Storage device, server, system, cost index method and program

Abstract

To provide a storage device that can reduce costs according to a value of data.SOLUTION: A storage device comprises: an access information acquisition unit for acquiring access information indicating, for each file, writing or reading of data to or from a storage unit; an average file size acquisition unit for acquiring an average file size of a set of files; a usage determination unit for determining a usage of the set of files based on the access information and the average file size; and a cost index calculation unit for calculating a cost index for the set of files according to the usage.SELECTED DRAWING: Figure 13

Description

[Technical Field]

[0001] The present disclosure relates to a storage device, a server, a system, a cost indexing method, and a program. [Background technology]

[0002] It is known to determine the cost of storing data in a storage device based on the amount of data read within a certain period of time.

[0003] For example, Patent Document 1 describes a storage system having a storage device, a memory, and a processor that controls data input / output to the storage device, wherein the processor monitors the amount of storage and the amount of reads, the amount of storage being at least one of the amount of writes and the amount of physical usage, the amount of writes being the total amount of data accepted as a write target, and the amount of physical usage being the total amount of data physically stored in the storage device, and the processor calculates a fee for a target period as a storage cost, which is the cost related to the use of the storage device, based on the amount of storage and the amount of reads for the target period in accordance with the results of the monitoring, and the processor further determines the fee for the target period based on the amount of reads prior to the target period. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 7107877 Summary of the Invention [Problem to be solved by the invention]

[0005] In the storage device disclosed in Patent Document 1, in order to reduce storage costs, a storage provider that provides storage services combines charging according to the amount of data stored with charging according to the amount of data read as a data value charge, thereby lowering the unit price of data storage for storage users. However, because the value of data is determined only by the amount of data read, for storage users, in the case of data that has a large amount of read but no actual value, combining charging according to the amount of data stored with charging according to the amount of data read does not reduce costs according to the value of the data.

[0006] An object of the present disclosure is to provide a storage device, a server, a system, a cost indexing method, and a program that solve the above-mentioned problems. [Means for solving the problem]

[0007] A storage device according to one aspect of the present disclosure includes an access information acquisition unit that acquires access information indicating, for each file, the writing or reading of data to or from a memory unit; an average file size acquisition unit that acquires the average file size of a set of files; a usage determination unit that determines the usage of the set of files based on the access information and the average file size; and a cost index calculation unit that calculates a cost index for the set of files according to the usage.

[0008] A server according to one aspect of the present disclosure includes an acquisition unit that acquires the cost index of the set of files and the amount of data stored in the memory unit from a storage device that includes an access information acquisition unit that acquires access information indicating for each file the writing or reading of data to or from a memory unit, an average file size acquisition unit that acquires the average file size of a set of files, a usage determination unit that determines the usage of the set of files based on the access information and the average file size, and a cost index calculation unit that calculates a cost index of the set of files according to the usage, and a cost calculation unit that calculates the cost of the set of files based on the cost index and the amount of data stored in the memory unit.

[0009] A storage system according to one aspect of the present disclosure comprises a storage device including an access information acquisition unit that acquires access information indicating for each file the writing or reading of data to or from a memory unit, an average file size acquisition unit that acquires the average file size of a set of files, a usage determination unit that determines the usage of the set of files based on the access information and the average file size, and a cost index calculation unit that calculates a cost index for the set of files according to the usage; an acquisition unit that acquires from the storage device the cost index for the set of files and the amount of data stored in the memory unit; and a cost calculation unit and server that calculate the cost of the set of files based on the cost index and the amount of data.

[0010] A cost indexing method according to one aspect of the present disclosure includes the steps of obtaining access information indicating the writing or reading of data to or from a storage unit for each file, obtaining an average file size of a set of files, determining a use of the set of files based on the access information and the average file size, and calculating a cost index for the set of files according to the use.

[0011] A program according to one aspect of the present disclosure is a program for causing a computer to execute the steps of acquiring access information indicating the writing or reading of data to or from a memory unit for each file, acquiring an average file size of a set of files, determining a use of the set of files based on the access information and the average file size, and calculating a cost index for the set of files according to the use. [Effects of the Invention]

