801 results about "Data recovery" patented technology

The invention relates to the technical field of network and information security, in particular to a zero-trust multi-party security data exchange method, which comprises the following steps of: generating a zero-trust token and a capability authorization bill and constructing context description data; authentication encryption is performed on the plaintext fragment, attribute-based encryption is performed on the data one-time key, and a policy bearing ciphertext container is assembled; in the trusted execution environment, authentication decryption is completed through a one-time secret key of data recovery through joint challenge and threshold deblocking, or strategy migration and transfer are achieved through proxy re-encryption; and aggregating the decryption event and the forwarding event by vector commitment, generating a time anchor, and mapping the time anchor into a next round of random base. According to the invention, fine-grained authorization of the key layer, no plaintext transfer, event-level verifiable auditing and rapid revocation are realized.

The invention discloses a row-level data recovery method and device for a damaged file of a GoldenDB database, and the method comprises the following steps: S1, scanning a to-be-recovered GoldenDB data file, and recognizing and caching all data pages; s2, on the basis of metadata of the data pages, cluster index leaf node pages containing user data are screened out from the cached data pages; s3, for each screened leaf node page, analyzing an internal record organization structure of the leaf node page, and performing row-level data recovery; the row-level data recovery comprises the steps of traversing user records according to a virtual record pointer, and performing cross check and recovery on a traversal path in combination with a page directory slot so as to extract and mark the user records one by one; and S4, outputting all the recovered row-level data.

The present application relates to the technical field of storage, and provides a method and apparatus for determining an optimal read voltage parameter of a flash memory, and a flash memory device. The method comprises: on the basis of a linear relationship model between a read retry voltage offset value and a bit flip count, acquiring a new read retry voltage offset value corresponding to a minimized predicted bit flip count of the flash memory; determining whether data can be successfully read under the new read retry voltage offset value; if yes, adding the new read retry voltage offset value to the header of a read retry offset table to form a new read retry offset table; and on the basis of the new read retry offset table, updating the linear relationship model by means of an adaptive learning model. By means of the efficient and adaptive voltage parameter determination method, the present application can improve the success rate of data recovery and reduce performance loss.

The invention relates to the technical field of data processing, in particular to a traffic data completion method and device based on a time autoregression low-rank tensor, and the method comprises the following steps: obtaining incomplete traffic data; constructing a three-dimensional tensor to represent incomplete traffic data, and obtaining an observation index set and a tensor matrix; taking a low-rank tensor completion model based on rank minimization as a framework, and introducing time autoregressive regularization and truncation weighted nuclear norms to obtain a low-rank tensor completion model; performing problem decomposition solving on the low-rank tensor completion model on the basis of an ADMM framework to obtain four variable parameters, namely, a variable parameter, a variable parameter and a variable parameter; and iteratively updating the variables according to the sequence until a preset convergence standard is reached, and outputting the complemented complete traffic data. According to the method, the time change is introduced into the completion of the three-order tensor as a new regularization item, so that the historical information can be learned during data recovery, the low-rank performance of the completed tensor can be ensured, and a complex missing scene can be better processed.

A method performed by a generative adversarial network, GAN, based system for outputting an estimated adversarial data, EAD, of an attack on an artificial intelligence, AI, model is provided. The method includes classifying a data point from an input data as (i) a real data point, or (ii) a manipulated data point. The method further includes, when the classification is a manipulated data point, outputting the estimated adversarial data including a difference between the manipulated data point and the data point from the input data. The method may further include using the EAD to build a data recovery module.

Linear unretimed interfaces lack clock and data recovery and retiming circuits implemented on a sophisticated digital signal processor. When the interface is not a retimed interface, it can be especially useful to extract some information about the link to allow for debugging and optimization of system deployment. An efficient solution can be implemented in unretimed interfaces to compute metrics such as the impulse response and signal histogram. Having the metrics allows for the solution to check and monitor the quality and the status of the link. Based on the link quality and status information, it is possible to address non-idealities and optimize performance of the unretimed interfaces and the link.

