612 results about "Access time" patented technology

The invention relates to the technical field of data processing, and discloses a multilevel cloud storage cluster construction and data storage method. The method comprises the steps that S1, multiple levels of storage layers are constructed and comprise a cache layer, a performance layer and a capacity layer, and the storage layers are provided with different storage media which are used for storing hot data, warm data and cold data respectively; s2, determining data popularity by monitoring data access frequency, access time interval and data importance; and S3, dynamically adjusting the storage hierarchy of the data according to the data popularity, and triggering hierarchical migration of the data. By constructing a multi-level storage layer and adopting a hierarchical architecture that the cache layer stores high-frequency data, the performance layer stores intermediate-frequency data and the capacity layer stores low-frequency data, high-heat data is preferentially stored in a high-performance medium, access delay is reduced, and data reading and writing efficiency is improved. Meanwhile, in combination with a dynamic data migration strategy, the storage position can be adjusted in real time according to the data access popularity, and the overall performance of the system is further optimized.

The invention provides a data all-flash storage optimization method and system based on cloud computing, and the method comprises the steps: receiving a storage operation request stream of a user terminal through collecting a multi-dimensional performance data set of each node of an all-flash storage cluster in real time, wherein the multi-dimensional performance data set comprises a storage space fragmentation rate, an input / output request queue depth and a network link bandwidth utilization rate; analyzing a to-be-stored data block identifier set and an operation mode label, traversing a historical access record library based on to-be-stored data block identifiers, extracting historical access time sequence characteristics and physical storage position proximity of associated data blocks, and combining the multi-dimensional performance data and the historical access time sequence characteristics to obtain a data block identifier set; according to the method, a dynamic access popularity prediction model in a preset time period is constructed, and finally, a cross-node fragmentation storage topological graph and a cache preloading strategy matrix are generated according to the proximity of the dynamic access popularity prediction model and a physical storage position, so that the optimization of all-flash storage is realized, and the data storage performance in a cloud computing environment is improved.

To provide a data storage device comprising a processing device, and a method.SOLUTION: Provided is a method implemented or performed when a read / write channel circuit of a control circuit of a disk drive controls operation of the disk drive. The method includes selecting a seek time model from a plurality of seek time models at least partially based on operation characteristics of an access command. The operation characteristics is related to the off-track sensitivity of executing the access command. The method also uses the selected seek time model to determine the access time for the access command and selects the next access command for execution based on the determined access time for the access command and the determined access time for the other access command among the plurality of access commands.SELECTED DRAWING: Figure 2C

The invention relates to the technical field of cloud computing storage, in particular to a cloud storage dynamic optimization method and system, and the method comprises the following steps: based on a cloud storage data access record, recognizing an access time interval sequence, analyzing the variation amplitude of adjacent time intervals, and calculating the standard deviation of the access time intervals; and determining the access period stability according to the standard deviation and the change amplitude, and classifying the data objects to obtain a data access period stability classification value. According to the method, task scheduling is more accurate by identifying a data access time interval sequence and changes thereof and refining data classification and storage resource allocation, a high-throughput and low-delay storage path is matched, the health condition of a storage node is evaluated, a fault node is identified in advance, data stability is guaranteed, and data copy distribution is adjusted; the storage reliability and stability are improved, the storage path for accessing the intensive data is optimized, the dynamic load balance of the storage resources is realized, and the storage efficiency is improved.

The invention relates to the technical field of big data processing, and provides a mass data storage optimization method which comprises the following steps: analyzing target data according to access frequency and / or access time of the data, and dividing the target data into hot data, warm data and cold data; aiming at the hot data, the temperature data and the cold data, performing compression processing by adopting corresponding compression algorithms; before the target data is stored, performing duplicate removal on the target data according to the fingerprint of the target data; monitoring the use condition of the memory, the access frequency of the target data and the performance of the compression algorithm in real time, and deploying system resources according to a monitoring result; and setting a multi-level cache, and caching different types of target data to the multi-level cache according to the divided types of the target data. According to the technical scheme, mass data can be efficiently stored and rapidly accessed, and the storage space utilization rate and the overall system performance are remarkably improved.