[0012] According to the above aspect, it is possible to reduce the cost of data stored in storage in accordance with the value of the data. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 illustrates an example of a configuration of a storage system according to the present disclosure. [Figure 2] FIG. 11 is a diagram I showing an example of processing of the storage device according to the present disclosure. [Figure 3] FIG. 2 is a diagram II showing an example of processing of the storage device according to the present disclosure. [Figure 4] FIG. 3 is a diagram III showing an example of processing of the storage device according to the present disclosure. [Figure 5] FIG. IV shows an example of processing by the storage device according to the present disclosure. [Figure 6] FIG. 5 is a diagram V showing an example of processing of the storage device according to the present disclosure. [Figure 7] FIG. 6 is a diagram VI showing an example of processing of the storage device according to the present disclosure. [Figure 8] FIG. 7 is a diagram showing an example of processing of the storage device according to the present disclosure. [Figure 9] 1 is a flowchart I showing an example of processing of a cost indexing method according to the present disclosure. [Figure 10] FIG. 10 is a diagram illustrating an example of processing by a server in a modified example. [Figure 11] FIG. 10 is a diagram illustrating an example of processing by a server in a modified example. [Figure 12] 10 is a flowchart I showing an example of processing of a method implemented by a server according to the present disclosure. [Figure 13] FIG. 1 is a diagram illustrating an example of a configuration of a storage device according to an embodiment of the present disclosure. [Figure 14] FIG. 2 is a diagram illustrating an example of a configuration of a server according to an embodiment of the present disclosure. [Figure 15] 10 is a flowchart II illustrating an example of processing of a cost indexing method according to an embodiment of the present disclosure. [Figure 16] 10 is a flowchart II illustrating an example of a process of a method implemented by a server according to an embodiment of the present disclosure. [Figure 17] FIG. 2 is a hardware configuration diagram illustrating the configuration of a computer in a storage device according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0014] Each embodiment will be described below with reference to the drawings. In all drawings, the same or corresponding components are designated by the same reference numerals, and common descriptions will be omitted.

[0015] First Embodiment Hereinafter, an embodiment according to the present disclosure will be described with reference to the drawings.

[0016] (Storage system configuration) The storage system 1 is used to calculate a cost index for each folder based on access information indicating the writing or reading of data to the storage unit, the average file size of the data folder, and the file attribute information of each file in the folder, and to calculate costs based on the calculated cost index and the data volume of a set of files.

[0017] 1, the storage system 1 includes a storage device 11 and a server 12. The storage device 11 is communicably connected to a client 3 via a network 2. In the following description, the network 2 is, for example, the Internet, but is not limited to this.

[0018] In an example of the present disclosure described in detail below, a folder is a block of data such as a set of files. The folder is intended to be the root folder of the object storage or a folder immediately below it, but this is just an example and may be a folder for each user or a folder for each billing unit.

[0019] (Storage device configuration) The storage device 11 writes or reads data to or from the storage unit 110 in response to an access request received from a client 3 connected via the network 2. The file service protocol by which the storage device 11 provides file access to the client 3 may be any file service protocol.

[0020] The storage device 11 records a history of the contents of data written to or read from the storage unit 110. Fig. 2 is a diagram showing an example of an access history table that the storage device 11 uses to record the history of the contents of data written to or read from the storage unit 110.

[0021] The access history table records, for example, the access time indicating the time when data was written to or read from the storage unit 110, the source of the access, the access type, the data size indicating the size of the data, and the file path indicating the location where the accessed data is stored. There are two access types: "Write" and "Read." "Write" indicates writing data to the storage unit and means storing or updating. "Read" indicates reading data from the storage unit.

[0022] 2, the first record has a timestamp of "2023 / 1 / 1 10:00:00" indicating the time of access to the storage unit 110, the access source that issued the access request is "Hoge\user1", the access type is "Write", the data size is "4KB", and the file path is " / 00001 / 0123456789 / text.txt". The second record has a timestamp of "2023 / 1 / 1 10:03:30" indicating the time of access to the storage unit 110, the access source that issued the access request is "Hoge\systemuser", the access type is "Read", the data size is "4KB", and the file path is " / 00001 / 0123456789 / text.txt", so it can be seen that the data indicated by the first record was read.

[0023] As shown in FIG. 1, the storage device 11 includes an access information acquisition unit 111, an average file size acquisition unit 112, a file attribute information acquisition unit 113, a usage determination unit 114, a cost index calculation unit 115, and an update unit 116.

[0024] The operation of each unit in the storage device 11 described below corresponds to the cost indexing method of the present disclosure.

[0025] (Access information acquisition section) The access information acquisition unit 111 acquires access information that indicates writing or reading of data to or from the storage unit 110 .

[0026] The access information is, for example, the type of access stored in the access history table shown in Fig. 2. There are two types of access: "Write" and "Read." "Write" indicates writing data to the storage unit 110, meaning storing or updating. "Read" indicates reading data from the storage unit 110.

[0027] (Average file size acquisition section) The average file size acquisition unit 112 acquires the average file size of a set of files. Specifically, the average file size acquisition unit 112 acquires the average file size of the files included in the folder based on the data size of each file in the access history table shown in FIG.

[0028] The average file size is the average size calculated for each folder for files accumulated in the storage unit 110 over a certain period of time. The certain period is, for example, a period set for determining prices, such as one day, one month, or one year. The length of the certain period is set depending on whether real-time determination of data indexes and prices is required. If real-time determination is required, the period is set to be short.

