88 results about "Distributed data store" patented technology

A robotic surgical system network includes a plurality of robotic surgical systems. Each system includes robotic arms, sensors, a surgeon console, and a control system with an integrated AI module. A network interface is associated with robotic surgical system and provides secure data communication. A central or distributed data repository securely stores surgical data aggregated from the robotic surgical systems. The surgical data includes at least one of procedural data, sensor readings, imaging data, AI decision logs, surgical outcomes, or user interaction data. A training module utilizes aggregated surgical data to train or update AI models for the robotic surgical systems using unsupervised learning, transfer learning, or federated learning techniques. A cybersecurity module implements security measures for data transmission and system access, the measures comprising at least one of encryption, multi-factor authentication, or real-time threat detection.

The invention discloses a data consistency processing method, a distributed storage system and electronic equipment, and belongs to the field of distributed data storage systems, and the data consistency processing method comprises the following steps: when any storage node in the distributed storage system receives to-be-updated data sent by a client, obtaining a corresponding data updating path by taking the storage node as a first storage node; according to the data updating path, each storage node carries out data persistence on itself after receiving the data to be updated, if persistence succeeds, the data to be updated is transmitted to the next storage node, if persistence fails, data rollback is carried out, and feedback information of path updating failure is sent to the upstream of the data updating path; and after receiving the information, each upstream storage node carries out data rollback on the current updated data. According to the scheme, even if the update message processing flow fails, the consistency of the data between the survival copies / fragments can be ensured in real time.

Record-level transaction conflicts may be detected at storage nodes of a database back-end storage service. When a prepare statement is received, a storage node can determine whether another prepare statement acting on at least one of the same records has succeeded. If so, then the storage node can indicate to the database access application that there is a conflict, allowing the database access application to wait to try again or abort the transaction.

The invention relates to the field of enterprise application integration, in particular to a supply chain finance-oriented multi-protocol conversion and semantic verification system and method, which comprises a protocol adaptation layer, a core processing layer, a management support layer and a distributed data storage layer, the protocol adaptation layer adopts a plug-in and metadata driving design, and a protocol plug-in is an independent JAR packet and supports multi-protocol encoding and decoding and hot updating; the core processing layer realizes data standardization and financial-level semantic verification through a general message model, a dynamic routing engine, a visual data conversion module and a rule engine; and the management support layer provides a low-code portal and supports rule configuration, simulation testing and full-link monitoring. According to the technical scheme, through the seven steps of configuration, decoding, routing, conversion, verification, coding and auditing, the method adapts to a multi-specification heterogeneous system, data intercommunication accuracy and compliance are improved, docking cost is reduced, and supply chain financial service requirements are met.

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 provides a big data processing method and system based on smart medical treatment, and relates to the technical field of smart medical treatment, and the method comprises the following steps: collecting health data of a patient through a medical device and an information system, and carrying out the data preprocessing of the health data of the patient through distributed data storage, and obtaining the preprocessed health data of the patient; analyzing the preprocessed health data of the patient by using a deep learning model to obtain a health analysis result of the patient; and performing disease prediction and risk assessment based on the health analysis result of the patient. The intelligent medical big data processing system has the beneficial effects that the safety, the real-time performance, the accuracy, the low power consumption, the fault tolerance and the like of the intelligent medical big data processing system are remarkably improved, so that the whole system can more efficiently support disease risk prediction, clinical early warning and remote diagnosis and treatment; and the intelligent and refined development of intelligent medical treatment is greatly promoted.

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 invention discloses a block chain decentralized data security storage method and system, and relates to the technical field related to data processing, the method comprises the following steps: performing fragmentation processing on to-be-stored data to generate N data fragments; obtaining N encrypted data fragments; calling application scene information of the to-be-stored data to evaluate the block chain network, and determining M nodes of the block chain network according to an evaluation result; performing node selection, and making a data distribution strategy according to a selection result; and distributing the N encrypted data fragments to a block chain network according to a data distribution strategy for data storage. The technical problems that in existing distributed data storage, it cannot be ensured that the data can be stored in safe, reliable and efficient nodes, and the safety, privacy and reliability of the data in the transmission and storage process are difficult to guarantee are solved, and the technical effect of improving the data safety and privacy and the data storage efficiency and reliability is achieved.

Various techniques for data deletion on a distributed data storage (DDS) protection network are disclosed. Some techniques can include receiving, by a first DDS protection network node of a plurality of DDS protection network nodes, a deletion request corresponding to a digital asset. The deletion request can encode a retroactive data protection object. Additionally, the techniques can include performing a deletion by deleting at least one of a plurality of component files of the digital asset based at least on at least one of a first plurality of identifiers encoded by the retroactive data protection object.

