205 results about "Data restoration" patented technology

The embodiment of the invention provides a computer communication method and system based on the Internet of Things, and the method comprises the steps: constructing a multi-level system architecture, carrying out the preprocessing and feature extraction of an original data flow, recognizing the data characteristics through a time sequence analysis method, and constructing a dynamic data model; deploying a monitoring agent at a transmission node to collect network performance indexes in real time, and constructing a network quality evaluation model; for an incomplete sensor data flow, prior probability distribution is constructed based on a dynamic data model and a network quality grade, and an optimal estimation value of missing data is calculated by adopting a Bayesian reasoning framework and an iterative algorithm; establishing a mapping relation between a network state and an optimal parameter through reinforcement learning to realize self-adaptive adjustment and optimization; and grading the data according to reliability, extracting high-reliability data points as anchor points, designing an iterative refinement algorithm to realize information propagation, and fusing to obtain a complete sensor data stream. According to the method, the problems of poor data recovery accuracy, static parameter configuration and insufficient adaptability in a complex network environment are solved.

The invention relates to the technical field of electric energy metering anomaly detection and diagnosis analysis, in particular to a dynamic return and compensation method and system based on an electric energy metering data restoration model, and the method designs a distortion traceability algorithm of multi-dimensional feature fusion and improved SVM (Support Vector Machine), and extracts the characteristics of load features, environment features, packet loss rate, sampling delay distortion and the like. And load fluctuation-dominated distortion, environment interference-dominated distortion and coupling-dominated distortion can be accurately positioned. For multi-source distortion restoration, a load self-adaption-environment compensation-coupling correction three-level restoration model is provided, and through differential compensation of different load types, dynamic calibration of environment parameters such as temperature and humidity, electromagnetic interference and the like and coupling coefficient matrix optimization, the measurement data restoration precision is stably maintained to be 98% or above. According to the invention, through the research on the metering data distortion traceability-coupling distortion data reduction-dynamic return and supplement calculation-return and supplement result closed-loop optimization method, the precise repair of metering errors and the scientific calculation of electric quantity return and supplement in a complex scene are realized.

The invention discloses a distributed file backup method for a sonar database system, which belongs to the technical field of sonar data processing and comprises the following steps: acquiring file data containing underwater acoustic signal data from the sonar database system; fragmenting the file data to generate data blocks and dynamically adjusting the sizes of the data blocks; generating a unique identifier for the data block based on the content hash value and the metadata; selecting distributed storage nodes based on availability, storage capacity, network delay and geographical distribution factors; the transmission data block uses an encryption protocol; updating the storage position and state of the backup metadata record; periodically verifying the integrity and availability of the backup data; executing a data recovery process to recover the original file data; the dynamically adjusted backup policy is based on real-time operation requirements and data importance levels. According to the method, through distributed storage and dynamic optimization, the backup efficiency, the data security and the system reliability are improved, and the method is suitable for sonar data management in an underwater detection system.

The invention discloses a wireless network data reliability transmission system, which is used in the technical field of data transmission and comprises a slave gateway deployment and data aggregation module. A scheduling protocol and priority management module; a hierarchical caching and breakpoint resuming module; and a trend prediction optimization decision module. According to the invention, in combination with priority-based scheduling, link quality evaluation, data caching and retransmission mechanisms, reliable transmission of data with different priorities in a wireless network can be ensured, and normal transmission can be recovered through an efficient data recovery mechanism when the network is unstable; through real-time environment state estimation and prediction, communication parameters and resource scheduling can be dynamically optimized, network performance is effectively improved, and communication delay is reduced. The hidden state of a communication environment is estimated in real time through comprehensive analysis of link quality, event records and cache state data, future hidden state changes are predicted through a time sequence convolutional network, and potential performance degradation risks are recognized in advance.