[0029] (File attribute information acquisition part) The file attribute information acquisition unit 113 acquires file attribute information for each file in a set of files. Specifically, the file attribute information acquisition unit 113 acquires file attribute information based on the file path recorded in the access history table shown in FIG. 2. The file path is information indicating where a file is stored in the storage unit 110, and includes a file extension. The file extension indicates file attributes such as the file format. Examples of extensions include ".txt" indicating a text file and ".mp4" indicating a video file.

[0030] (Application determination department) The use determination unit 114 determines the use of a set of files based on the access information and average file size. The use determination unit 114 may also be configured to determine the use of a set of files using file attributes in addition to the access information and average file size. The use determination unit 114 determines which of the predefined uses a folder corresponds to. For example, as shown in the use classification table of FIG. 3, folder uses are set as big data, distribution, and other data. Here, big data refers to data collected periodically using Internet of Things (IoT) technology. In recent years, with the development of technologies such as IoT (Internet of Things), which connects all kinds of things to the Internet, so-called big data, which are huge data groups that are difficult for humans to grasp in their entirety, have been created. Big data is expected to contribute to the creation of new value in industry through its use in situations such as highly accurate predictions and real-time processing of diversified data, but the massive amount of collected data must be stored.

[0031] The distribution data is, for example, audiovisual and video data distributed via the Internet.

[0032] Data other than big data and distribution data is classified as other data, including office use, backups, archives, databases, VDI (virtual desktops), and temporary workspaces.

[0033] By using the usage classification table, it is possible to set classifications according to the value judgment of data, taking into account that the characteristics of data change with changes in technology and trends in usage methods.

[0034] The usage determination unit 114 determines the usage of the folder as one of the usages shown in the usage classification table of Fig. 3, with reference to the access pattern table shown in Fig. 4 and the file pattern table shown in Fig. 5. In the access pattern table shown in Fig. 4, criteria for each folder are previously defined as judgment items for the access pattern, including "number of writes," "number of reads," "average number of writes," "average number of reads," "write periodicity," and "read periodicity." In the file pattern table shown in Fig. 5, "file size," "average file size," "extension," and "file type" are previously defined for each folder.

[0035] The use determination unit 114 determines the use of the folder according to the flow shown in FIG.

[0036] 4 shows an example of an access pattern table used for analyzing access patterns. In the access pattern table, the number of writes is the total number of writes for all files contained in a folder during a predetermined period, the number of reads is the total number of reads for all files contained in a folder during a predetermined period, the average number of writes is the total number of writes for all files contained in a folder during a predetermined period divided by the number of files, and the average number of reads is the total number of reads for all files contained in a folder during a predetermined period divided by the number of files.

[0037] The usage determination unit first uses the access pattern table shown in FIG. 4 to determine, for each folder, whether the average number of reads is greater than a predetermined threshold (step S11). The average number of reads is, for example, one even when all stored files are read. Therefore, as an example, the predetermined threshold is set to three times. However, the period set for determining the cost of a folder is set depending on whether real-time performance is required for determining the data index and price, and is set to a shorter period if real-time performance is required. Therefore, the meaning of the index will be different if it is set to one month versus one day, even if the same number of reads is three times. Therefore, the threshold is designed in accordance with the period set for determining the cost.

[0038] If the average read count is greater than the predetermined threshold (step S11: YES), the access pattern table shown in FIG. 4 is used to determine whether the average write count for the folder is less than the predetermined threshold (step S12). For example, since the average write count is 1 in the initial state where all stored files have been written, the threshold is set to 1.2 times as an example of a state where no updates or deletions have been performed. If the average write count is less than the predetermined threshold (step S12: YES), the system determines whether a certain number of files in the folder have a predetermined file extension (step S13). The predetermined file extension may be, for example, an extension indicating an image, music, video, or web file. The certain number for determining that the majority of files in the folder have the predetermined file extension may be, for example, 80% of all files in the folder that have the predetermined file extension. While the case where the determination is made using the predetermined file extension has been described here, the file type may also be determined by a method other than the extension, for example, by reading the beginning of the file. If it is determined that the folder contains a certain number of files with a predetermined file extension or more (step S13: YES), the folder's use is determined to be distribution data (step S14).If it is determined that the folder does not contain a certain number of files with a predetermined file extension or more (step S13: NO), the folder's use is determined to be other use (step S15).

[0039] If the average number of writes to the folder is greater than or equal to a predetermined threshold (step S12: NO), or if it is determined that there are not a certain number of files with a predetermined file extension in the folder (step S13: NO), the folder's use is determined to be office work, database, VDI, temporary work area, or other data (step S15).

