294 results about "Data location" patented technology

The invention relates to the technical field of computers, in particular to a heterogeneous computing power scheduling method and device, equipment, a storage medium and a product. The method comprises the following steps: generating an equipment topological graph based on equipment information in a node resource pool; performing partition management on the computing devices in the device topological graph; based on a partition management result, analyzing the to-be-calculated task through a preset flow gateway, and determining a task request data position, a task scale and a task feature; determining a to-be-calculated node according to the task request data position, the task scale and the task feature; and distributing the to-be-calculated task to the to-be-calculated node, and generating a target scheduling strategy based on the real-time performance index and the historical execution data of the to-be-calculated node. According to the method, the utilization efficiency of computing resources is improved by generating the equipment topological graph and performing partition management, the scheduling strategy is optimized by combining real-time performance data, it is ensured that scheduling optimization can be performed according to the real-time state, and the effect of heterogeneous computing power scheduling is improved.

The invention relates to the technical field of data processing, and discloses a cold and hot data exchange method and system based on optical storage and a storage medium. The method comprises the following steps: performing access feature acquisition and analysis on data in the optomagnetic hybrid storage system, calculating an access life cycle factor, generating a logic interval heat evaluation result, performing temperature grading, formulating a cold and hot data placement strategy, generating a data placement mapping table, executing batch migration according to priority, and updating a data position record. According to the method, the problem of how to realize logic interval hot degree accurate identification, temperature grade dynamic grading, storage mapping optimal matching and batch migration task efficient organization under the optomagnetic hybrid architecture is solved.

The embodiment of the invention provides a memory access method and device, electronic equipment and a readable storage medium. The method comprises the following steps: receiving a cache line access request; extracting label information from a target memory address corresponding to the cache line access request, wherein the label information comprises a shared label, a private label, a group index, inter-block offset and intra-block offset; querying whether the cache line access request hits the L1 cache or not based on the label information; the group index is used for determining a target group, the shared tag and the private tag are used for determining a target cache line in the target group, and the inter-block offset is used for determining a target cache block in the target cache line; and if the cache line access request hits the L1 cache, determining a target data position in a hit target cache block based on the in-block offset, and executing a corresponding memory access request based on the target data position. According to the embodiment of the invention, on the basis of ensuring the data access efficiency, the storage space of the cache line is fully utilized, and the waste of the cache space is reduced.

The invention provides an automatic data fitting method and system combined with equipment position calibration, and the method comprises the steps: firstly collecting a multi-source sensor data set of target equipment in a three-dimensional space, including equipment motion track data, position coordinate offset and environment interference parameters, carrying out the feature extraction of the multi-source sensor data set, and carrying out the feature extraction of the target equipment; generating a target feature set containing spatial position correlation features, dynamic trajectory fluctuation features and environment coupling features, then calling a pre-trained adaptive fitting model, inputting the target feature set to perform dynamic parameter matching, and generating an initial calibration parameter set; and generating a dynamic path sequence of equipment position calibration based on the initial calibration parameter set, triggering the equipment to execute automatic position calibration according to the sequence, and feeding back calibrated verification data to the model update parameters, thereby improving the precision, real-time performance and adaptivity of equipment position calibration.

The invention discloses a memory management method, electronic equipment, a storage medium and a computer program product, and relates to the technical field of computers. The cold and hot marks are set for the memory pages according to the cold and hot scores, memory data of different cold and hot grades can be distinguished, whether data transfer is conducted on the memory data of the memory pages or not is judged by comparing with the types of the storage media where the memory pages are located, and energy consumption can be reduced by transferring the data to the storage media matched with the cold and hot marks; whether the current operation mode of the target storage medium supports data transfer or not is judged before data transfer, the target storage medium is adjusted to be in the operation mode supporting data transfer, all the storage media do not need to be kept in the operation mode supporting data transfer all the time, the lowest energy consumption of the operation mode of the storage medium can be kept, and the operation efficiency is improved. The energy consumption can be reduced by combining the dynamic adjustment of the data position according to the load and the static power consumption management.

The invention discloses a computer batch data storage method and system based on a block chain, and relates to the technical field of computer batch data storage.The computer batch data storage method comprises the steps that computer batch data are analyzed through a data classification method, the computer batch data are divided into hot data and cold data according to the access frequency, and a classified data set is obtained; performing encryption processing on the classified data set by adopting a homomorphic encryption method to obtain an encrypted data set; distributing the encrypted data set to a corresponding storage level by adopting intelligent contract definition logic to obtain a data record with a distributed storage position; creating a detailed index record and storing the detailed index record on the block chain to obtain an index record on the block chain; determining a data position when the specific data is retrieved by adopting a method of querying the index record on the block chain, and obtaining verified data; and checking the integrity of the data and the running state of the system by adopting a security auditing method to obtain an auditing result, and adjusting a storage strategy based on the auditing result.