The invention provides a data backup and recovery method and electronic equipment, which can be applied to the technical field of information. The data backup and recovery method comprises the following steps: in response to a detected backup trigger event, performing multiple times of backup on target data based on a preset backup strategy corresponding to the backup trigger event to obtain multiple pieces of backup data and backup metadata for respectively indexing the multiple pieces of backup data; storing the plurality of backup data in at least one of a local storage medium and a remote backup server, and storing the plurality of backup metadata in the remote backup server; in response to the detected backup recovery event, generating multiple pieces of candidate backup version information based on the multiple pieces of backup metadata; and in response to a recovery instruction for target backup version information in the multiple pieces of candidate backup version information, recovering target backup data corresponding to the target backup version information based on target backup metadata corresponding to the target backup version information.

Mechanisms are provided for identifying clean backups of a monitored computing system. A backup of a state of a computing system is generated. In response, these operations are performed: alert data associated with the monitored computing system is retrieved, where alert data is stored in response to patterns of data accesses indicating a possible cyber-attack on the computing system; a classification engine executes a classification operation on the alert data to determine if it indicates that the state of the monitored computing system was the target of a cyber-attack within a predetermined period of time prior to a time the backup was generated; if so, a first tag is generated for the backup indicating the backup to be corrupted; if not, a second tag for the backup is generated indicating the backup to be clean; and the first or second tag is stored in association with the backup.

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 discloses a carbon emission data restoration method and system, and relates to the technical field of carbon emission data restoration, and the method comprises the steps: obtaining to-be-restored carbon emission data, carrying out the data preprocessing of the to-be-restored carbon emission data, obtaining corresponding original carbon emission data, carrying out the data restoration of the original carbon emission data, obtaining corresponding initial correction data, and carrying out the restoration of the initial correction data; and performing correction processing on the initial correction data to obtain corresponding correction data, and optimizing the correction data according to a preset target function and the initial correction data to obtain corresponding target carbon emission data. The technical problems that according to a traditional carbon emission data restoration method, the influence of factors such as energy structure adjustment, policy change and extreme weather on carbon emission data is ignored, distribution has strong time-varying characteristics, the deviation between the restored carbon emission data and the actual situation is obvious, and the accuracy of carbon emission level evaluation is reduced are solved.

The invention relates to the technical field of multi-agent collaboration, in particular to a task execution method and system based on multi-agent collaboration, and the method comprises the steps: carrying out the semantic analysis and multi-granularity decomposition of a user task instruction, generating a subtask dependence structure, and storing the subtask dependence structure into a dynamic task pool; performing collaborative planning and rehearsal execution on the to-be-executed subtasks, generating context snapshots, executing Push, and writing the Push into a historical state stack; retrieving an evidence chain based on the domain knowledge base and extracting a fact triple set, performing consistency comparison based on structured evidence triples on the candidate reasoning paths, and outputting conflict confidence and consistency scores; when the consistency score is lower than a threshold value, triggering a projectile stack, physically clearing wrong branch intermediate data, recovering a historical context, injecting a negative feedback prompt to generate a new inference branch, and returning to continue rehearsal execution; if the verification is passed, outputting a result and entering a next subtask; therefore, the controllability and auditing performance of multi-agent cooperative task execution are improved.

A technique for recovering data following a failure of a first availability zone (AZ) of a cloud-based system includes creating a plurality of temporary instances in a second AZ of the cloud-based system. The technique further includes copying, by the plurality of temporary instances, recovery data from multiple cloud-based snapshots to a plurality of local volumes of the second AZ such that the temporary instances of the plurality of temporary instances copy respective portions of the recovery data in parallel. The technique still further attaching the plurality of local volumes to a storage-controller instance running in the second AZ.

The invention relates to the technical field of database management, in particular to an automatic database backup and recovery method and system based on artificial intelligence, and the method comprises the steps: collecting the operation data of a database in real time, and constructing a dynamic data feature model; dynamically generating a backup strategy through a backup strategy generation module based on the data feature model; executing backup operation according to the backup strategy, creating and updating a metadata index used for rapid recovery in the backup process, monitoring the backup state in real time, and automatically triggering a grading retry mechanism when backup abnormity is detected; automatically executing a recovery test, verifying the integrity and recoverability of the backup data, and if verification fails, triggering an alarm and performing backup again; and when a data recovery request is received, quickly positioning and recovering target data based on the metadata index and the transaction log, and monitoring a recovery state in real time in a recovery process. The rigidity of a traditional fixed strategy is overcome, and the backup efficiency is improved.