The invention relates to the field of industrial internet intrusion prevention, in particular to a computer network big data security protection method and system, and the method comprises the following steps: monitoring network flow, collecting user identity, equipment security state, access time and network behavior data, and generating a network behavior record. In the invention, a dynamic security assessment system is constructed through network flow monitoring, identity verification and behavior analysis, and compared with static strategy or fixed rule matching, the dynamic security assessment system can adapt to a continuously changing network attack environment. Authority dynamic adjustment is performed based on the user identity verification state, flexible management and control of the access authority are ensured, and the problem of long-term high authority abuse is avoided. Threat detection not only depends on historical mode matching, but also is combined with real-time behavior analysis, and accurate isolation is executed for potential threats, so that protection measures are changed from passive response to active intervention, and the delay of manual intervention is reduced.

The invention discloses a cache processing method of heterogeneous equipment, a heterogeneous system, a product, a device and a medium, and relates to the technical field of data storage. And according to the target virtual address access times corresponding to each device in the heterogeneous system, realizing a global data caching mechanism. And determining a file page corresponding to the target heterogeneous device based on the target virtual address access frequency, so that the file system layer has the capability of managing the memory cache of the heterogeneous device. And the predicted file page of the target heterogeneous device is verified, and the file page is moved under the condition that the verification is passed, so that the distribution accuracy of the target heterogeneous device is improved. The file page of the target heterogeneous device is mapped and moved to the memory of the host side, the target heterogeneous device does not need to be accessed, the file page stored in the memory of the processor is directly accessed, the increased access rate of the processor accessing the target heterogeneous device is avoided, the delay of accessing the memory of the target heterogeneous device is reduced, and the access efficiency is improved. And the data transmission rate and the system efficiency of the heterogeneous system are improved.

The invention belongs to the field of data storage, and discloses a frequency access data storage migration method and device for big data, and the method comprises the steps: obtaining a data access log, carrying out the preprocessing of the data access log, and obtaining a time window statistical matrix; carrying out timeliness attenuation weighting calculation on a plurality of data access times in the time window statistical matrix to obtain a weighted access frequency vector; obtaining a multi-dimensional feature matrix based on the weighted access frequency vector; clustering the feature vector of each time window slice in the multi-dimensional feature matrix through a Gaussian mixture model to obtain a clustering tag vector; inputting the clustering label vector into an access frequency prediction model to obtain an access frequency prediction value of the data in a future preset time step; the migration decision matrix is determined based on the access frequency predicted value and the data storage cost parameter, data migration is carried out based on the migration decision matrix, the data migration complexity can be reduced, and the access speed and the storage cost are balanced.

The invention discloses a dynamic access control strategy system based on behaviors, comprising: A, a behavior acquisition module for acquiring user behavior data in real time, the behavior data comprising login information, operation records, access resources, access time, access frequency and equipment information; b, the behavior analysis module is used for carrying out preprocessing, behavior pattern recognition and anomaly detection on the collected behavior data to generate a behavior analysis result; c, an access decision module which dynamically generates an access control decision in combination with user identity information, a behavior analysis result and a resource authority requirement; and D, a strategy updating module which updates the access control strategy in real time according to the security audit result, the user feedback and the new threat information. Compared with the prior art, the method has the advantages that a dynamic access control strategy based on behaviors is provided, the access authority of the user is dynamically adjusted by collecting and analyzing the user behavior data in real time, and finer, more flexible and safer access control is achieved.