The invention discloses a multi-modal robot interaction system, and relates to the technical field of robots, the system comprises a robot subsystem and a cloud processing subsystem which are in communication connection with each other, the robot subsystem comprises a multi-modal sensing module and an interaction execution module, and the cloud processing subsystem comprises a cloud processing module. The multi-mode sensing module is used for collecting target data of at least one target user and sending the target data to the cloud processing module, and the target data comprises at least one of touch data, distance data, posture data, position data, action data and voice data; the cloud processing module is used for analyzing the target data, generating an interaction instruction and sending the interaction instruction to the interaction execution module; and the interaction execution module is used for receiving and executing the interaction instruction, so that the higher expectation of the user in the aspects of emotion accompanying and personalized service is effectively met.

The invention relates to the technical field of electric vehicle charging pile management and distribution, and discloses a new energy charging pile management and distribution method and system, and the method comprises the steps: collecting charging user data, position data and environment data, and carrying out the preprocessing; and analyzing the preprocessed data, and constructing a prediction model of the charging demand of the user. And calculating the load condition of each charging pile according to a demand result predicted by the model, and adjusting a charging pile distribution strategy. According to the invention, through the steps of data preprocessing, charging demand prediction, load calculation and distribution strategy optimization, real-time monitoring and feedback and the like, intelligent management of charging pile resources is realized. The method plays a key role in improving the efficiency of the charging service, reducing overload and idle phenomena, optimizing the user experience and the like. A more intelligent, efficient and personalized charging pile management and distribution system is provided for electric vehicle users, the utilization rate of charging pile resources is effectively improved, the waiting time of the users is shortened, and the flexibility and stability of the system are enhanced.

The invention discloses a computer data remote security management system based on block chain encryption, relates to the technical field of data security, and solves the problems that an existing verification mechanism is difficult to resist man-in-the-middle attack, and an attacker can bypass detection by tampering data and forging a verification code. According to the invention, through feature matching and dynamic interval feature calculation of the block chain storage node, dual binding of the transmission channel and the storage node is realized; in combination with randomization processing of virtual data positions, check codes have high uniqueness and reverse cracking resistance, man-in-the-middle attack and data forgery risks are effectively resisted, and a dual check code comparison mechanism before and after data transmission is realized; the verification code is generated before transmission, the identification code is generated after transmission, whether the data is tampered or lost can be accurately detected through consistency verification of the verification code and the identification code, and the integrity of the data in the remote transmission process is ensured.

The invention provides a data processing method and device for a stream processing framework, equipment and a medium, and relates to the technical field of big data, in particular to the technical field of data warehouses. The method comprises the steps of pausing a real-time task of a stream processing framework in response to a first task control instruction, obtaining a first consumption data position corresponding to the real-time task when the real-time task is paused, and starting a first offline batch task, the first task control instruction is sent based on a real-time monitoring result of a real-time task state and consumption delay data in the streaming processing framework; after the capacity expansion operation is executed on the stream processing framework, the real-time task is started again, so that the real-time task starts to process data from a corresponding second consumption data position when the real-time task is started; wherein the first offline batch task is used for processing data between the first consumption data position and the second consumption data position. According to the invention, an integrated data warehouse of real-time stream and offline stream can be realized, and the concurrency and accuracy of data are improved.

Performing charge / showback operations in a large-scale data system by scanning multiple data sources to identify data objects for processing as a unitary group with respect to common characteristics that have an impact on finances within the system. Metadata of the identified data objects are stored in a dynamic dataset that defines a single data access unit for the referenced data objects. The system processes a user query regarding cost allocations, cost forecasts, and resource usage of respective groups within an organization. The query initiates a charge-back or show-back operation that allocates costs associated with each respective usage of resources by a department or cost center, and accesses the referenced data objects through the dataset as a single unit based on data content rather than data location in a file directory of the system.