The invention relates to the technical field of file storage management, and discloses a Lustre architecture-based high-performance file storage and processing method and system, the method comprises the following steps: obtaining spatio-temporal characteristics of file access; predicting a popularity value of the file based on the spatial-temporal characteristics; determining a storage strategy of the file based on the popularity value of the file; carrying out distributed storage on the file based on the storage strategy, and continuously detecting a node state; if it is detected that the node load is unstable, adaptive data migration is carried out on the node with the unstable load; if the node is detected to have a fault, generating a data recovery path based on the three-dimensional topological coordinates of the node, and migrating a file stored in the node having the fault based on the data recovery path; according to the method, the storage strategy is determined through the file popularity value, and the abnormal condition of the node is efficiently processed, so that the file storage and processing performance and efficiency are comprehensively improved.

The invention provides a sensor data recovery method and system based on mask perception space-time modeling, and belongs to the technical field of Internet of Things and intelligent sensing data processing. The method comprises the following steps: modeling a missing position into a trainable potential vector representation through an adaptive missing representation module, and avoiding noise introduced by traditional zero filling or mean filling; a missing perception space-time decoding module is adopted, and a dynamic weight distribution mechanism of mask constraint is combined in the decoding process, so that information is effectively prevented from being excessively smooth; designing a space-time dual-channel feature aggregation unit, and capturing spatial dependence and time sequence dependence between the sensors at the same time; and finally realizing accurate completion of a large-scale space-time sensor matrix through an output recovery unit. According to the method, the accuracy and robustness of sensor data restoration can be remarkably improved, the reliability of subsequent monitoring, prediction and anomaly detection is enhanced, and the method has wide engineering application value.

The invention discloses an incomplete multi-mode smooth contrast clustering method based on information interpolation, which comprises the following steps of: firstly, modeling a missing view into multivariate Gaussian distribution based on distance weighted nearest neighbor by utilizing a view interpolation mechanism based on statistical information, and carrying out interpolation on the missing view to obtain a complete multi-view data set; secondly, using an encoder to extract potential features, capturing global structure information of multiple views through an FFN-Attention-FFN structure, and extracting local structure information of the multiple views through a graph convolutional network; thirdly, reconstructing a view by using a graph decoder; and finally, generating a clustering distribution result by using the MLP. According to the method, a view interpolation mechanism based on statistical information is introduced, the influence of a weak correlation view on a completion result is reduced by introducing distance weighting, and the data recovery quality is improved; the FFN-Attention-FFN structure is combined with the graph convolutional network, so that the global and local structure information of the data can be effectively captured; and negative sample pairs are expanded by adding Gaussian noise, so that sample distribution is smoother.

The embodiment of the invention provides a virtual machine migration method and device, a cloud computing system and electronic equipment, and relates to the technical field of cloud computing, and the method comprises the steps that a first physical machine interrupts running of a first virtual machine in response to a migration instruction of the first virtual machine, notifying the CXL switch to remove a first mapping relation between the first physical machine and the first memory space, and sending state recovery data to the second physical machine; the CXL switch relieves the first mapping relation and establishes a second mapping relation between the second physical machine and the first memory space; the second physical machine recovers and operates the first virtual machine based on the state recovery data and the memory data in the first memory space, and sends a virtual machine recovery operation notification to the first physical machine; and the first physical machine destroys the state recovery data in response to the virtual machine operation recovery notification. By applying the scheme provided by the embodiment of the invention, the migration efficiency of the virtual machine can be improved.

The invention discloses a method for improving data transmission bandwidth through an FPGA. The method comprises the steps that a data packaging module of a detector main control board sends data to be transmitted to a multi-channel GTP sending end in parallel; the data acquisition card receives the data of the corresponding channels through the multi-channel GTP receiving end and recovers Data and KCOD of each channel; an FIFO read-write control module of the data acquisition card writes data recovered by multiple channels into asynchronous FIFOs corresponding to the channels through write logic, and data buffering is carried out; the FIFO read-write control module simultaneously reads cache data of a plurality of asynchronous FIFOs through read control logic to realize cross-clock domain synchronization of multi-channel data; performing CRC (cyclic redundancy check) and processing on the read multi-channel data to obtain synchronous effective transmission data; and a single-channel GTP is upgraded to a dual-channel GTP or a multi-channel GTP, so that the data transmission bandwidth is improved, and normal operation of the FPGA chip is ensured.

