Abstract: A storage apparatus includes a plurality of storage devices, and a control unit for providing a predetermined storage area of the plurality of storage devices to the host computer as a virtual volume group including one or more virtual volumes. The control unit configures one or more data sets having one or more redundancy levels from the plurality of storage devices, provides a storage area of a storage pool including the plurality of data sets to a part of a storage area of the virtual volume, limits a combination of the storage devices configuring the data sets to be assigned to the virtual volume to a given number of combinations of two combinations or more, uniformly distributes the storage devices, and uses a given number of different combinations of the storage devices to be assigned to the virtual volume in units of the virtual volume group.

Abstract: To reduce a calculation processing load as a whole while realizing a small amount of data loss for at least one of compression and decompression. For each of a plurality of pieces of data, a storage system determines a compression operation scale of the data based on a feature of the data, executes a lossy compression operation according to the determined compression operation scale to covert the data into encoded data, and stores the encoded data or compressed data thereof into a storage device.

Abstract: To generate an optimum compressor irrespective of the number of dimensions and a format of a multidimensional dataset. A storage system refers to dimension setting information, which is information representing an attribute for each of data dimensions of the multidimensional dataset, and generates a compressor based on the dimension setting information.

Abstract: A first node group including at least three nodes is predefined in a distributed storage system. Each node of the first node group is configured to send data blocks stored in storage devices managed by the node to other nodes belonging to the first node group. A first node is configured to receive data blocks from two or more other nodes in the first node group. The first node is configured to create a redundant code using a combination of data blocks received from the two or more other nodes and store the created redundant code to a storage device different from storage devices holding the data blocks used to create the redundant code. Combinations of data blocks used to create at least two redundant codes in redundant codes created by the first node are different in combination of logical addresses of constituent data blocks.

Abstract: Provided is a data processing system which includes a processor and a storage device, and inputs/outputs data using a learned compander that compresses and expands data, wherein the data processing system comprises an estimation unit which uses learning data and estimates a region of interest to a data model, and a learning unit which causes the compander to learn according to an evaluation function in which each region was weighted based on the region of interest, and a result of the compander compressing and expanding the learning data.

Abstract: A virtual storage system according to an aspect of the present invention includes multiple storage systems each including: a storage controller that accepts a read/write request for reading or writing from and to a logical volume; and multiple storage devices. The storage system defines a pool that manages the storage device capable of allocating any of storage areas to the logical volume, and manages the capacity (pool capacity) of the storage areas belonging to the pool, and the capacity (pool available capacity) of unused storage areas in the pool. Furthermore, the storage system calculates the total value of the pool available capacities of the storage systems included in the virtual storage system, and provides the server with the total value as the pool available capacity of the virtual storage system.

Abstract: The present disclosure provides an information compression system that is capable of achieving higher compression efficiency. A data acquisition section acquires data. A generation section (segmentation section and integration section) determines each object depicted by the data and a sense of each object, and according to results of the determination, generates compression target data by converting values of elements in the data to identification information indicating each object and the sense of each object. A data storage section generates compressed data by compressing the compression target data. This makes it possible to convert highly random element values to slightly random identification information and compress the resulting converted information while reducing the amount of information. Consequently, the compression ratio can be increased.

Abstract: A data compression system compresses original data by a first lossy compression method to generate first compressed data, decompresses the first compressed data to generate first decompressed data, extracts residual information between the original data and the first decompressed data, compresses the residual information by a second lossy compression method different from the first lossy compression method to generate second compressed data, and stores the first compressed data and the second compressed data in the one or more storage devices.

Abstract: A storage system monitors the first access frequency of occurrence which is the access frequency of occurrence from a host device during a first period, and the second access frequency of occurrence which is the access frequency of occurrence from a host device during a second period shorter than the first period. Along with performing data relocation among the tiers (levels) in the first period cycle based on the first access frequency of occurrence, the storage system performs a decision whether or not to perform a second relocation based on the first access frequency of occurrence and the second access frequency of occurrence, synchronously with access from a host device. Here the threshold value utilized in a decision on whether or not to perform the first relocation is different from the threshold value utilized in a decision on whether or not to perform the second relocation.

Abstract: A data compression processing system includes: a selection unit configured to select a compression processing setting to be applied to processing target data from among a plurality of compression processing settings; and a compression processing unit configured to compress the processing target data according to the compression processing setting selected by the selection unit. The selection unit is configured to: receive a condition required for compression processing of the processing target data; apply a plurality of compression processing settings applicable to the processing target data to evaluation data to perform compression processing; select, from the plurality of compression processing settings, a setting that satisfies the condition when applied to the processing target data based on a result of the compression processing for the evaluation data; and manage the selected compression processing setting in association with the condition.