The invention provides a game strategy planning method and system, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence, the method is applied to multiple agents, and the multiple agents comprise at least one unmanned aerial vehicle and at least one unmanned ship. According to the method, environment data, attitude data, position data and game party data of a target game region are acquired in real time, an accurate environment model and a state and action space are constructed, an objective function of a current task is efficiently solved by applying a Monte Carlo algorithm and a deterministic strategy gradient algorithm, a game countering strategy set is generated, and the game countering strategy set is calculated. And based on the game countering strategy set, the motion planning data of each agent for executing the current task is determined, each agent is controlled to execute the task according to the plan, and the game countering strategy generation accuracy, the task allocation accuracy and the task execution efficiency of the multiple agents are remarkably improved.

The invention relates to the technical field of cold chain logistics management, in particular to an intelligent cold chain management method and system based on the Internet and multi-dimensional analysis, and the method comprises the following steps: S1, collecting multi-dimensional data in a cold chain transportation process in real time, including temperature data, humidity data, vibration data, position data and state data of a transportation vehicle; s2, preprocessing the collected multi-dimensional data; s3, abnormal conditions in the cold chain transportation process are analyzed, and an abnormal analysis report is generated; s4, judging whether abnormal conditions such as temperature exceeding, humidity abnormity or excessive vibration occur in the cold chain transportation process or not, and recording specific information of occurrence of the abnormal conditions; and S5, sending the corresponding abnormal information to terminal equipment of related management personnel. According to the invention, through combination of multi-dimensional data acquisition and a big data analysis technology, comprehensive real-time monitoring and automatic abnormity early warning of the cold chain transportation process are realized, and the management efficiency is significantly improved.

The invention discloses a method and an apparatus in a node used for wireless communication. The node receives the first request; generating a first result through the first model as a response to receiving the first request; the first model is used for at least one of training or reasoning; the identifier of the first model is a first identifier, and the first identifier is a non-negative integer; the first identifier is associated with a first index, and the first index is one of a plurality of indexes included in a first index set; the first index set is associated to a first sub-identifier set; the plurality of types of data indicated by the plurality of sub-identifiers included in the first sub-identifier set comprise at least one of channel quality information data, codebook data and position auxiliary information data; the sub-identifier associated with the first identifier depends on the first index. According to the method, the design of the model identifier and the matching of the data in the system adopting human intelligence and machine learning are optimized, so that the overall performance of the system is optimized.

The invention discloses a drug inspection information sharing method and system based on a block chain, and relates to the technical field of drug inspection data management, and the method comprises the steps: sending an authentication request to a block chain network when a drug inspection device is started, verifying the state of the device according to a device digital identity certificate after an intelligent contract receives the authentication request, and sending the verification result to a server; generating a temporary operation token, encrypting the temporary operation token by using the equipment public key and returning the temporary operation token to the medicine inspection equipment; the medicine inspection equipment performs medicine inspection through the temporary operation token, synchronously acquires inspection data, a GPS position, an inspection timestamp and an equipment fingerprint, calculates a composite hash value, and encrypts the inspection data; and submitting the composite hash value to a block chain network, performing space-time compliance verification through an intelligent contract, obtaining a drug batch DID, and generating an on-chain block associated with the drug batch DID. According to the invention, the identity credibility of the medicine inspection equipment is ensured, and the authenticity, integrity and time-space consistency of inspection data are realized.

A fuel price determination system may receive transaction data identifying purchases, made with transaction cards and mobile transaction card applications of client devices, of fuel at fuel stations. The fuel price determination system may receive location data identifying locations associated with users of the client devices and the transaction cards, and user history data associated with prior purchases of fuel at fuel stations by the users. The fuel price determination system may process the transaction data, location data, and user history data, with a machine learning model, to determine fuel prices at the fuel stations. The fuel price determination system may determine a ranked list of particular fuel stations in a geographical area based on the fuel prices and populate, based on the location data and the ranked list, a map to identify the particular fuel stations and the fuel prices at the particular fuel stations.

The invention relates to a block backup indexing method, system and device based on a B + tree and a storage medium, and belongs to the technical field of disaster recovery backup. The method comprises the steps of intercepting a QEMU block write-in request and extracting an IO descriptor, writing block data into a disk and obtaining a physical offset, initializing a two-dimensional B + tree index structure, inserting the block IO descriptor and offset information into a two-dimensional B + tree, querying the position of the block data according to a logic offset and / or timestamp range, and deleting and updating index nodes according to a specified range. The system comprises a block data interception module, a block data writing module, a B + tree initialization module, a block data insertion module, a block data search module and a block data deletion module. According to the method, through a two-dimensional hierarchical index structure of the logic offset and the timestamp, joint efficient positioning of time and space dimensions is achieved, sharing of timestamp leaf nodes between local and global B + trees is supported, data redundancy is effectively avoided, and range query efficiency is improved.