[0040] If it is determined in step S11 that the average number of reads is not greater than a predetermined threshold (step S11: YES), it is determined whether or not there is periodicity in the writes (storage or update) (step S16). The periodicity of the writes can be determined, for example, by converting the access pattern plotted on the time axis to the frequency axis using a Fourier transform and judging from the sharpness of the peaks. If there is periodicity in the writes (step S16: YES), it is determined whether or not there are reads (step S17). If there are no reads (step S17: NO), it is determined whether or not the average file size is greater than a threshold (step S18). The file size threshold is, for example, 1 GB. This takes into consideration that, for example, backup files will be archived and compressed, and stored as data in a virtual tape device. If the average file size is greater than the threshold (step S18: YES), the folder's use is determined to be, for example, for backup, and is set to "other" (step S20).

[0041] If it is determined in step S17 that there is a Read (step S17: YES), and if it is determined in step S18 that the average file size is not larger than the threshold (step S18: NO), the folder is determined to be used for big data (step S19).

[0042] In step S16, if it is determined that there is no periodicity in Write (step S16: NO), there is no periodicity in Read / Write, and therefore the use of the folder is determined to be "other" such as office data, archive data, etc.

[0043] (Cost Index Calculation Section) The cost index calculation unit 115 calculates the cost index of a set of files according to their intended use.

[0044] The cost index calculation unit 115 refers to the cost index calculation table shown in FIG. 7 and calculates a cost index for each folder using a cost usage calculation formula according to the use determined by the use determination unit 114.

[0045] For example, in the cost index calculation table of Fig. 7, if the folder is used for big data, the cost index calculation formula is Read presence / absence × Type of access source × Data increase presence / absence × Access pattern presence / absence. The cost index calculation unit 115 determines the weight for each parameter used in the cost index by referring to the cost index calculation sub-table shown in Fig. 8.

[0046] For example, the access patterns of the access pattern sub-table may be based on periodic reading of data from the storage unit and data that has not yet passed a predetermined period of time since being stored in the storage unit.

[0047] For example, if the folder's use is big data, there is read, the access source is a general user, there is data increase, and there is neither periodic reading of data from the storage unit (periodic read) nor data that has not yet passed a specified period since being stored in the storage unit (new data), then the cost index = (whether or not there is read (1)) x (type of access source (1)) x (whether or not there is data increase (5)) x (whether or not there is access pattern (1)) = 1 x 1 x 5 x 1 = 5.

[0048] As another example, if the folder is used for distribution, the cost is calculated using the number of reads per file. For example, if the number of reads of that file is 50 times in a month, the cost index = (number of reads) = 50.

[0049] (Update section) The update unit 116 updates the cost index to a new cost index on a predetermined date. The cost index may be stored in the storage unit 110, for example, or may be stored in a separate storage unit.

[0050] Here, the predetermined date is, for example, the date on which the price is periodically determined in an embodiment in which price reviews are performed. For example, if the price is reviewed once a month, the date is set to the last day of each month. The price review interval may be, for example, once a year, monthly, or daily. The shorter the price review interval, the more real-time the value judgment of the data and its reflection in the price. However, since the threshold must be designed to be low, the value judgment becomes too sensitive and more susceptible to errors. Therefore, if the value judgment is data that is not easily affected by errors and the real-time nature of the price is emphasized, the price review interval may be set to, for example, daily. However, if the impact of errors on the value judgment is more important than the real-time nature of the price, the price review interval may be set to, for example, monthly.

[0051] (Cost indexing method) The cost indexing method in this embodiment will be described.

[0052] The cost indexing method in this embodiment is carried out according to the flow shown in FIG.

[0053] First, the access information acquisition unit 111 of the storage device 11 acquires access information indicating the writing or reading of data to or from the memory unit 110 for each file (step S111).

[0054] Next, the average file size acquisition unit 112 of the storage device 11 acquires the average file size of the set of files (step S112).

[0055] The file attribute information acquisition unit 113 of the storage device 11 acquires the file attribute information of each file in the set of files (step S113).

[0056] The use determination unit of the storage device 11 determines the use of the set of files based on the access information, the average file size, and the file attribute information (step S114).

[0057] Specifically, the step of determining the use of the file is carried out according to the flow shown in FIG.

[0058] Next, the cost index calculation unit 115 of the storage device 11 calculates the cost index of the set of files according to the purpose of use (step S115).

[0059] Furthermore, the update unit 116 of the storage device 11 updates the cost index to a new cost index on a predetermined date (step S116). (Complete) (Action and effect) The storage device 11 of this embodiment determines the use of a set of files based on the access information, average file size, and file attribute information, and calculates a cost index for the set of files according to the use.

[0060] This makes it possible to provide an index for data stored in storage that is different from the read amount, which indicates the reading of data from storage.