The invention relates to a multi-copy distributed data storage system and method based on SDS and Ceph, and the system architecture comprises an RADOS layer which is used for segmenting to-be-stored original data into a plurality of objects and storing the plurality of objects; the storage pool layer comprises a plurality of storage pools, each storage pool comprises a plurality of PG collating groups, the PG collating groups are used for carrying out organization management and position mapping on storage of the objects, and the PG collating groups and the objects are in a one-to-many mapping relationship; the OSD layer comprises a plurality of object storage devices OSDs, the OSDs are used for storing objects on the physical disks, the Ceph system manages the physical disks by managing the OSDs, and the OSDs and the physical disks are in one-to-one mapping relation. By means of the train data storage method and device, the problems that in the related technology, a centralized storage mode is usually adopted for train data, and reliability and expandability are poor are solved, and the effect of improving the reliability, expandability and redundancy of the train data is achieved.

In some examples, a data management and storage (DMS) platform comprises peer DMS nodes in a node cluster, a distributed data store comprising local and cloud storage, and at least one processor configured to perform operations in a method of creating a local consolidated patch file from a patch file chain stored in the cloud storage. Example operations comprise, in a first dry-run phase, creating a patch file image of data blocks in one or more cloud patch files stored in the cloud storage; in a second data-transfer phase, downloading at least some of the data blocks from the cloud patch files identified by the patch file image; and creating and storing, in the local storage, the local consolidated patch file using the downloaded data blocks.

The present application relates to the technical field of data storage, and particularly relates to a distributed data storage and access processing method. The method comprises the following steps: presetting a guide configuration file in a distributed storage cluster to perform identity authentication and communication link establishment on each storage node and a cluster management center, thereby generating a secure data interaction channel; a data sending end device sends a data storage request to the cluster management center through the secure data interaction channel and distributes data shards to appropriate storage nodes; a data receiving end device sends a data access request to the cluster management center through the secure data interaction channel and generates an access path and feeds back the access path to the data receiving end device; by monitoring the corresponding resource usage in each storage node in real time, when a preset threshold is reached, based on the result of insufficient resources, according to a preset data migration strategy and a load balancing algorithm, the data is redistributed to other storage nodes. The present application can realize efficient storage and rapid access of data in a distributed environment.

A custodial token platform may implement a single smart contract for outbound messages. The custodial token platform may deploy, to a blockchain distributed data store, a self-executing program that batches messages from the self-executing program to multiple addresses of the blockchain distributed data store that are external to a custodial token platform associated with the self-executing program. The custodial token platform may select, from the multiple withdrawal requests and based on selection criteria, a set of withdrawal requests to fulfill via a batch message from the self-executing program. The custodial token platform may broadcast, to the blockchain distributed data store, a message that calls the self-executing program. The message includes an indication of a set of external addresses associated with the set of withdrawal requests, and the message causes a transfer of a set of crypto tokens from the self-executing program to the external addresses via the batch message.

The invention relates to the technical field of edge computing storage, and discloses a distributed data storage dynamic optimization method based on edge computing. The method comprises the following steps: acquiring data storage state data and data access request data of distributed edge nodes, and constructing a data resource distribution model according to the data storage state data and the data access request data; determining a system resource early warning state in combination with a preset optimization condition and the model, entering a dynamic optimization mode and generating a data migration priority queue when early warning is triggered, and executing data migration operation according to the queue; and updating the data resource distribution model according to a migration result, determining a system resource quit state based on the updated model, quitting the dynamic optimization mode during triggering, and transmitting the optimized storage state data to a central management system. According to the method, the node state and the access requirement are sensed in real time, the data distribution is dynamically adjusted, the edge node isomerism and the data access dynamics are adapted, and the distributed data storage efficiency is improved.

A global policy-driven framework for managing, revising, and implementing data coherency policies in a distributed data storage system. An edge node of the distributed data storage system receives a request from an application to store a data object in the system. The edge node, in response to receiving the request to store the data object, generates a coherency policy request, which is then submitted to the primary node of the system. The primary node of the system generates a coherency policy response, which is returned to the edge node. The edge node then stores the data object in the system in accordance with the coherency policy response.