Abstract: To provide a data compression/decompression system that can appropriately decompress compressed data. A first computer generates first identification information that can identify a first execution environment; and stores the first identification information on a storage device in association with compressed data of data. A second computer generates second identification information that can identify a second execution environment; and determines whether or not the first identification information, and the second identification information match.

Abstract: In write processing of a data set group to be written to be one or more data sets to be written, a storage system performs encoding processing including processing for generating a data model showing regularity of the data set group to be written and having one or more input values as an input and the data set group as an output. In the write processing, the storage system writes the data model generated in the encoding processing and associated with a key of the data set group to be written.

Abstract: A first node group including at least three nodes is predefined in a distributed storage system. Each node of the first node group is configured to send data blocks stored in storage devices managed by the node to other nodes belonging to the first node group. A first node is configured to receive data blocks from two or more other nodes in the first node group. The first node is configured to create a redundant code using a combination of data blocks received from the two or more other nodes and store the created redundant code to a storage device different from storage devices holding the data blocks used to create the redundant code. Combinations of data blocks used to create at least two redundant codes in redundant codes created by the first node are different in combination of logical addresses of constituent data blocks.

Abstract: A storage system that performs irreversible compression on time-series data using a compressor/decompressor based on machine learning calculates a statistical amount value of each of one or more kinds of statistical amounts based on one or more parameters in relation to original data (time-series data input to a compressor/decompressor) and calculates a statistical amount value of each of the one or more kinds of statistical amounts based on the one or more kinds of parameters in relation to decompressed data (time-series data output from the compressor/decompressor) corresponding to the original data. The machine learning of the compressor/decompressor is performed based on the statistical amount value calculated for each of the one or more kinds of statistical amounts in relation to the original data and the statistical amount value calculated for each of the one or more kinds of statistical amounts in relation to the decompressed data.

Abstract: Both of a high compression ratio and a high processing speed are achievable. In a data compression and decompression system that includes a parallel processing device performing a plurality of processes in parallel, the parallel processing device divides original data into a plurality of data by a predetermined unit. The parallel processing device performs coding processes on the plurality of data in parallel using a predetermined model to create a plurality of coded data. The parallel processing device creates compressed data of the original data from the plurality of coded data.

Abstract: To generate an optimum compressor irrespective of the number of dimensions and a format of a multidimensional dataset. A storage system refers to dimension setting information, which is information representing an attribute for each of data dimensions of the multidimensional dataset, and generates a compressor based on the dimension setting information.

Abstract: Provided is a data processing system comprising a compression/expansion unit configured by including a compressor which compresses data, and an expander which expands the data compressed by the compressor, wherein the compression/expansion unit comprises a first interface unit capable of outputting configuration information of the compressor, and a second interface unit capable of outputting the data compressed by the compressor.

Abstract: Provided is a data processing system which includes a processor and a storage device, and inputs/outputs data using a learned compander that compresses and expands data, wherein the data processing system comprises an estimation unit which uses learning data and estimates a region of interest to a data model, and a learning unit which causes the compander to learn according to an evaluation function in which each region was weighted based on the region of interest, and a result of the compander compressing and expanding the learning data.

Abstract: An object of the invention is to optimize a storage cost for data. There is provided a storage system including a storage device, a memory, and a processor configured to control input and output of data to and from the storage device. The processor monitors a storage amount that is at least one of a write amount (a total amount of data received as a write target) and a physical use amount (a total amount of data physically stored in the storage device), and a read amount (a total amount of data that is read), and calculates a fee as a storage cost that is a cost related to use of the storage device in a target period, based on a storage amount and a read amount in the target period in accordance with a monitoring result.

Abstract: A first node group including at least three nodes is predefined in a distributed storage system. Each node of the first node group is configured to send data blocks stored in storage devices managed by the node to other nodes belonging to the first node group. A first node is configured to receive data blocks from two or more other nodes in the first node group. The first node is configured to create a redundant code using a combination of data blocks received from the two or more other nodes and store the created redundant code to a storage device different from storage devices holding the data blocks used to create the redundant code. Combinations of data blocks used to create at least two redundant codes in redundant codes created by the first node are different in combination of logical addresses of constituent data blocks.