77results about How to "Improve data availability" patented technology

The invention discloses an intelligent energy transaction management system and method based on the block chain technology. The system includes an intelligent metering device subsystem and an energy transaction platform subsystem. The energy transaction platform subsystem includes an intelligent contract generation module, a first intelligent contract execution module, an intelligent contract management module, a remote data acquisition module, a payment module, a distributed block chain and a payment data acquisition and verification module. The intelligent metering device subsystem includes a communication module, a second intelligent contract execution module, an execution unit and a local data acquisition module. The local data acquisition module is used for regularly acquiring measurement data of at least one intelligent metering instrument and converting, aggregating, gathering and statistically calculating the acquired data and providing calculation result data. The system and method of the invention can provide transparent, trustworthy, scrutinizeable and traceable data for energy transaction parties, have high data usability and reliability and can be widely applied in the field of energy transaction data processing.

An apparatus for reducing data unavailability time after a loss of main power in a storage controller is described. The controller backs up its volatile memory containing posted-write data to a non-volatile memory upon detecting a loss of main power. The controller continues to provide battery power to the volatile memory to sustain the posted-write data. If the battery is able to supply power to the volatile memory until main power is restored, the controller foregoes restoring the posted-write data to the volatile memory from the non-volatile memory. By not incurring the restore time, which may be substantial if the volatile memory is large since read rates from volatile memories are typically slow, the data unavailability time is reduced. The selective restore feature is user-disableable and also includes a brown-out timer for allowing a user to specify how long to battery-power the volatile memory if the feature is enabled.

A system and method for clustered failover over transport media that does not support moving of transport addressed between network interface controllers is provided. This reviving file server of a cluster, upon detection of the failure of its partner, assumes ownership of the disks owned by the failed file server. The surviving file server activates a secondary discriminator or port for access by clients who normally utilized the failed file server. Clients generate the name of the surviving or failover file server by appending at set item to the name of the failed file server.

The invention discloses a family data center system based on cloud storage, which is established based on cloud storage on a public cloud and comprises a data storage management module and a family data management module, wherein the data storage management module is used for providing data cloud storage and management service based on the public cloud; and the family data management module is used for performing the cloud storage of family data through calling the data storage management module and managing the family data. The invention also discloses a family data management method based on the cloud storage. Through the family data center system and the family data management method, a data storage and data exchange space can be provided for various family equipment like an intelligent mobile phone, a tablet personal computer, a PC (Personal Computer) machine, a notebook computer, a cloud terminal / virtual machine, an IPTV (Internet Protocol Television), a satellite television receiver and other external equipment, and a content receiving space can be provided for a third party content provider on an internet, so that the massive storage and the reliable storage of the family data are realized; and online content ordering service and message pushing service based on a family data center can also be developed to create more applications.

A storage subsystem such as an array of disk drives, method of managing disk drives in the storage subsystem and program product therefor. The storage subsystem may be a redundant array of independent disks (RAID) and the individual disks drives may be Self-Monitoring, Analysis and Reporting Technology (SMART) capable drives. When one of the drives gives an indication of an impending failure, a disk image of the failing disk is built on an available spare disk. Once the image is complete, the failing disk may be replaced without down time for rebuilding a failed disk.

A storage system architecture comprises one or more volumes distributed across the plurality of nodes interconnected as a cluster. The volumes are organized as a striped volume set (SVS) and configured to store content of data containers served by the cluster in response to data access requests issued by clients. The content of each data container is apportioned among the volumes of the SVS to thereby improve efficiency and storage service provided by the cluster. Each data container is implemented on each of the volumes of the SVS as a sparse data container which stores data amongst sections of sparseness within the data container.

The invention discloses a differential privacy data publishing method and system based on dependency removal. Each data owner independently sections an own original data set and obtains a differential value data set, the first two items of the differential value data set are subjected to summation and noise adding, then, the obtained value is uploaded to a cloud service provider after the obtained value is subjected to homomorphic encryption, and the cloud service provider carries out homomorphic decryption operation; each data owner transforms the differential value data set item to obtain a transformation coefficient, and stable noise consisting of white noise which is mutually independent and complies with Gaussian distribution is added; the data owner carries out inverse wavelet transform to obtain a scrambled data set, and the data set is uploaded to the cloud service provider; and the cloud service provider utilizes Wiener filtering to carry out filtering, and the cloud service provider carries out inverse transformation on a refined data set and publishes the refined data set to the data item of a third-party data user when the data user requests the data set. The differential privacy data publishing method and system effectively reduces the data calculation amount and interaction amount and improves a resource use ratio and data availability.

