between the client and a verified TEE node; the TEE is a trusted execution environment; the transaction data is encrypted by the client based on the session key; the encrypted data packet is anonymously submitted to the TEE node, so that the TEE node decrypts the encrypted data packet based on a private key, transaction screening processing is performed on the decrypted transaction data based on the transaction data type, and winning transaction data is obtained; after the winning transaction data is verified in terms of integrity and legality, the winning transaction data is submitted to a block chain for block packaging and data storage, and incentive distribution is performed. The application can guarantee tamper-proof transaction order and transparent income distribution.

The application provides a data storage method, medium and computer program product for a large model. The data storage method for the large model comprises: in an inference stage of the large model, organizing quantized data to be stored and corresponding quantized parameters in a same storage tensor, wherein the storage tensor has multiple dimensions, and from an outermost layer to an innermost layer dimension, the dimensions comprise: a block dimension corresponding to a physical storage block in a paging management mechanism, each physical storage block having a continuous physical address range; an attention head dimension corresponding to an attention head defined for the large model; a word element dimension corresponding to a word element generated in the inference stage; a quantization grouping dimension corresponding to a quantization grouping of each word element on a feature dimension of each attention head; and a data dimension organizing quantized data and quantized parameters of each quantization grouping; and based on a logical storage structure of the storage tensor, storing the quantized data and the quantized parameters in a physical storage block of a cache.

The invention provides an interactive processing method for mentioning functions and a related device, and relates to the technical field of software, and the method comprises the following steps: obtaining an input operation, and determining an operation type of the input operation; under the condition that the operation type is insertion operation, a rich text is inserted at the current cursor position, the rich text comprises a mention text block, business data of mention objects in the mention text block are stored in a custom attribute mode, and custom attributes comprise target style attributes; and outputting the mention text block according to the target style attribute, and recovering the mention text block to a preset default style attribute after the mention text block is output. According to the method, the user-defined attribute function of the rich text is utilized, the service data serves as the metadata to be directly attached to the text interval to be stored, the problem of data storage splitting is solved, the input style is reset after the mention text block is inserted, and style inheritance is prevented.

A system for classifying, allocating and managing mobile phone numbers based on usage type via a central portal / agency, characterized by the following technical features: a. The server system includes at least one processing unit and a network communication connection for electronic communication with telecommunications operators and external authorities; b. an access and interface unit configured to provide secure access to a country-specific interface for the allocation of mobile phone numbers; c. one or more data storage units that store the following: i. a categorization register data structure that includes predefined user categories and associated category identifiers (Cat_IDs) that can be selected by an applicant, ii. Allocation rules for verification authorities that link regulated categories to independent government or authorized external verification bodies, and iii. a centrally managed numbering resource comprising numbering blocks provided by telecommunications authorities and / or algorithmically generated numbering sequences, independent of mobile network operators' holdings; d. an online application module that is executed by the processing unit and is configured to receive an allocation request, capture a user-selected category, and provide interfaces for uploading documents for KYC and category-dependent verification documents; e. a verification interface module configured to send verification requests to an associated verification authority and receive a response confirming authorization; f. an allocation manager configured to select or generate an available mobile phone number from the centrally managed numbering resource after successful authorization confirmation and to link the corresponding Cat_ID to the number through a numbering plan-compliant digit encoding and / or metadata linking; and g. a tamper-proof audit ledger module that is stored in the data storage unit and records the category selection, verification result and provisioning events for activation and unlocking in order to retrieve and transmit them to an interface of the regulatory authority.

The invention relates to the technical field of data storage, and particularly discloses an AWG waveform data storage method based on a DDR architecture, which comprises the following steps: waveform data storage configuration: performing logic hierarchical division on a DDR storage space, and configuring header information descriptors containing data length information for each waveform sub-block, classified storage and identification of test excitation waveform data are realized; and dynamic waveform scheduling: after the upper computer issues the initial base address of the unified waveform data block, the FPGA calculates the initial address of the waveform data of each channel according to the initial base address, and transmits the waveform data of each channel to the corresponding DAC unit in parallel in combination with the length of the waveform data to generate a test excitation waveform. The DDR storage space is logically divided into multi-channel independent areas, multi-waveform sub-blocks are divided in each area, and a special header information descriptor is matched, so that pre-storage and quick positioning of multiple test excitation waveforms are realized, and the limitation that a traditional scheme only supports a single test mode is solved.

This invention relates to a multi-level parallel processing system for massive amounts of data from medium- and high-orbit SAR, comprising: a data storage device for storing multiple full-scene observation data returned by medium- and high-orbit synthetic aperture radar within a preset period; a distributed computing device including a data exchange node and multiple data processing nodes connected to the data exchange node; the data exchange node, connected to the data storage device, for acquiring multiple full-scene observation data, decomposing each full-scene observation data into multiple task blocks, and distributing the multiple task blocks to the multiple data processing nodes; and the multiple data processing nodes for performing parallel processing on the received task blocks using a multi-threaded model and feeding back the corresponding processing results to the data exchange node. This device, through a multi-level joint parallel approach of data-task-algorithm, can effectively improve the throughput of processing massive amounts of data, meeting real-time or near-real-time imaging requirements.

The invention provides a memory device and a data storage method thereof. The data storage method includes: generating, by a data controller, a first user data feature of user data stored in a random access memory; sending, by the data controller, the first user data characteristic of the user data to an IMS memory device; comparing the first user data feature with a plurality of second user data features in a plurality of feature values stored in the IMS memory device to generate a comparison result, the feature values including the second user data features and a plurality of entity block addresses corresponding to data stored in the storage device; sending, by the IMS memory device, the comparison result to the data controller; and determining, by the data controller, whether to write the user data into the storage device based on the comparison result.

The present application relates to the field of data processing, more particularly, the present application relates to a kind of based on distributed financial data storage method and system, method includes: obtaining the financial transaction data stream to be stored and is divided to obtain multiple data blocks;For single data block, the distribution variation degree of the data block is calculated, based on distribution variation degree, respectively determine the weighted probability for constructing compression encoding table, encryption round of encryption algorithm and replication factor in distributed storage system, and based on the three key parameters determined in sequence, data block is compressed, encrypted and stored;Compression, encryption and storage are carried out to all data blocks, thus complete the distributed security storage of the financial transaction data stream.The present application controls compression, encryption and storage link by unified index linkage, while improving the anti-statistical analysis ability of encrypted data, realizes the adaptive balance of storage security and resource cost.