The embodiment of the invention discloses a data restoration method and electronic equipment, and the method is applied to conference equipment, and comprises the steps: obtaining a conference restoration directory based on conference restoration setting data, carrying out the data backup processing of the conference restoration directory, and obtaining target backup data, determining a data reduction triggering condition corresponding to the preset conference time information based on the conference reduction setting data, obtaining conference data related to the preset conference event, storing the conference data in a device storage space of the conference device, and determining the conference event when the data reduction triggering condition is satisfied according to the preset conference time information and the local time of the conference device. And performing restoration processing on the conference equipment based on the target backup data to release the equipment storage space of the conference equipment. Therefore, the technical problem that the conference efficiency is influenced by functional abnormality caused by gradual increase of data accumulation in the conference equipment because the user often ignores to delete the files after the conference equipment participates in the conference is solved.

The invention relates to the technical field of data processing, and discloses a data processing method, a readable medium and equipment. In the data processing method disclosed by the invention, a source device can newly add a search entry in a related user interface for recovering backup data, and obtains a keyword input by a user in the search entry. And then, the source device sends the keyword input by the user to the target device and receives target data corresponding to the keyword input by the user and obtained by the target device from the stored backup data of the source device, and the source device displays the target data. According to the embodiment of the invention, the source device can obtain the target data corresponding to the keyword input by the user from the target device, and the user selects whether data recovery needs to be carried out or not and selects the target data needing to be recovered or backup data corresponding to the target data, so that the use experience of the user is improved.

The invention relates to a data backup recovery method and device, computer equipment and a readable storage medium. The method comprises the steps that in response to a backup request for a database of a target service system, whether uncompleted service operation exists in multiple pieces of middleware associated with the target service system or not is detected, the backup request carries a test scene name and a service timestamp, and under the condition that the uncompleted service operation does not exist in the multiple pieces of middleware, the multiple pieces of middleware correspond to the test scene name and the service timestamp. The method comprises the following steps: acquiring and storing key cache data of a target service system, carrying out physical backup on a database, carrying out associated storage on the key cache data and physical backup data obtained by physical backup based on a test scene name and a service timestamp, and responding to a data recovery request for the database. And writing the key cache data into the corresponding middleware under the condition that the uncompleted business operation does not exist in the plurality of middleware, and carrying out physical recovery on the database based on the physical backup data. By adopting the method, the performance test efficiency can be effectively improved.

The invention relates to the technical field of distributed databases, and discloses a task execution method and device, computer equipment and a storage medium, and is applied to a distributed database, the method comprises the following steps: receiving an execution request for an operation and maintenance task of the distributed database uploaded by a user, carrying out content analysis on the execution request, and sending the analysis result to the user; acquiring initial state data of the operation and maintenance task; performing snapshot processing on the initial state data according to a preset snapshot execution strategy to obtain snapshot data of the operation and maintenance task; and executing the operation and maintenance task according to a preset task execution strategy, clearing the snapshot data when the execution of the operation and maintenance task is successful, and triggering a state rollback operation when the execution of the operation and maintenance task fails, so as to recover the current state data of the operation and maintenance task to the initial state data. In this way, the execution efficiency and reliability of the operation and maintenance task of the distributed database can be effectively improved.

This application relates to the computer field, and provides a data restoration method and apparatus for a storage device, to implement data restoration without losing data after an attack by ransomware, and reduce performance overheads and storage space overheads. The method includes: A storage device stores data in append write mode; determines first data in response to inaccessibility to target data, where the first data is data marked as invalid, and is data associated with the target data; and restores the first data.

1. The name of the design product: data forensics analysis AI host. 2. The use of the design product: AI host for data recovery. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view. 5. The design for which protection is sought contains colors.

The invention relates to a data recovery method and device and electronic equipment, and the method comprises the steps: under the condition of triggering recovery of a target storage object, traversing a storage medium according to a preset step length to obtain a data block in the storage medium, and determining second copy level metadata; determining candidate copies of the data group according to the first copy level metadata of the target storage object and the second copy level metadata of the data block; under the condition that at least one unlost copy or candidate copy exists in each data set of the target storage object, combining the unlost copies of the data sets with the candidate copies to form candidate data sets; combining the candidate data into candidate storage objects according to the sequence of the data groups of the target storage objects, and determining second object level metadata of the candidate storage objects; and under the condition that the first object level metadata is matched with the second object level metadata, taking the candidate storage object as a recovered target storage object. According to the embodiment of the invention, data recovery can be realized.