The invention relates to the technical field of distributed storage, in particular to a high-speed distributed storage system and method, and the system comprises a file index characterization module which carries out the statistics of the access frequency and the recent access timestamp of each data block in the system, and obtains the popularity magnitude of the file data blocks; according to the method, the popularity magnitude concept is introduced on the basis of linkage statistics of the data block access frequency and the recent access time, the data blocks with remarkable service influence in the current system can be recognized, the priority processing sequence of different data blocks in the repair process is divided, and the decision-making efficiency during fault recovery is improved. After the to-be-repaired data blocks are identified, the comprehensive weight values are formed through correlation calculation with the popularity magnitude, and all the weight values are arranged in a descending order, so that dynamic grading and sequential scheduling of repair tasks are realized, and important data blocks are guaranteed to preferentially obtain recovery resource support.

The invention relates to the technical field of database cache management, in particular to an LSM engine data cache optimization method, which comprises the following steps of: based on cache region data of an LSM storage engine, recording access times of implementation detailed rules, counting distribution density of implementation detailed rules, arranging the data into a priority sequence, and generating an implementation detailed rule access distribution information set. According to the method, accurate mastering of the implementation detailed rule distribution density is achieved by recording the implementation detailed rule access times and distribution positions, the implementation detailed rule distribution density is grouped and sorted into the priority sequence, the cache data reading efficiency is improved, and the cache data reading efficiency is improved by adjusting and optimizing the data storage layout and reducing the high-frequency data retrieval delay. The method has the advantages that the problem of uneven storage allocation is solved, the resource utilization rate is increased, data distribution is optimized through high-frequency implementation rule comparison, new implementation rule matching is dynamically adjusted, the hit rate and the response speed are increased, the system load is reduced, and the storage performance and the resource allocation efficiency are remarkably improved.

The invention relates to the technical field of computer storage, in particular to an intention perception data prefetching method and device of solid-state storage equipment and a storage medium. The method comprises the following steps: collecting user behavior data, wherein the user behavior data comprises an application use frequency, file access time, a system call log, a hard disk reading track and network flow information; classifying, filtering and preprocessing the collected user behavior data to generate a time sequence and a behavior sequence, and mapping the time sequence and the behavior sequence into multi-dimensional feature vectors; according to the intention perception data prefetching method of the solid-state storage device, dynamic and efficient data prefetching is achieved in combination with real-time analysis of the user operation intention, and the data access speed and the overall performance of the solid-state storage device are improved.

A hotspot data elimination and maintenance method in a distributed cache system comprises the steps that the access frequency, the time locality score, the service weight and the real-time data popularity value of data are acquired, and the dynamic priority score of the data is generated; determining failure data based on the dynamic priority score; dividing the data into hot spot area data, temperature spot area data and cold spot area data, when the cache space is insufficient, preferentially eliminating the data with the lowest dynamic priority score and the retention benefit value lower than a preset threshold value in the cold spot area data, and if the cache space is still insufficient, performing data elimination on the temperature spot area data according to the latest access time of the temperature spot area data; packaging the cold point area elimination data, the warm point area elimination data and the failure data into a final transaction message; and broadcasting the final transaction message through a preset protocol, and performing distributed consistency maintenance operation on the final transaction message through the receiving node. According to the invention, intelligent and efficient cache data elimination and consistency maintenance management can be realized.

The invention belongs to the technical field of computers, and particularly discloses a data migration method based on a heterogeneous network memory pool and a data center, the method is applied to the data center, the data center comprises a management node and a plurality of cabinets, each cabinet comprises a plurality of nodes, CXL is adopted between the nodes in the same cabinet, RDMA is adopted between the nodes of different cabinets, and the management node is connected with the management node. The method comprises the following steps: monitoring access popularity of a node to a memory page; under the condition that the access popularity of the first node to the target memory page is greater than a popularity threshold value, migrating the target memory page from a second node to which the target memory page belongs to the first node through the management node, and initializing the access popularity of the first node to the target memory page; according to the method and the device, the access times and the access frequency of each cross-cabinet page are tracked, so that the high-heat target memory page with relatively high access times and access frequency can be migrated from the node to which the target memory page belongs to the CXL memory of the node of the cabinet to accelerate access.