[0061] (Server configuration) The server 12 is used to obtain the cost index of a folder and the file size of a file included in the folder from the storage device 11 via the network 2 and calculate the cost of the folder.

[0062] As shown in FIG. 1, the server 12 includes an acquisition unit 121 that acquires a cost index and an average file size of a set of files from the storage device 11, and a cost calculation unit 122 that calculates the data volume of the set of files from the average file size and calculates the cost of the set of files based on the cost index and the data volume.

[0063] In the present disclosure, the server 12 is configured to include the cost calculation unit 122, but the cost calculation unit 122 may be configured such that the storage device 11 includes the cost calculation unit.

[0064] (Acquisition Department) The obtaining unit 121 obtains the cost index and the average file size of a set of files.

[0065] The acquisition unit 121 acquires the cost index and the data amount for each folder from the storage device 11 via the network 2.

[0066] The cost calculation unit of the storage device 11 calculates the cost index of the folder for each predetermined date, and the update unit updates the calculated cost index. Therefore, the acquisition unit of the server can acquire the updated cost index on each predetermined date.

[0067] The amount of data can be obtained for each folder from the file size in the access information table.

[0068] (Cost Calculation Department) The cost calculation unit 122 calculates the data amount of a set of files from the average file size, and calculates the cost of the set of files based on the cost index and the data amount.

[0069] The unit price for the amount of data stored in a folder is determined based on a cost index. As an example, Figure 10 shows a unit price determination model for determining the unit price for the amount of data from a cost index. For example, the unit price is set to a constant value until the cost index reaches a specified value, and once it exceeds the specified value, the unit price is increased quadratically with respect to the cost index.

[0070] By calculating costs in this way, data with a large cost index within a predetermined range, i.e., valuable data, will have a higher unit price than data with a small cost index within a predetermined range, and data with a small cost index will have a lower unit price than data with a large cost index. This allows more fees to be collected from valuable data.

[0071] For example, as shown in Figure 11, a price calculation table is used in which the ratio of the unit price to the base unit price is set for each cost index. Referring to the price calculation table in Figure 11, the unit price for a folder with a cost index of 5 is 0.5 times the base unit price, and the unit price for a file with a cost index of 50 is twice the base unit price. In this way, the price for each folder is calculated by multiplying the calculated unit price of the cost index by the amount of data.

[0072] The cost index calculated according to the present disclosure can be applied to purposes other than calculating the price of folders. For example, when storing data and migrating it to a storage device with high redundancy, calculating a cost index for each folder makes it possible to automatically migrate the data according to the value of the data.

[0073] An example of the method according to the present disclosure will be described below with reference to FIG.

[0074] The method implemented by the server 12 includes the steps of: obtaining a cost index and an average file size of a set of files from a storage device (S21); calculating a price of the data by calculating the amount of data of the set of files from the average file size (S22); and calculating the amount of data of the set of files from the average file size and calculating the cost of the set of files based on the cost index and the amount of data (S23).

[0075] (Action and effect) According to the server of the present application, the cost index and average file size of a set of files can be obtained from a storage device via a network, the data volume of the set of files can be calculated from the average file size, and the cost of the set of files can be calculated based on the cost index and the data volume.

[0076] Therefore, for data stored in storage, it is possible to determine a unit price according to an index different from the read amount indicating the reading of data from storage.

[0077] This allows for more fees to be collected from valuable data.

[0078] For example, in the case of video or music distribution, the read volume of the video or music file is directly linked to the number of times it is played, so charging by the read volume is appropriate as a charge based on the value of the data, and the price of the data is determined according to the read volume. However, with big data, in order to create value, data may first be read repeatedly through trial and error. In such cases, the read volume increases before the value of the data is created, and a price determined according to the read volume of data whose value is unknown may be too high for storage users.

[0079] When it comes to creating value using so-called big data, it is difficult to predict in advance whether or not value can actually be created, and how much value can be created. Even if value can be created, it may take a considerable amount of time to realize that value. Since data storage costs continue to accumulate until value is actually created, if the data storage costs become an excessive burden, it may become difficult to continue the business.

[0080] Furthermore, as in Cited Document 1, when charging according to the value of big data, the value of the data is determined based on the amount of reads made to a storage device within a certain period, a mismatch may occur between the value of the data and the price within that period.

[0081] If there is a mismatch between data value and price, not only will storage users be forced to pay higher data storage costs, but storage providers may also lose opportunities to acquire new customers. Therefore, it is necessary to determine the value of data contained in big data using an index other than read volume.

[0082] In addition, the value of the data contained in big data can be determined using an index other than the read volume in addition to the read volume, which reduces the mismatch between data value and price and provides storage providers with an opportunity to acquire customers without imposing high data storage costs on storage users.