The embodiment of the present application relates to the technical field of photovoltaic communication test, and discloses a kind of distributed photovoltaic multi-protocol communication test method and related equipment, the method comprises: communication signal interference is simulated based on network signal attenuation simulator, whether communication protocol is switched according to communication quality parameter and parameter threshold value, communication data is cached based on multi-level data caching mechanism, communication interruption is detected, and interrupted data is continued to be transmitted based on congestion control algorithm, data loss is identified by missing data algorithm, data is completed by completion algorithm, and test report is generated according to data recovery rate, time efficiency index, resource consumption index, protocol adaptability index, protocol switching parameter, caching parameter, continuation parameter and data completion parameter.The embodiment of the present application can simulate the test of communication protocol switching, data caching, interruption identification, data continuation, data loss identification and completion under a variety of weak network environments, and has high test precision and good test effect.

To provide a data recovery system that can reliably read the original data, even if the original data is heavily corrupted. [Solution] The original data unit and redundant data units prepared for each column are read from the data code, and the damaged original data unit is restored from the undamaged redundant data unit and the undamaged original data unit for each column of the data code through calculations using a 32-bit Galois field matrix. This configuration improves the probability of restoring the original data unit (fault tolerance) and the accuracy of reading the data code.

A cross-platform data migration method and a cross-platform data migration system include determining that a first database is compatible with a second database, receiving a user request associated with an instruction to migrate data from the first database to the second database, determining that backup data corresponding to a current state of the first database is available, mounting the backup data onto the second platform via a distributed file system protocol, converting the backup data from the source endian format to a target endian format, and restoring the backup data in the target endian format to the second platform.

Disclosed in the embodiments of the present application are a data recovery method, system and apparatus, and a computer-readable storage medium and a program product. The method comprises: in the current scheduling period, acquiring use information of a storage unit in a storage unit cluster, wherein the use information comprises a recovery state and a historical recovery time; on the basis of the recovery state, determining, from the storage unit cluster, at least one first storage unit which is not in a data recovery state; when the recovery state represents being in the data recovery state, determining, to be a second storage unit, the storage unit corresponding to the recovery state; on the basis of the historical recovery time, determining a target storage unit from the at least one first storage unit; stopping a data processing service of the target storage unit, executing a data recovery operation by means of the target storage unit, and updating the recovery state of the target storage unit; and stopping a data recovery operation of the second storage unit, and recovering the data processing service of the second storage unit. By means of the present solution, the garbage recycling efficiency and the storage cluster performance can be improved.

The invention discloses a multi-camera linkage monitoring method and system, and the method comprises the steps: obtaining the first image data of a first camera, and enabling the first image data to comprise the data of a target person; performing analysis based on the character data and a pre-trained extraction model, and determining character identification data; sending the character identification data to a second camera, collecting second image data of the target character by the second camera, and performing data compression based on the character identification data to form compressed data; receiving compressed data of the second camera, performing data restoration based on the character identification data to obtain restored data, and performing monitoring analysis based on the first image data and the restored data; according to the scheme, the data volume transmitted by the camera can be reduced.

The invention discloses a WiFi probe ping-pong data restoration method based on a Transformers architecture. The method comprises the following steps: constructing expressions of input data and output data; wiFi probe ping-pong data are collected, and data preprocessing is carried out based on dynamic coordinate system normalization of a track center; constructing a WiFi Transform model, taking the preprocessed data as input, and mapping a high-dimensional vector output by a decoder into a two-dimensional coordinate in an output layer; a loss function is designed to carry out training on the WiFi Transform model; and realizing the reduction of the WiFi probe ping-pong data based on the trained model. According to the method, the WiFi probe data is restored into the real track data as a sequence-to-sequence translation process, so that the ping-pong effect problem in a WiFi positioning system is effectively solved.