The invention relates to the technical field of data storage, and provides an object storage intelligent layering method and device based on a decision tree, and the method comprises the steps: collecting object data, carrying out the preprocessing of the collected object data, and setting an access time window and a storage label for the obtained standardized object data; performing feature extraction on the stored standardized data, and performing dimension reduction processing on the extracted features to obtain feature data; constructing a training model, training and testing the training model by adopting feature data, and selecting a decision tree model from the training model for production deployment; and performing classified storage prediction on the uploaded object data by adopting the deployed decision tree model, and storing the object data to a corresponding storage pool according to a classified storage prediction result. According to the method, the future access frequency of the object can be predicted and directly allocated to different storage medium layers, so that the data migration time and space loss are saved, the storage system efficiency is improved, and the user access performance is improved.

The invention provides a resource optimization method and system for a router, a gateway and a camera in the technical field of edge computing. The method comprises the following steps: S1, training a network state prediction model and deploying the network state prediction model to edge computing equipment; s2, the edge computing device collects network index data based on a dynamic weight data collection mechanism and caches the network index data to a time sequence database; s3, inputting the network index data into the network state prediction model to obtain a network state prediction result; s4, generating a network resource optimization strategy based on the network state prediction result, verifying the network resource optimization strategy based on the digital twin technology, and executing the network resource optimization strategy; and S5, performing rolling updating on the network index data cached in the time sequence database based on the access times and the final access time. The method has the advantages that the flexibility and rationality of network resource configuration are greatly improved, and then the system performance and efficiency are greatly improved.

The invention discloses a device access method and an electronic device, relates to the technical field of artificial intelligence, and can dynamically adjust the access priority of the device and reduce the perception of a user on the access time delay of the whole device in the environment. In the scheme, when the plurality of intelligent devices are to be accessed, the first device can acquire the state information of the user, and when the state information acquired by the first device at the first time is the first state information, the intelligent device corresponding to the first state information in the plurality of intelligent devices can be preferentially controlled to be accessed. And when the state information acquired by the first equipment at the second time is changed into the second state information, the access of the intelligent equipment corresponding to the second state information in the plurality of intelligent equipment can be preferentially controlled.

The invention discloses a cloud storage acceleration method and system based on edge computing, and relates to the field of electrical digital data process.The method comprises the steps that a file access track ring is constructed; extracting historical access files as a first associated file set; calculating the access time difference of each historical access file; determining a plurality of association clusters and two association file sets according to the access time difference; performing cyclic displacement in the second associated file set to obtain a displacement associated cluster; extracting a third associated file set; determining a prefetching file; setting an annular cache queue, and determining a prefetching position according to the position information; when the space of the annular cache queue is smaller than a preset value, the prefetched file corresponding to the prefetched position in the preset interval of the annular cache queue is reserved, and a final prefetched file is obtained; and when it is detected that the user accesses the target file, loading the final prefetched file from the cloud storage server to the edge server. The method and device are used for solving the problem that the cache hit rate of the associated files is reduced, and the cloud storage acceleration speed is increased.

The invention relates to the technical field of security monitoring for preventing confidential files from being leaked, and discloses a security monitoring method for preventing confidential files from being leaked. By setting the user permission matrix and the dynamic access condition set, the system finely manages user permissions, it is ensured that the user only accesses related files, and the risk of unauthorized access is reduced. The dynamic condition set includes access time, device identification, and geographic location, preventing access by unsecure devices or locations. And the system verifies the permission matching degree in real time and rejects access which does not conform to conditions in time, so that the risk of permission abuse and leakage is reduced. A detailed log is generated in each access, an operation result and rejection information are recorded, and an administrator is notified when an abnormal behavior occurs. In combination with file sensitivity evaluation and a multi-layer encryption strategy, the system takes different protection measures according to file sensitivity. Through real-time authority management and auditing, file operation compliance is monitored, and potential violation behaviors are found in time.