[0083] The storage device of the present disclosure can achieve the following effects by "including an access information acquisition unit 111 that acquires access information indicating the writing or reading of data to or from the memory unit 110 for each file, an average file size acquisition unit 112 that acquires the average file size of a set of files, a use determination unit 114 that determines the use of the set of files based on the access information and the average file size, and a cost index calculation unit 115 that calculates a cost index for the set of files depending on the use."

[0084] The storage device of the present disclosure obtains access information indicating the writing or reading of data to or from the memory unit 110 for each file, and an average file size that obtains the average file size of a set of files, and determines the use of the set of files based on the access information and the average file size.

[0085] A cost index for the set of files is calculated according to the determined uses.

[0086] This has the effect of "providing an index for data stored in storage that is different from the read amount that indicates the reading of data from storage."

[0087] In addition, the storage device of the present disclosure further includes a "file attribute information acquisition unit 113 that acquires file attribute information for each file in a set of files," and "the usage determination unit 114 determines the usage of a set of files based on access information, average file size, and file attribute information," thereby achieving the effect of "being able to provide an index for data stored in storage that is different from the read volume that indicates the reading of data from storage."

[0088] In addition, in the storage device disclosed herein, "when the use is big data, the cost index calculation unit 115 calculates a cost index based on whether or not a read has been performed, the access source information, whether or not the data has increased, and the access pattern," thereby making it possible to determine the value of the data contained in the big data using an index other than the read amount.

[0089] In addition, the storage device of the present disclosure further comprises an "updating unit 116 that updates the cost index to a new cost index on a predetermined date," thereby enabling timely value judgment of data.

[0090] In addition, the storage device of the present disclosure further "based on the access pattern being the periodic reading of data from the memory unit and data that has not yet passed a specified period of time since being stored in the memory unit," thereby enabling timely determination of data indices for data that requires real-time performance.

[0091] Second Embodiment Hereinafter, an embodiment according to the present disclosure will be described with reference to the drawings.

[0092] An example of a storage device according to the present disclosure will be described below with reference to FIG.

[0093] (composition) The storage device 11m includes an access information acquisition unit 111m that acquires access information indicating for each file the writing or reading of data to or from a memory unit, an average file size acquisition unit 112m that acquires the average file size of a set of files, a usage determination unit 114m that determines the usage of the set of files based on the access information and the average file size, and a cost index calculation unit 115m that calculates a cost index for the set of files in accordance with the usage.

[0094] (Action and effect) The storage device 11m of the present disclosure determines the use of a set of files based on the access information and the average file size, and calculates a cost index for the set of files according to the use.

[0095] This makes it possible to provide an index for data stored in storage that is different from the read amount, which indicates the reading of data from storage.

[0096] Third Embodiment Hereinafter, an embodiment according to the present disclosure will be described with reference to the drawings.

[0097] An example of a server in the present disclosure will be described below with reference to FIG.

[0098] (composition) The server 12m includes an acquisition unit 121m that acquires the cost index of the set of files and the amount of data stored in the memory unit from a storage device 11 that includes an access information acquisition unit 111m that acquires access information indicating for each file the writing or reading of data to or from a memory unit, an average file size acquisition unit 112m that acquires the average file size of a set of files, a usage determination unit 114m that determines the usage of the set of files based on the access information and the average file size, and a cost index calculation unit 115m that calculates a cost index of the set of files according to the usage, and a cost calculation unit 122m that calculates the cost of the set of files based on the cost index and the data amount.

[0099] (Action and effect) According to the server of this embodiment, the cost index and average file size of a set of files can be obtained from a storage device via a network, the data volume of the set of files can be calculated from the average file size, and the cost of the set of files can be calculated based on the cost index and the data volume.

[0100] Therefore, for data stored in storage, it is possible to determine a unit price according to an index different from the read amount indicating the reading of data from storage.

[0101] <Fourth embodiment> Hereinafter, an embodiment according to the present disclosure will be described with reference to the drawings.

[0102] An example of the method according to the present disclosure will be described below with reference to FIG.

[0103] The cost indexing method according to the present disclosure is carried out according to the flow shown in FIG.

[0104] The method includes the steps of: acquiring access information indicating, for each file, the writing or reading of data to or from a storage unit (S111m); acquiring an average file size of the set of files (S112m); determining a use of the set of files based on the access information and the average file size (S113m); and calculating a cost index for the set of files according to the use (S114m).

[0105] (Action and effect) According to the method of the present disclosure, the usage of the set of files is determined based on the access information and the average file size, and a cost index for the set of files is calculated according to the usage.

[0106] This makes it possible to provide an index for data stored in storage that is different from the read amount, which indicates the reading of data from storage.

[0107] Fifth Embodiment Hereinafter, an embodiment according to the present disclosure will be described with reference to the drawings.

[0108] An example of the method according to the present disclosure will be described below with reference to FIG.