This application discloses a method and electronic device for solid-state drive (SSD) fault recovery, relating to the field of data recovery technology for storage devices. The fault recovery method includes: first, obtaining the SSD's status flag; if a fault is determined based on the status flag, setting the SSD to read-only mode and traversing multiple block units to obtain their types and write timestamps; then, determining multiple target block units based on the target type and the types of the multiple block units, and determining a target block unit list based on the write timestamps of the target block units; and finally, restoring the metadata to a first-level table based on the logical addresses of the metadata stored in the target block units in the target block unit list. This first-level table represents the mapping relationship between logical addresses and physical addresses. Therefore, this application solves the problem of data security and integrity not being guaranteed when an SSD fails, greatly improving data recovery efficiency and the reliability of the recovered metadata.

The application provides a data processing method, device, system, equipment and readable storage medium, relates to the technical field of block chain, and the method comprises the following steps: when the data stored by a first node is behind the data stored by a second node, obtaining the difference value between the latest batch of the data stored by the first node and the latest batch of the data stored by the second node, obtaining recovery data according to the difference value, and recovering the data stored by the first node according to the recovery data so that the data stored by the first node is the same as the data stored by the second node. In the technical scheme, different recovery data is obtained through the difference value, the data of the first node is recovered, in the scene that there are various different data batch spans between the first node and the second node, the data recovery can be flexibly and effectively realized, the first node can be ensured to be timely and quickly consistent with the data stored by the second node, and the stability of the distributed system is improved.

Methods and apparatuses for synchronizing data recovery files in cloud-based database management platforms include a server that allocates physical storage media for database management platforms hosted in a cloud computing environment and attaches a source database management platform in a first region of the environment to the allocated storage media. The server attaches a target database management platform in a second region of the environment to the allocated storage media. The server establishes a periodic replication job between the source database management platform and the target database management platform, including validating change files associated with differential data changes in a primary database instance and transmitting the validated change files to the target database management platform for replication in a secondary database instance.

The invention discloses a shale gas well productivity prediction method and system based on a mask convolutional neural network, and relates to the technical field of oil and gas field development and artificial intelligence. The method comprises the steps that firstly, geological, drilling and fracturing multi-factor time series data of a shale gas well are obtained and preprocessed; dividing the preprocessed data into time window samples through a sliding window, and reconstructing the time window samples into a two-dimensional image format; a mask convolutional neural network model is constructed, the model shields data of a to-be-predicted time point through a mask module, and a prediction task is converted into an image generation task; performing depth feature extraction and data restoration on the image with the mask by using a backbone network module and combining common convolution, expansion convolution, a multi-scale residual structure and an attention mechanism; and finally, a prediction value of the masked position is extracted through a decoding module, and a productivity prediction result is obtained. According to the method, time sequence prediction is innovatively converted into an image generation problem, the powerful feature extraction capability of the convolutional neural network is fully utilized, the limitation of a traditional method on processing high-dimensional and nonlinear time sequence data is effectively overcome, and the precision and reliability of shale gas well productivity prediction are remarkably improved.

As part of a data restore operation from a backup data store, a system reads data objects of the backup data store in parallel into a buffer, which includes reading chunks of a first data object into the buffer. The data objects are provided from the buffer to a data compressor that incrementally compresses the data objects as the data objects are received at the data compressor to produce compressed data objects. The compressed data objects are transferred in parallel to a target data store as part of the data restore operation.

The application discloses an Oracle database management method and device based on VMware snapshots, equipment and a storage medium, and the method comprises the following steps: creating a target virtual machine on a VMware virtual platform, and restoring the target virtual machine based on full backup of an Oracle database; when full backup of the target virtual machine is restored, performing snapshot processing on the target virtual machine to generate a first VMware snapshot of the target virtual machine; when incremental backup is performed, obtaining incremental data of the Oracle database in a current backup stage, wherein the current backup stage is a stage between current backup and adjacent previous backup; performing incremental restoration in the target virtual machine to obtain a database copy of the target virtual machine when the adjacent previous incremental backup is completed, and restoring the incremental data into the database copy; and when the restoration processing is completed, updating the first VMware snapshot based on the incremental data. The backup and restoration efficiency is significantly improved.