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

The application discloses a method and device for realizing high-speed operation of an algorithm based on a multi-level field cache, which comprises the following steps: a configuration management CPU sends algorithm parameters to an FPGA chip and saves the algorithm parameters in a RAM; a service processing CPU creates a handle and sends the handle to the configuration management CPU; the configuration management CPU generates a key number according to the handle; the configuration management CPU sends a key library to the FPGA chip; the service processing CPU sends a to-be-operated message to the FPGA chip; an algorithm scheduling module performs fragmentation judgment, and performs subsequent processing according to a sequence judgment result; a password operation module takes the received key, an initialization vector or an intermediate chain variable and the to-be-operated message as input, performs password operation, and outputs a calculation result and an operated intermediate chain variable; whether the to-be-operated message is the last data fragment is judged according to a tail fragment identifier, and subsequent processing is performed according to a tail fragment judgment result. The application can reduce the communication interface and CPU access times, realize high-speed operation of a password algorithm, and improve the overall performance of a password service system.

The embodiment of the invention provides a display device and an advertisement data playing method. According to the method, storage positions are dynamically allocated according to advertisement data characteristics, memory occupation is reduced, and the access speed of key data is increased; a priority score is generated by calculating the access frequency, the resource type weight and the final access time of the advertisement data, and a low-score data block is preferentially removed when the storage space is insufficient, so that the cache hit rate of high-frequency / hot advertisements is ensured; by downloading recent advertisement data to the local in advance, real-time downloading delay during playing is avoided, large file advertisements are stored in blocks, cached parts are read preferentially during playing, meanwhile, remaining data blocks are downloaded in the background, and rapid playing of the advertisement data is achieved. In addition, cloud advertisement data change is monitored, local cache is dynamically synchronized, data timeliness is ensured, a local index table is quickly queried before the advertisement is played, direct playing or playing while playing is selected according to cache integrity, waiting time is shortened, and the problem that the advertisement playing speed is low is solved.

The invention relates to the technical field of electronic data digital processing, and discloses a data maintenance management method and system based on artificial intelligence. The method comprises the following steps: acquiring multi-dimensional features such as an access time sequence, metadata, an association relationship and a service context of data; constructing a hybrid model fusing a long-short-term memory network and a graph attention network, and predicting a future value score of the data; dynamically generating a hierarchical storage, archiving or deleting strategy based on the score and storage cost-performance model; and through the access feedback after the execution of the monitoring strategy, the prediction model is optimized in a closed-loop manner by using a reinforcement learning mechanism. The system comprises a data feature acquisition module, a value prediction module, a strategy generation module and an execution feedback module. According to the method, self-adaptive, refined and intelligent management of the full life cycle of the data is realized, the utilization efficiency of storage resources is remarkably improved, and the operation and maintenance cost is reduced.

The invention discloses an automatic management method and management system for an unmanned file library, and relates to the technical field of intelligent file management, and the method comprises the steps: continuously monitoring and recording the access time period, frequency and importance mark score of each file through a sensor; by analyzing the use frequency, the time period and the importance mark of different archives, the access requirements of which archives will be increased within a period of time in the future are predicted; a prediction model is generated according to the access frequency trend, the access demand change of each file in a certain time in the future is obtained, a self-adaptive optimization mechanism is established, and the files which are frequently accessed are automatically moved to a position which is easier to access through a self-adaptive path optimization algorithm. According to the invention, full-process automation from data acquisition and analysis to path optimization and archive access is realized, manual intervention is greatly reduced, and the unmanned trend of modern archive management is met; and the change of file access requirements can be adapted.

The invention provides an encrypted data storage and key management protection method for a blue-ray disc, which relates to the technical field of data storage security and comprises the following steps of: performing multi-frequency data block division by extracting access time sequence characteristics of original data, calculating a multi-dimensional entropy value to determine an encryption algorithm parameter and a key; and extracting physical characteristic signals of the blue-ray disc to obtain sector defect distribution and evaluate reliability, thereby realizing optimal mapping storage of encrypted data and a multi-dimensional reliability sector group. According to the invention, the data storage security is effectively improved, the key management mechanism is optimized, and the physical characteristics of the blue-ray disc are fully utilized to enhance the data protection capability.