[0109] The method includes a step of obtaining a cost index for a set of files and the amount of data stored in a memory unit from a storage device (S121m), and a step of calculating a cost for the set of files based on the cost index and the amount of data (S123m).

[0110] (Action and effect) According to the method of the present disclosure, the cost of a set of files can be calculated based on the cost index and the amount of data acquired from the storage device via the network.

[0111] Therefore, for data stored in storage, it is possible to determine a unit price according to an index different from the read amount indicating the reading of data from storage.

[0112] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0113] 17 is a hardware configuration diagram showing the configuration of a computer that implements the storage device according to this embodiment. The computer includes, for example, a processor, a main memory, storage, an interface, and a large-capacity storage device.

[0114] Each functional unit of the storage device described above is implemented in a computer 1100. The operation of each functional unit described above is stored in the form of a program in a storage 1130. A processor 1110 reads the program from the storage 1130, loads it into a main memory 1120, and executes the above-described processing in accordance with the program. The processor 1110 also allocates a storage area in the main memory 1120 to be used by each functional unit described above in accordance with the program.

[0115] The program may be for realizing some of the functions to be performed by the computer 1100. For example, the program may be combined with other programs already stored in the storage 1130 or other programs implemented in other devices to perform the functions. Furthermore, the computer 1100 may include a custom LSI (Large Scale Integrated Circuit) such as a PLD (Programmable Logic Device) in addition to or instead of the above configuration. Examples of PLDs include a PAL (Programmable Array Logic), a GAL (Generic Array Logic), a CPLD (Complex Programmable Logic Device), and an FPGA (Field Programmable Gate Array). In this case, some or all of the functions to be performed by the processor 1110 may be realized by the integrated circuit.

[0116] Examples of storage 1130 include a magnetic disk, a magneto-optical disk, and a semiconductor memory. Storage 1130 may be an internal medium directly connected to the bus of computer 1100, or an external medium connected to computer 1100 via interface 1140 or a communication line. When this program is distributed to computer 1100 via a communication line, computer 1100 that receives the program may load the program into main memory 1120 and execute the above-mentioned processing. The program may also be a program for realizing part of the above-mentioned functions. Furthermore, the program may be a program that realizes the above-mentioned functions in combination with another program already stored in storage 1130, i.e., a so-called differential file (differential program).

[0117] Some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes.

[0118] (Appendix 1) an access information acquisition unit that acquires access information indicating, for each file, writing or reading of data to or from the storage unit; an average file size acquisition unit for acquiring an average file size of a set of files; a usage determination unit that determines a usage of the set of files based on the access information and the average file size; a cost index calculation unit that calculates a cost index of the set of files according to the intended use; Equipped with Storage device.

[0119] (Appendix 2) a file attribute information acquisition unit that acquires file attribute information of each file in the set of files; The use determination unit determines the use of the set of files based on the access information, the average file size, and the file attribute information. 2. The storage device of claim 1.

[0120] (Appendix 3) When the use is big data, the cost index calculation unit calculates a cost index based on whether or not a read has occurred, access source information, whether or not data has increased, and an access pattern. 3. The storage device of claim 1 or 2.

[0121] (Appendix 4) and an update unit that updates the cost index to a new cost index on a predetermined date. 4. The storage device according to any one of claims 1 to 3.

[0122] (Appendix 5) the access pattern is based on periodic reading of data from the storage unit and data that has not yet passed a predetermined time since being stored in the storage unit; 5. The storage device according to any one of claims 1 to 4.

[0123] (Appendix 6) an access information acquisition unit that acquires access information indicating, for each file, writing or reading of data to or from the storage unit; an average file size acquisition unit for acquiring an average file size of a set of files; a usage determination unit that determines a usage of the set of files based on the access information and the average file size; a cost index calculation unit that calculates a cost index of the set of files according to the intended use; From a storage device comprising: an acquisition unit that acquires the cost index of the set of files and the amount of data stored in the storage unit; and a cost calculation unit that calculates the cost of the set of files based on the cost index and the amount of data; Equipped with server.

[0124] (Appendix 7) As the cost index increases, the unit price per data volume increases quadratically. A server as described in Appendix 6.

[0125] (Appendix 8) the storage device further comprises a file attribute information acquisition unit that acquires file attribute information of each file of the set of files; The use determination unit determines the use of the set of files based on the access information, the average file size, and the file attribute information. 6. A server as set forth in Appendix 6 or 7.

[0126] (Appendix 9) When the use is big data, the cost index calculation unit calculates a cost index based on whether or not a read has occurred, access source information, whether or not data has increased, and an access pattern. A server as set forth in any one of appendices 6 to 8.

[0127] (Appendix 10) The storage device further includes an update unit that updates the cost index to a new cost index on a predetermined date. 10. The storage device according to any one of appendixes 6 to 9.