The invention relates to a redundant data parallel preprocessing optimization method based on a heterogeneous computing platform, which belongs to the technical field of electronic information and comprises the following steps of: firstly, determining redundant data in a data preprocessing stage; secondly, effective data positions are marked in real time, and the number of effective data is counted; secondly, determining a threshold value according to the number, dimension and type of original storage data, and proposing an intelligent data structure selection strategy according to the number of effective data; and double-precision calculation is only performed on the identified redundant data once and the result is cached, and the result is directly reused in subsequent iteration. According to the method, the problems of low computing resource utilization rate, over-high cross-device communication bandwidth occupation, storage I / O bottleneck and the like caused by data redundancy in heterogeneous computing are effectively solved.

The invention discloses a material-environment coupled self-adaptive riveting parameter optimization method and system. The method comprises the following steps: acquiring force data, speed data, position data, environment data and material data in a riveting process; when the force data is greater than a preset force threshold value, adjusting the parameters of the riveting equipment to obtain stable force data; performing fluctuation mode analysis on the stability strength data to obtain an equipment state report; combining the material data with a preset strength prediction model to obtain initial prediction strength; adjusting the initial prediction force according to the comprehensive correction coefficient to obtain the optimal prediction force; and judging whether the equipment parameters need to be adjusted or not according to the predicted optimal force and stable force data to obtain a judgment result, and adjusting the riveting equipment according to the judgment result and the equipment state report. According to the method, the riveting operation stability and the equipment maintenance efficiency can be improved by predicting and adjusting the riveting force in real time and combining long-term data analysis and identification equipment abrasion and material change.

Methods, systems, and devices for error detection, error correction, and error management by memory devices are described. Programmable thresholds are configured for a memory device based on a type of data or a location of stored data, among other aspects. For example, a host device configures a threshold quantity of errors for data at a memory device. When retrieving the data, the memory device tracks or counts errors in the data and determine whether the threshold has been satisfied. The memory device transmits (e.g., to the host device) an indication whether the threshold has been satisfied, and the system performs functions to correct the errors and / or prevent further errors. The memory device also identifies errors in received commands or identifies errors introduced in data after the data was received (e.g., using an error detecting code associated with a command or bus).

A system and method for encoding and decoding optical codes with context-aware, multi-level security. Input data is classified into security levels with associated context sensitivity requirements. The system compresses data using public and private codebooks based on security classifications, then generates optical codes incorporating both compressed data and context requirements. When scanned, the system collects environmental contextual data (location, network environment, device security, user behavior), analyzes it against embedded context requirements, and dynamically determines which security levels are accessible in the current environment. Only authorized security levels are decoded using appropriate codebooks based on both user credentials and current contextual factors. This approach enables fine-grained, context-sensitive access control that adapts to changing environments while maintaining the compression benefits and capacity advantages of the multi-level security framework.

The invention discloses a real-time video stream transmission method and device based on an unmanned aerial vehicle and electronic equipment, and relates to the technical field of unmanned aerial vehicle communication.The method comprises the steps that network state data, position information and historical transmission records of the unmanned aerial vehicle are obtained, and the historical transmission records of the unmanned aerial vehicle are obtained according to the network state data and the position information; adjusting a coding parameter of the to-be-transmitted video stream by adopting a self-adaptive coding strategy to obtain a target coding parameter, and coding the to-be-transmitted video stream based on the target coding parameter to obtain a target video stream; and screening the transmission path set based on the network state data, the position information and the historical transmission record to obtain a plurality of optimal transmission paths, and transmitting the target video stream by adopting the plurality of optimal transmission paths. According to the invention, the technical problem that the transmission delay is increased and the image quality is reduced due to the instability of the network state and the unicity of the transmission path in the prior art is solved.

Embodiments of the present invention disclose an approach for data security and management. Specifically, the approach involves managing the analysis of sensitive data across multiple data centers. The system includes a data location repository that stores and updates information regarding the locations of sensitive data in data centers. When a request to access sensitive data from an analysis process is received, a specific data center where the data is stored is identified. The necessary components of the analysis process are transferred to that data center. The migrated analysis process is then executed using the locally stored sensitive data, without physically transferring the data. The generated analysis results are transferred back to the original data center where the analysis process originated.