The invention provides a geospatial data based user privacy protection method and system. The method comprises: partitioning data space; combining similar cells to the same partition based on a uniformity measurement parameter; adding random noise conforming to Laplace distribution into each partition to obtain a noise data set; and externally providing a data query result based on the noise data set. The invention, based on analysis of noise errors and uniform assumption errors, proposes a novel data field granularity partitioning model for balancing the noise errors and the uniform assumption errors to minimize total data query errors. A condition that query is rectangular query is considered when the model is created, so that an actual data query condition is better met. Furthermore, the similar cells in the data space are combined, so that the query error of the geospatial data is smaller, and the data availability is greatly enhanced while the record security of user privacy is protected.

A storage subsystem such as an array of disk drives, method of managing disk drives in the storage subsystem and program product therefor. The storage subsystem may be a redundant array of independent disks (RAID) and the individual disks drives may be Self-Monitoring, Analysis and Reporting Technology (SMART) capable drives. When one of the drives gives an indication of an impending failure, a disk image of the failing disk is built on an available spare disk. Once the image is complete, the failing disk may be replaced without down time for rebuilding a failed disk.

The invention discloses an energy-saving-oriented high-reliability data storage method in a data center environment, aiming at solving the technical problem that a hybrid high-reliability data storage method is provided under the condition of an energy-saving-oriented closed node. In the method, a large number of nodes are allowed to be closed so as to reduce power consumption, and at least one copy of all data is ensured to be stored on active nodes, thus availability of the data is kept. The method comprises the following steps of: firstly dividing clusters and numbering nodes in racks to form logical rings as well as numbering the nodes among the racks to form mutually non-intersected rings; then dividing files to be stored and determining backup quantity of data; and determining a copy placement position of each data block in a queue by adopting a hybrid data storage method. In the method, large-scale node closure and reduction of the power consumption can be supported, reliability of the data can be ensured, and data recovery capability is strong, thus the problems of the energy consumption of a data center and the reliability of the data are effectively solved.

The invention relates to a device for providing road navigation road, especially a road traffic controller, wherein the electric map of its data memory contains the inlet top point from each cross road into said road and the road arc record relative to the inlet top point with steering limit character; the main controller controls the map edit modifier, based on the steering limit information at each port of cross road provided by the input module, to modify the road arc data of relative inlet top point of electric map; and the receiver / sender receives present position and target position information, to send the navigation path to the carrier terminal; the searcher extracts the electric map data and uses the steering limit character of each road arc to use the Di jkStra algorism to calculate out the shortest navigation path in top point serial type.

The invention discloses an information push method and a server, wherein the server comprises a server site acquisition module suitable for acquiring a plurality of service sites to be pushed according to position information reported by a terminal; a search module suitable for searching information stored in a database relating to the service sites to be pushed according to individualized information push requests reported by the terminal; a push value acquisition module suitable for obtaining a push value of each service site to be pushed according to the information relating to the service sites to be pushed; and a push module suitable for pushing the service sites to be pushed to the terminal according to the push value of each service site to be pushed. According to the scheme provided by the invention, information pushed through position-based services is finer, the data is more accurate, and the data validity is higher, so as to better meet the individualized demands of users.

The invention discloses a financial product real time recommendation method based on a random forest algorithm. The financial product real time recommendation method based on the random forest algorithm comprises steps of analyzing user history transaction data and user characteristic data, constructing a training set and a testing set for the history transaction data and user characteristic data, using the random forest algorithm to set up a prediction model related to the financial product and performing prediction on the financial product that a user interests in. The financial product real time recommendation method based on the random forest algorithm uses a random forest to perform financial product recommendation, and compared with the prior art, the financial product real time recommendation method is fast in speed, less in parameters and good in effect and effectively improves sales efficiency and accuracy.

The invention provides an on-line data mining optimized control method based on the cyber physical system (CPS) of a power distribution network. The method comprises the steps of acquiring the data source of the CPS of the power distribution network and cleaning the data source; establishing an association relationship model between the data source and a controlled variable and conducting the data mining; verifying the correctness of the above association relationship with the actual power distribution network as an analysis example; on the condition that the above association relationship is correct, matching the above association relationship with association rules and outputting a matching result; on the condition that the above association relationship is not correct, correcting association rules; and controlling the power distribution network according to the output result. By adopting the above method, on the premise that the safe operation of the power distribution network is ensured, the cost of power enterprises is lowered. Therefore, the method facilitates the pioneering and developing process of the electricity market.