The embodiment of the invention discloses an application upgrading method and device, equipment, a terminal, a storage medium and a program.The method is applied to an operation system of a WebAssembly virtual machine and comprises the steps that a first upgrading instruction initiated by a to-be-upgraded application is received; the first upgrading instruction comprises application data retention indication information of the to-be-upgraded application; obtaining an old-version application corresponding to the to-be-upgraded application and an application data object of the old-version application according to application data retention indication information included in the first upgrading instruction, and storing application data in the application data object of the old-version application; receiving a second upgrading instruction initiated by the to-be-upgraded application; and recovering the application data in the application data object of the old-version application to the application data object of the new-version application corresponding to the old-version application according to the second upgrading instruction. According to the technical scheme provided by the embodiment of the invention, the application upgrading flexibility in the operation system of the WebAssembly virtual machine can be improved.

A method and system for efficient data recovery via change block tracking and replication comprising storing data using secured and immutable storage snapshots from a plurality of first devices on a plurality of storage arrays via a first network path and a second network path, determining a condition of data loss, power loss, or a cyber compromise event, and based on determining the condition, instantiating recovery of data using the secured and immutable storage snapshots from the plurality storage arrays via a third network path.

The invention relates to a data recovery method and device, computer equipment, a computer readable storage medium and a computer program product. The method is applied to a distributed system, the distributed system comprises a plurality of node groups, each node group comprises a storage data block and a verification data block of a storage node, and the method comprises the following steps: detecting each node group, and if a fault node exists in a target node group, judging whether the fault node exists in the target node group; obtaining a target verification data block and a target storage data block in a target node group where the fault node is located; the target verification data block is obtained by encoding the total storage data block in the target node group; and performing decoding processing according to the target verification data block and the target storage data block to obtain recovery data of the fault node. By adopting the method, the data recovery efficiency can be improved.

The invention discloses a filter circuit, a clock data recovery method, a circuit and a receiver, and belongs to the technical field of signal processing. The filter circuit comprises: a voting module configured to vote according to at least two groups of input data to obtain a target voting result, and send the target voting result to a selection module, each group of input data comprising a clock phase and data, and the target voting result indicating a relative relationship between the clock phase and the data; the selection module is configured to determine a clock adjustment parameter according to the target voting result, obtain a target adjustment coefficient and send the clock adjustment parameter and the target adjustment coefficient to the processing module; the processing module is configured to obtain recovery parameters according to the clock adjustment parameters and the target adjustment coefficient, and the recovery parameters are used for recovering the clock and the data. The obtained recovery parameters are more accurate, noise is effectively suppressed, and the accuracy of recovering clocks and data based on the recovery parameters is improved.

The invention discloses a mapping table reconstruction method and storage equipment. The method comprises the following steps: determining a final check point in a storage medium; determining a target mapping table needing data recovery based on the final check point; sequentially reading metadata of each data block in the storage medium according to the last check point, wherein the metadata comprises a logic address of currently written data and a historical physical address corresponding to the logic address when the logic address is written last time; determining a target block matched with the target mapping table in the data block according to the logic address; constructing a data writing linked list of the logic address according to the historical physical address of the target block; and reconstructing the target mapping table according to the data write-in linked list. According to the invention, the reconstruction efficiency of the mapping table can be improved while accurate reconstruction of the mapping table is ensured.

The invention relates to the technical field of power system automation, and discloses a distributed photovoltaic spatio-temporal data recovery and unsupervised clustering method and system.The distributed photovoltaic spatio-temporal data recovery and unsupervised clustering method comprises the steps that observation data of a distributed photovoltaic system are collected, and the observation data comprise historical distributed photovoltaic output time sequences; the collected historical distributed photovoltaic output time sequence is used as an input signal to be transmitted to each module of the GRAIL framework so as to drive a network to jointly learn time sequence dynamic characteristics and a clustering structure; wherein the GRAIL framework is a closed-loop iterative structure, and comprises a clustering sensing data generation module, a latent feature representation module and a self-adaptive clustering and refining module. The method can be widely applied to distributed photovoltaic station operation monitoring and abnormity identification scenes, and intelligent regional state recovery and mode grouping are realized.

The invention relates to the technical field of digital storage, and provides a method and a system for recovering long-term storage failure of a mobile terminal, through the design of a built-in independent power supply, a startup disk can still supply power continuously when the mobile terminal is in a power-off state, and the limitation of traditional OTG (On-The-Go) equipment is broken through. The read-write state of the data block of the flash memory chip is automatically monitored through the storage controller, and a health report is generated in real time; and when the early warning data block is detected, a bidirectional communication protocol is triggered. In a data backup link, a boot disk adopts a hierarchical check mechanism to generate CRC codes for each data block for centralized storage, and meanwhile, an overall SHA-256 code is calculated and double-end synchronization is performed. And in the recovery stage, the backup integrity is ensured through SHA-256 code comparison, then the data accuracy is verified block by block through CRC codes, and finally, the backup file is automatically migrated to the nonvolatile partition. The seamless closed loop from fault detection to data recovery is realized aiming at the system guidance problem after long-term storage of the equipment.