This invention discloses an intelligent meteorological data processing system, comprising: a meteorological data parsing and storage subsystem, which implements two-phase commit based on Kafka middleware for receiving and parsing multi-source heterogeneous meteorological data; a business configuration subsystem, which provides a rule configuration interface for dynamically configuring meteorological data processing rules and synchronizing the processing rules to business nodes in real time; a business monitoring subsystem, which collects business indicators in real time through Kafka log streams; and a distributed data storage subsystem, which uses a distributed MySQL cluster to store meteorological data and caches it through Redis. This invention solves the problems of complex operation and maintenance, data backlog, poor scalability, and low reliability of traditional meteorological decoding systems by dynamically configuring business rules, distributed meteorological data decoding, distributed storage architecture, real-time monitoring and alarm mechanism, and fault tolerance function.

The invention discloses an urban power grid dispatching analysis system based on a graph calculation operator. The urban power grid dispatching analysis system comprises a data layer, an operator layer and an application layer, the data layer is used for collecting power grid data including power grid real-time operation data, meteorological data and user load data collected by an SCADA system and high-frequency synchronous data collected by a PMU, and a relational database is constructed according to the collected data; the operator layer constructs a power grid graph model based on power grid topological characteristics and operation data; the operator layer comprises a data patterning engine, and the relational data is converted into graph structure data in real time by adopting an ETL technology and a stream processing mechanism based on sub-mode splitting; the operator layer adopts distributed data storage, applies a dynamic load balancing algorithm, and dynamically distributes data writing tasks according to the load condition of each node; the operator layer comprises a core operator subset; and the application layer is used for interacting with a user. The method has the advantages that efficient scheduling and analysis of super-large-scale power grid graph calculation operators are achieved.

The invention relates to an identity credential implementation method and system based on a block chain and a medium, and the method comprises the steps: modeling a verifiable credential VC / verifiable expression VP into a soul binding token, achieving identity credential information capitalization, carrying out the chain management of the identity credential of a user in the block chain, and improving the identity credential implementation efficiency. The system comprises a soul binding token life cycle management module, a soul binding token identity data generation and verification module, a distributed data storage and sharing module and a block chain module. Compared with the prior art, on-chain management can be carried out on the identity credential of the user in the block chain under the condition that the privacy of the user is protected, and automatic verification of VC / VP is facilitated.

The invention discloses a distributed data security storage and access control method oriented to engineering machinery, relates to the field of engineering machinery, solves the problem of poor storage effect of the existing distributed data security storage method, and comprises the following steps: S1, performing data analysis on instrument working data generated in each engineering instrument area, the method comprises the following steps: S1, carrying out distributed storage demand analysis on an engineering instrument area according to an analysis result, carrying out data generation amount monitoring data acquisition on each engineering instrument area according to the analysis result, and obtaining construction project monitoring data, S2, carrying out distributed storage demand analysis on one engineering instrument area according to the construction project monitoring data, and obtaining storage demand analysis data according to the analysis result, and S3, carrying out distributed storage demand analysis on the engineering instrument area according to the analysis result. And according to the storage demand analysis data, carrying out storage mode matching on each engineering instrument area, and carrying out access authority control on the distributed storage engineering instrument areas, so that the storage matching degree of the distributed data storage mode and the engineering instrument data can be improved.

Disclosed in the present invention is a big data-based information collection system for software development. The system comprises: a dynamic data collection module, which is used for automatically collecting a code submission record, a task completion situation and defect tracking information during software development by means of an API interface and a log file; a data pre-processing module, which is used for performing formatting, deduplication and missing value filling processing on collected original data, so as to ensure the quality of the original data for subsequent analysis; a distributed storage module, which is used for using a distributed data storage method to store pre-processed data in a blockchain system, so as to realize efficient storage and access of massive data; and an intelligent analysis module, which is used for using a machine learning algorithm to perform deep analysis on data stored in a distributed manner, so as to identify a software development trend and predict a project development risk. The system can monitor a software development progress in real time, predict a potential problem, and assist in decision making.

A system groups multiple entities in a large distributed data store (DDS), such as directories and files, into a subset called a domain. The domain is treated as a unit for defining policies to detect and treat sensitive data. Sensitive data can be defined by enterprise or industry. Treatment of sensitive data may include quarantining, masking, and encrypting, of the data or the entity containing the data. Data in a domain can be copied as a unit, with or without the same structure, and with transformations such as masking or encryption, into parts of the same DDS or to a different DDS. Domains can be the unit of access control for organizations, and assigned tags useful for identifying their purpose, ownership, location, or other characteristics. Policies and operations, assigned at the domain level, may vary from domain to domain, but within a domain are uniform, except for specific exclusions.