An embodiment of the invention discloses a method for data recovery. The method for the data recovery includes reading serial numbers of data objects in a data exception memory, distributing the serial numbers in a united mode during the process that the data object is written in a plurality of memories, comparing the serial numbers of the data exception memory with those of a data replica memory, and copying data objects corresponding to extra serial numbers of the data replica memory to the dada exception memory to achieve the data recovery. The embodiment of the invention further discloses a device for the data recovery. According to the method and the device for the data recovery, after the difference between the dada exception memory and the data replica memory is obtained by comparing the serial numbers, only the data objects corresponding to the extra serial numbers rather than all data are copied to the data exception memory, so that the amount of copied data is reduced, and the expenses of data copy are saved.

The invention discloses a data extracting and predicting model establishing method for environment monitoring. The method comprises the environment monitoring data extracting step and the environment predicting model establishing step. Data extracting logic and dispatching schedule can be customized, and user operation is facilitated. The standard and uniform regulation of environment data is established, and the environment data is unified. Scientific data effectiveness verification is adopted in the extracting process, and the data effectiveness of an environment data center is improved. The data are fully utilized through the data mining process of the environment monitoring data. An environment model is established through the extracted data, and support can be provided for an environment-friendly strategy.

The invention discloses a music analysis data set construction method and a pitch and value extraction method based on the data set, and mainly solves the problems that in the prior art, the performance of a traditional method is good in the single tone recognition subdivision field, but the performance in the complex tone recognition field is relatively weak. The music analysis data set construction method and the pitch and value extraction method based on the data set comprise the following steps of selecting and registering digital music scores into a digital music score library; registering a music score played by a player into the digital music score library; carrying out matching on a class label sequence and the sound characteristics to form a sound characteristic-music element dataset construction method; and based on the data set, executing the pitch and value extraction method and system from musical sound and musical instruments. According to the scheme, the value information and the pitch information of the digital sound signal generated by the musical instruments are extracted by using a supervised machine learning model, the purpose of extracting music elements in the complex tone can be well extracted, and the method has very high practical value and popularization value.

The invention discloses a video conference-oriented cloud storage access system, which includes a file management module, a rights management module, a cache management module, a cloud storage access module and a data security module, wherein: the file management module is used for Manage the mapping of file names and file handles; the data security module performs calculation and verification according to the hash algorithm, performs hash calculations for each uploaded file, and saves the hash value. When the user needs to read data, first Perform hash calculation, and compare the hash value with the hash value saved when uploading before. If the two are equal, it proves that the read data has integrity, otherwise a file error is returned; the cloud storage access module is a cloud The access interface provided by the storage service. The invention achieves beneficial effects such as saving user's storage investment, higher data availability and reliability, and the like.

The invention relates to the technical field of Internet and discloses a method for marketing transformation of BiddingX platform. The method includes the steps that the BiddingX platform monitors data of a whole process, integrates the data, and imports the data into a DMP system in real time; the DMP system drives an algorithm engine of BiddingX, and a full-flow solution for every marketing contact. The monitoring includes exposure monitoring, click monitoring and landing page monitoring, and the marketing contacts include creative display, advertisement click, landing page, website / APP, conversion and social sharing. According to the method for marketing transformation of the BiddingX platform, a plurality of marketing channels and marketing conversion processes are uniformly managed onthe same platform, so that the management efficiency, data transparency and data availability are maximized, and data loss and process sections are reduced. A plurality of marketing optimization solutions are driven by using DMP data, so the marketing effect is improved.

The invention discloses an equipment economic data evaluation method based on multi-source data interaction analysis, and the method comprises the steps: constructing a standardized equipment structure model according to the evaluation and analysis demands of massive equipment economic data, generating a multi-dimensional data evaluation and analysis object, and evaluating the equipment economic data according to the actual demands of equipment life cycle cost evaluation, performing information search and comparative analysis on the basis of a multi-source economic data resource library, and flexible real-time online interactive analysis is achieved. The method can be widely applied to the economic analysis and evaluation process of various types of equipment, the problems of structural analysis modeling and interactive evaluation analysis of multi-dimensional economic data are effectively solved, and the complexity and workload of evaluation analysts on original data analysis operation are reduced; and an efficient processing method and a generalized system design for equipment economic data evaluation and analysis are realized.