The embodiment of the invention relates to the technical field of photovoltaic communication testing, and discloses a distributed photovoltaic multi-protocol communication testing method and related equipment, and the method comprises the steps: determining whether to switch a communication protocol or not according to a communication quality parameter and a parameter threshold value based on the interference of a network signal attenuation simulator on a communication signal, the method comprises the following steps: caching communication data based on a multi-level data caching mechanism, detecting communication interruption, continuously transmitting interrupted data based on a congestion control algorithm, identifying data loss through a missing data algorithm, and complementing the data through a complementing algorithm. And generating a test report according to the data recovery rate, the time efficiency index, the resource consumption index, the protocol adaptability index, the protocol switching parameter, the cache parameter, the continuous transmission parameter and the data completion parameter. According to the embodiment of the invention, tests of communication protocol switching, data caching, interruption identification, data continuous transmission, data loss identification and complementation in various weak network environments can be simulated, the test precision is high, and the test effect is good.

The invention discloses a data recovery method and electronic equipment, and relates to the technical field of storage systems.The data recovery method comprises the steps that a virtual disk array is created according to virtual disks, and the virtual disks in the virtual disk array are divided into data disks and verification disks; writing the write-in data of the write-in request into a data disk, obtaining verification information according to the data written into the data disk, and writing the verification information into a verification disk; and if the abnormal data exists, performing data reconstruction on the abnormal data according to the data except the abnormal data in the virtual disk array and the verification information to obtain repaired data. The problems that a data error correction mode of a storage system is single, only underlying data processing abnormity can be sensed, but abnormal data cannot be recovered can be solved. According to the method, when any virtual disk in the virtual disk array has abnormal data, the abnormal data can be recovered and corrected by means of data reconstruction, and the data stability and data security of a storage system are guaranteed.

A receiver includes an analog to digital converter circuit, a phase detector circuit, a digital loop filter circuit, a phase interpolator circuit, and a bias adaption circuit. The analog to digital converter circuit is configured to convert a first signal into a second signal according to a clock signal. The phase detector circuit is configured to detect a phase of the second signal to generate a phase detection signal. The digital loop filter circuit is configured to scale the phase detection signal with a proportional path gain coefficient and a bias value to generate a third signal. The phase interpolator circuit is configured to generate the clock signal according to the third signal. The bias adaptation circuit is configured to accumulate the phase detection signal to generate the bias value.

The invention discloses a data reconstruction method and device, electronic equipment and a storage medium, and relates to the technical field of data storage and recovery, and the data reconstruction method comprises the steps that under the condition that a to-be-reconstructed disk exists in a distributed storage system, the redundancy of the to-be-reconstructed disk is determined based on state data of the to-be-reconstructed disk; determining a target redundancy level corresponding to the redundancy of the to-be-reconstructed disk from a plurality of preset redundancy levels; different redundancy levels correspond to different erasure code types; the erasure code types corresponding to different redundancy levels represent different combinations of data recovery rates and storage resource occupation proportions; and switching the erasure code type of the to-be-reconstructed disk to a target erasure code type corresponding to the target redundancy level, and according to the target erasure code type, transmitting the fault data block in the to-be-reconstructed disk to a specified disk for data reconstruction. The problem that data recovery performance, resource consumption and network bandwidth resource occupation cannot be dynamically balanced in the data reconstruction process in the prior art is solved.

A method, computer program product, and computer system for managing a quorum device for a storage system having network of storage controllers of storage clusters. includes: using a first storage controller as a volume-based quorum device 201 for a second storage controller, wherein the first storage controller is aware of being treated as a quorum device; taking snapshots of cluster state metadata 206 at known points and saving as quorum volumes; and recovering the storage cluster from the cluster state metadata in the event of a failure 207. The method may also include selecting recovery points for taking snapshots depending on the type of cluster state metadata, it may also include integrating storage-centric actions into a control flow of the quorum device. The method may create safeguarded copies of the metadata, and may store multiple copies for point-in-time recovery.