The invention relates to the technical field of data security protection, in particular to a big data security protection method. The method comprises the following steps: acquiring system operation data; performing storage position mapping on the system operation data to obtain a data position mapping table; performing real-time data encryption according to the data position mapping table to obtain an encrypted data storage table; acquiring system memory data; performing reference counting statistics on the system memory data based on the encrypted data storage table to obtain a data reference state table; performing residue detection analysis on the data reference state table to obtain a data residue mark set; performing residual data multi-level cache clearing according to the data residual mark set to obtain a memory clearing verification table; and performing defragmentation optimization on the memory cleaning verification table to obtain an optimized memory layout diagram. According to the method, the weak link of dynamic data protection in the prior art is effectively solved, and the security and reliability of the big data system are remarkably improved.

The invention relates to a front-end monitoring method and device, computer equipment, a computer readable storage medium and a computer program product. According to the method, a front-end page is monitored, an identifier corresponding to front-end error information is generated under the condition that the front-end error information is monitored, screen recording data is generated under the condition that a screen recording function is started, and the front-end error information, the identifier and the screen recording data are stored in report information. After the reported information is uploaded to the server side, a worker can quickly position the screen recording data corresponding to the front-end error information through the identifier so as to check the process of the front-end error, and can also analyze the cause of the front-end error through the front-end error information; under the condition that the screen recording function is not started, after the identifier is stored in the report information and uploaded to the server side, a worker can still rapidly locate the data position where the front-end error occurs through the identifier, and therefore the front-end error is analyzed.

The invention is applicable to the technical field of data mining, and provides a deep learning-based false data positioning and recovery system for a power system, which comprises a data acquisition and standard processing module, a position detection module and a data recovery module, the data acquisition and standard processing module is used for acquiring operation parameters of the electric power system and performing cleaning and normalization processing on the operation parameters to generate standardized operation parameters; the position detection module is used for inputting the standardized operation parameters into a preset spatial-temporal feature fusion detection model and outputting a predicted position index of the false data; and the data recovery module is used for generating recovery data according to the predicted position index and the TVAE-WGANGP recovery model. According to the method, the positioning sensitivity and the data reconstruction precision in a complex attack scene can be remarkably improved, and a reliable active defense technology is provided for security protection of a smart power grid.

This disclosure provides a data processing method and apparatus. The method, during the migration of a metadata table from a source cluster to a target cluster, detects a write operation on the metadata table, performs a checkpoint operation on the metadata table to back up the existing metadata information under the checkpoint operation, migrates the existing metadata information to the target cluster, and then replays the existing metadata information based on the corresponding log files after the write operation to obtain the target metadata information after the write operation. Finally, after the metadata table migration is complete, the corresponding data file is migrated to the target cluster. This technical solution avoids data location confusion during data migration and does not affect normal read / write operations for users.

A method and system for collecting, matching and reporting evidence related to a collision event captured on a first collision detection device associated with a vehicular transportation system. A first incident report of the collision event communicated from the first collision detection device to the cloud-based application. The first incident report includes image data, location data, and temporal data of the collision event. A collision event database of the cloud-based application is searched to locate a second incident report of the collision event. The first incident report is compiled with the second incident report when the collision event of the first incident report matches the recorded collision event of the second incident report. A collision evidence report is generated based on the compiled first and second incident reports.

The technology disclosed herein relates to a multi-link device and methods, media, and systems associated with the multi-link device. The multi-link device can establish multiple wide area network (WAN) connections with multiple base stations. The multi-link device has multiple sets of antennas, and each WAN connection is associated with at least one of the multiple sets of antennas. The multi-link device also has a local area network (LAN) interface that is capable of establishing a plurality of LAN connections. The multi-link device can determine which of the WAN connections has a highest uplink bandwidth or a lowest uplink bandwidth. In some embodiments, the multi-link device ranks each of the WAN connections based on uplink bandwidth. Further, the multi-link device can transmit various sets of data (e.g., video data, image data, audio data, location data) to the multiple base stations via the WAN connections that are concurrently active.

This invention relates to the field of data processing technology and discloses a method for monitoring the trajectory of policy data changes. The method includes: constructing a policy data model based on the policy business chain; triggering a data snapshot corresponding to the policy data model according to the workflow of the policy business chain to obtain the policy data object; detecting data change fields in the policy data object and identifying policy change data in the policy data model based on the data change fields; determining the data position of the policy change data in the policy data model and generating a policy change model based on the data position; and rendering the policy change model to obtain a policy trajectory change model. This invention also proposes a monitoring device, computer equipment, and storage medium for policy data change trajectories. This invention can improve the accuracy and efficiency of monitoring policy data change trajectories.