The invention relates to a multi-modal manufacturing data preprocessing method in an intelligent factory, which comprises the following steps: S1, receiving manufacturing data acquired by an industrial data acquisition system, and forming a training set D by the manufacturing data; S2, clustering the training set D to obtain a clustering result, constructing a neural network model, and training the neural network model according to the training set D and the clustering result thereof to obtain a final multi-modal manufacturing data integration model; S3, classifying the manufacturing data set needing to be processed through the multi-modal manufacturing data integration model; S4, performing denoising processing on the manufacturing data set; S5, performing redundancy elimination processing on the manufacturing data set; and S6, identifying missing values in the manufacturing data set, and filling the missing values. The multi-modal manufacturing data are clustered according to the model cluster by constructing the multi-modal manufacturing data integration model, so that data processing of subsequent links is facilitated. A data multi-stage optimization cleaning strategy is used, so that the data quality is improved, and the data correctness, consistency, integrity and reliability are ensured.

The invention provides a graph data anonymization method and device based on a deep neural network and a storage medium. According to the method, an anonymous graph with high anonymity and high data availability can be generated for data release, and the method comprises the following steps: 1, sampling by using a random walk strategy of a node2vec algorithm to obtain a real node sequence in graphdata, and representing nodes in the node sequence as vectors in an One-hot manner; 2, constructing a learning model of graph data features based on a deep neural network, training the learning modelby taking a real node sequence as input, and optimizing model parameters to obtain a trained learning model; 3, inputting a real node sequence into the trained learning model, and outputting a randomwalk sequence of the simulated nodes; 4, adding noise meeting a differential privacy mechanism to the obtained random walk sequence of the simulated node, and then performing synthesis to obtain an anonymous graph.

The invention provides a power distribution network mass data fusion method and device. The method includes the steps of establishing a unified data channel for multi-source data, extracting data information through the data channel, determining a data belonging individual according to the extracted data information, and establishing an analysis dataset for the data information by means of a corresponding preset fusion mode on the basis of the data belonging individual. By means of the technical scheme, the data availability of a power distribution network is improved, the fusion of static data and dynamic data is realized, the cross-system in-data service collaboration is realized, the precision of aid decision making and computational analysis of the power distribution network is improved, and the requirements of unified decision making and analysis are met.

A position representative element generation method for track data release specifically comprises the following steps: 1) based on position point index construction of a Hilbert index value curve, generating position clusters at all moments; 2) according to the privacy budget configuration of each position cluster, generating a sampling position cluster of each position cluster by using a samplingmechanism based on a privacy budget threshold; 3) applying a differential privacy index mechanism to each sampling position cluster to select a representative element of the position cluster; and 4)replacing the original position point in each position cluster with the position representative element to realize generalization of the original trajectory data. The method provided by the inventioncan ensure that the privacy protection requirement of a data provider is satisfied in a trajectory data publishing mode, provides strict privacy guarantee, and improves the availability of the trajectory published data.

A safety storing system of network is prepared as providing file sharing function of cross-platform, optimizing share concept of network file, utilizing experienced IP Ethernet technique, applying TCP / IP protocol for data transmission, connecting S2 E product with network by utilizing mode of setting IP address of S2 E product in order to realize connection of arbitrary to arbitrary.

The invention belongs to the technical field of privacy protection, and particularly relates to a general data release privacy protection method based on a random response technology. The method is based on the random response technology, and is characterized in that the calculation complexity of the reconstructed unbiased estimation result is reduced from exponential growth to linear growth by utilizing a matrix decomposition method and the Kronecker property, the error minimization of the unbiased estimation result is realized, the privacy protection parameters are allowed to be independently set for each attribute, and the calculation efficiency, the data availability and the application flexibility are effectively improved. The method supports the data release of a single sensitive attribute and multiple sensitive attributes, wherein the sensitive attributes comprise a Boolean attribute, a classified attribute and a numerical attribute; an efficient and flexible data publishing privacy protection mechanism can be provided for the scientific research and management in the fields of medical treatment, finance, biological information, transportation and the like, the data privacyis protected in the data publishing process, the useful information of published data is reserved, and the sharing of the data is promoted.