The invention provides a data processing method and device, processing equipment, a program product and a medium, and relates to the technical field of block chains. The method comprises the following steps: according to original data submitted by a first user, generating encrypted data corresponding to the original data; generating a target watermark image corresponding to the original data according to a first identity label of a first user and the encrypted data; and on the basis of an intelligent contract, according to the encrypted data and the target watermark image, generating a second identity label of a data element corresponding to the original data and meta-information corresponding to the second identity label. According to the scheme, the problem that an existing distributed data storage system lacks data ownership management is solved.

The invention relates to a teaching equipment and Internet of Things system data connection interaction terminal, which comprises a positioning base, a connector, communication antennas, an intelligent gateway, a distributed data storage unit, a data processing unit and a driving circuit, and is characterized in that the upper end surface of the positioning base is connected with the connector, and the communication antennas are respectively located in the positioning base and the connector; each communication antenna is electrically connected with the intelligent gateway and the driving circuit and establishes data connection with the intelligent gateway, the intelligent gateway is embedded in the connector, and the distributed data storage unit, the data processing unit and the driving circuit are all located in the positioning base. The use method comprises three steps of physical assembly, system networking and communication operation. The system is high in integration, modularization and intelligentization degree, networking is convenient, networking management and monitoring requirements of operation states of various types of teaching equipment can be effectively met during operation, the management capability of teaching activities can be improved, and the labor cost of system operation and maintenance can be reduced.

The application discloses a portrait report presentation method, device, equipment and medium, and belongs to the technical field of data storage. The method comprises the following steps: acquiring condition information corresponding to a portrait query request, and generating a portrait item based on the condition information; generating a database query statement according to the portrait item, and obtaining item metadata and an item result set of the portrait item by using the database query statement; wherein the item metadata is an identifier of the condition information; generating a data bucket identifier corresponding to the item result set based on the item metadata according to a preset data bucket identifier generation rule, performing distributed data storage proxy on the item result set according to the data bucket identifier, and generating and presenting a portrait report based on the distributed stored item result set. The technical problem that a single data source cannot meet the data storage needs and a storage bottleneck exists is solved.

In one approach, filesets to be backed up are divided into partitions and snapshots are pulled for each partition. In one architecture, a data management and storage (DMS) cluster includes a plurality of peer DMS nodes and a distributed data store implemented across the peer DMS nodes. One of the peer DMS nodes receives fileset metadata for the fileset and defines a plurality of partitions for the fileset based on the fileset metadata. The peer DMS nodes operate autonomously to execute jobs to pull snapshots for each of the partitions and to store the snapshots of the partitions in the distributed data store.

The application relates to the technical field of edge computing storage, and discloses a distributed data storage dynamic optimization method based on edge computing. The method acquires data storage state data and data access request data of distributed edge nodes, and constructs a data resource distribution model according to the data; the method combines preset optimization conditions with the model to determine a system resource early warning state, enters a dynamic optimization mode when the early warning is triggered, and generates a data migration priority queue, and executes a data migration operation according to the queue; the method updates the data resource distribution model according to a migration result, determines a system resource exit state based on the updated model, exits the dynamic optimization mode when the exit state is triggered, and transmits the optimized storage state data to a central management system. The method dynamically adjusts data distribution by real-time sensing of node states and access demands, adapts to edge node heterogeneity and data access dynamics, and improves distributed data storage efficiency.

Embodiments of the present disclosure provide a distributed data storage control method, device and electronic equipment, the method comprising: receiving, by a proxy node, a first change request for a target file in a NAS cluster, the first change request being used to directly or indirectly trigger a change in target metadata of the target file; in response to the first change request, assigning, by a distributed lock management node in the NAS cluster, a corresponding distributed lock and returning a first response information to the proxy node; receiving, by the proxy node, the first response information, configuring a corresponding local memory lock for the distributed lock corresponding to the first change request; and based on the first change request having the distributed lock and the local memory lock, controlling the change in the target metadata of the target file in the NAS cluster, so as to avoid the target metadata from being disordered and improve system stability.

This invention discloses a dynamic compression-type distributed data storage method, storage system, and apparatus, comprising: setting up a distributed storage node plugin, starting a private distributed storage node, and triggering a content addressing identifier smart contract based on a storage request from an external system; generating a corresponding key pair for the distributed storage node, wherein the content addressing identifier smart contract specifies a blockchain node address; enabling the distributed storage node to adapt to a dynamic distributed network based on the content addressing identifier smart contract; the blockchain node selecting a weighting factor for the stored data and calculating the data value of the stored data; the distributed storage node setting stored data attributes, allocating the entire storage area, reserving storage space for the stored data according to the data value, and determining a default storage period; compressing the stored data according to the data value, data attributes, reserved storage space, and storage period, and storing the compressed data in a database.