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.

Embodiments of the invention provide an instruction processing method and apparatus, a computer device and a storage medium. The method comprises the steps of obtaining a setting instruction and a vector calculation instruction from a preset instruction local memory or an instruction buffer; updating a preset shadow register according to the setting instruction to obtain a first update value; performing data recovery on the first update value by using a preset real register to obtain a second update value; and executing the vector calculation instruction according to the second update value. According to the method, the preset shadow register is used for speculative execution according to the instruction of the assembly line, an update value is obtained in advance, and when the instruction needing to be scoured is executed, the wrong update value is backed up and recovered by using the preset real register, so that the register values of the shadow register and the real register are kept consistent; therefore, the performance and the efficiency when the vector calculation instruction is executed are improved.

The invention discloses a data aggregation method with fault tolerance and privacy protection functions, and relates to the technical field of smart power grid data security. The method comprises the following steps: setting security parameters, and issuing public parameters; enabling the intelligent electric meter to randomly select a first private key and a blind factor to calculate and publish a first public key, and enabling the aggregation gateway to randomly select a second private key to calculate and publish a second public key; encrypting the collected power consumption data of the user by using the intelligent electric meter to generate a data report; when the aggregation gateway receives the data report, executing a traditional data aggregation algorithm, and if the data report receives the data report, executing a data aggregation algorithm supporting fault tolerance to generate an aggregation ciphertext; and verifying the validity of the data and the time in the data center, and performing data recovery by using the private key. According to the method, data aggregation with fault-tolerant and privacy protection functions can be realized for two application conditions of a fault ammeter and a fault-free ammeter.

The invention provides a cloud instance login method and device, electronic equipment and a storage medium, and relates to the technical field of cloud computing. The cloud instance login method comprises the steps that an access credential is generated according to a login request, and the access credential comprises the access authority of a cloud storage server; acquiring historical user data from the cloud storage server according to the access credential; and loading the cloud instance in the corresponding state according to the historical user data. According to the method, the cloud instance does not need to be completely restarted or initialized after the user logs in, the operation environment can be directly recovered based on historical user data, the cold start waiting time is shortened, seamless recovery of personalized configuration, application state and operation progress is supported, the user is located at the last leaving position every time the user logs in, and the natural fluency of continuous use is improved.

The invention discloses a data recovery method and device, electronic equipment and a storage medium, and the method comprises the steps: monitoring the resource state of a distributed storage system under the condition that a data recovery request of a to-be-recovered node is received; according to the network resource state, the hardware resource state and the load state, the number of nodes participating in data recovery at the same time, the physical range of the nodes called by the data recovery, the coding mode adopted by the data recovery and the memory resources occupied by the data recovery are determined; determining a data recovery strategy according to the number of the nodes participating in data recovery at the same time, the physical range of the nodes called by the data recovery, the coding mode adopted by the data recovery and the memory resources occupied by the data recovery; and executing the determined data recovery strategy to recover the data of the node to be recovered. The resource state of the storage system can be considered, the recovery strategy most suitable for the current resource state of the storage system is combined based on the resource state, and the data recovery efficiency is improved.

A Redundant Array of Independent Disks (RAID) scheme can be used to allow recovery from a memory failure. RAID 6 can be used to recover data from up to two catastrophic failures. Typically, a hardware encoder is used to generate parities of the RAID 6 protection scheme, and a separate hardware decoder is used in the data recovery process. In an example data storage device described herein, some of the components of the hardware encoder are used to perform the data recovery process, thereby eliminating the need for a separate, additional hardware component.

The invention discloses a medical training data quality inspection method, related equipment and a program product, and relates to the technical field of artificial intelligence. When it is determined that the first reasoning result corresponding to the first problem in the medical training data contains error information, the probability distribution of the token level in the first reasoning result is predicted through a large model in the medical field. According to the method, the error reasoning model is configured, the error reasoning model is trained by adopting a problem sample in the medical field and an error reasoning result, the model simulates the token selection preference of error reasoning, and the error reasoning model performs reasoning on the first problem to obtain the probability distribution of the token level in the second reasoning result. According to the method, the two probability distribution differences of the token level can be compared, key information most possibly containing errors in the first reasoning result can be intelligently recognized, the purpose of automatically positioning potential error points in the first reasoning result is achieved, the modification direction is pointed out for data recovery work, and the data recovery work difficulty is reduced.