The invention provides an on-off control method and device for a gateway port and a medium. The on-off control method comprises the steps of obtaining historical access log data and threat intelligence data of a target port in a gateway; based on the historical access log data and the threat intelligence data, performing time sequence analysis by using a pre-trained long-short-term memory network model to obtain a predicted security access time period of the target port in a future preset time period; generating a temporary port exposure preset rule of the target port according to the predicted security access time period; determining a traffic feature vector of the real-time traffic data packet of the target port; using a preset deep reinforcement learning agent to determine an on-off control instruction for the target port based on the traffic feature vector and a temporary port exposure preset rule; and executing the on-off control instruction to modify an access control list state of the gateway firewall to the target port. According to the method and the device, dynamic and refined gateway port on-off control can be realized, so that the service flexibility and security are considered.

The invention provides an information processing method and device, and aims to solve the problem that a candidate cell does not know whether the cell is a target cell to be accessed by a terminal or not before the terminal performs cell switching, so that the corresponding operation is difficult to execute in advance. The method provided by the embodiment of the invention comprises the following steps: sending indication information to second network equipment; wherein the indication information comprises information required by the second network equipment for terminal access management and / or resource management. Through the above scheme, the second network device can execute the terminal access management operation related to terminal access based on the indication information before the terminal changes or adds the serving cell, so as to reduce the access time delay, and / or perform resource management based on the indication information, such as releasing / deactivating uplink resources, so as to avoid resource waste.

The invention discloses a polling arbitration method and a polling arbitration system for dynamically updating weight by an EWMA algorithm, and the method comprises the following steps: monitoring and receiving a request signal sent by each AHB bus channel on a matrix bus in real time; taking a preset arbitration period as a time window, collecting the current request access times of each AHB bus channel, reading the historical request times stored in the last period, calculating the request variation of each channel, and performing uniform quantization; and on the basis of the historical weight value and the quantized value, an exponentially weighted moving average value is calculated through an EWMA algorithm. When the method is used, the actual weight value of each AHB channel can be adaptively and dynamically adjusted every fixed arbitration period number, resource allocation and system fairness are improved, and it is ensured that an arbiter can more accurately reflect the actual demand of each AHB channel on a matrix bus.

The invention discloses an access method and device of a low-orbit satellite communication system, and belongs to the field of satellite communication. The method comprises the following steps: if an auxiliary information timer of a current satellite cell is overtime and random access fails, determining whether an adjacent cell of which the beam signal strength reaches access threshold strength exists at present; if it is determined that the neighbor cell with the beam signal strength reaching the access threshold strength exists currently, determining an optimal satellite cell of random access according to the current satellite cell and the remaining service time of the neighbor cell to the ground terminal; the remaining service time is the remaining time when the satellite cell beam signal covers the ground terminal. According to the invention, the access can be accelerated, the access time delay can be reduced, and the risks of switching, signaling resource waste and switching failure increase caused by fast switching after access can be avoided.

The invention relates to a data storage method and device, electronic equipment, a storage medium and a program product. The storage cost can be effectively reduced. The method comprises the following steps: setting an archiving life cycle for a target storage bucket in a first storage system, wherein the first storage system is a storage system of which storage data can be accessed in real time; under the condition that at least one piece of data meeting a target condition exists in the target storage bucket, the at least one piece of data is transferred from the first storage system to an archiving storage system, and the archiving storage system is a storage system in which stored data cannot be accessed in real time; wherein the target condition comprises at least one of the following items: the access frequency of the data in the archiving life cycle is less than or equal to a frequency threshold; the duration from the access time of the last access of the data in the archiving life cycle to the current moment is greater than or equal to a duration threshold.