[0128] (Appendix 11) the access pattern is based on periodic reading of data from the storage unit and data that has not yet passed a predetermined time since being stored in the storage unit; 11. The storage device according to any one of appendixes 6 to 10.

[0129] (Appendix 12) an access information acquisition unit that acquires access information indicating, for each file, writing or reading of data to or from the storage unit; an average file size acquisition unit for acquiring an average file size of a set of files; a usage determination unit that determines a usage of the set of files based on the access information and the average file size; a cost index calculation unit that calculates a cost index of the set of files according to the intended use; a storage device comprising: From the storage device, an acquisition unit that acquires the cost index of the set of files and the amount of data stored in the storage unit; a cost calculation unit that calculates the cost of the set of files based on the cost index and the data amount; Equipped with Storage system.

[0130] (Appendix 13) a file attribute information acquisition unit that acquires file attribute information of each file in the set of files; The use determination unit determines the use of the set of files based on the access information, the average file size, and the file attribute information. 13. The storage system of claim 12.

[0131] (Appendix 14) When the use is big data, the cost index calculation unit calculates a cost index based on whether or not a read has occurred, access source information, whether or not data has increased, and an access pattern. 14. The storage system of claim 12 or 13.

[0132] (Appendix 15) and an update unit that updates the cost index to a new cost index on a predetermined date. 15. The storage system of any one of appendices 12 to 14.

[0133] (Appendix 16) the access pattern is based on periodic reading of data from the storage unit and data that has not yet passed a predetermined time since being stored in the storage unit; 16. The storage system of any one of appendices 12 to 15.

[0134] (Appendix 17) obtaining access information indicating, for each file, whether data is written to or read from the storage unit; obtaining an average file size for a set of files; determining a usage of the set of files based on the access information and the average file size; calculating a cost index for the set of files according to the usage; Contains Cost indexation methods.

[0135] (Appendix 18) obtaining file attribute information for each file in the set of files; The step of determining the use determines the use of the set of files based on the access information, the average file size, and the file attribute information. The cost indexing method described in Appendix 17.

[0136] (Appendix 19) When the use is big data, the step of calculating the cost index calculates the cost index based on whether or not a read has occurred, access source information, whether or not data has increased, and an access pattern. 18. A cost indexing method as set forth in Appendix 16 or 17.

[0137] (Appendix 20) further comprising updating the cost index to a new cost index on a predetermined date. 20. A cost indexing method according to any one of appendices 16 to 19.

[0138] (Appendix 21) the access pattern is based on periodic reading of data from the storage unit and data that has not yet passed a predetermined time since being stored in the storage unit; 21. A cost indexing method according to any one of appendices 16 to 20.

[0139] (Appendix 22) obtaining access information indicating, for each file, whether data is written to or read from the storage unit; obtaining an average file size for a set of files; determining a usage of the set of files based on the access information and the average file size; and calculating a cost index for the set of files according to the intended use.

[0140] (Appendix 23) further causing the computer to perform a step of obtaining file attribute information for each file in the set of files; The step of determining the use determines the use of the set of files based on the access information, the average file size, and the file attribute information. 22. The program of claim 1.

[0141] (Appendix 24) When the use is big data, the step of calculating the cost index calculates the cost index based on whether or not a read has occurred, access source information, whether or not data has increased, and an access pattern. 24. The program of claim 22 or 23.

[0142] (Appendix 25) and further causing the computer to execute a step of updating the cost index to a new cost index on a predetermined date. 25. The program of any one of appendices 22 to 24.

[0143] (Appendix 26) the access pattern is based on periodic reading of data from the storage unit and data that has not yet passed a predetermined time since being stored in the storage unit; 26. The program of any one of appendices 22 to 25. [Explanation of symbols]

[0144] 1. Storage System 2 Network 3 Client 11 Storage devices 11m storage device 12 Servers 12m server 110 Storage section 111 Access Information Acquisition Unit 111m Access Information Acquisition Department 112 Average file size acquisition section 112m Average file size acquisition section 113 File attribute information acquisition unit 114 Application determination section 114m Application determination section 115 Cost Index Calculation Unit 115m Cost Index Calculation Section 116 Update Department 121 Acquisition Department 121m Acquisition Department 122 Cost Calculation Department 122m Cost Calculation Department 1100 Computer 1110 processor 1120 main memory 1130 Storage 1140 Interface

Claims

1. an access information acquisition unit that acquires access information indicating, for each file, writing or reading of data to or from the storage unit; an average file size acquisition unit for acquiring an average file size of a set of files; a usage determination unit that determines a usage of the set of files based on the access information and the average file size; a cost index calculation unit that calculates a cost index of the set of files according to the intended use; Equipped with Storage device.

2. a file attribute information acquisition unit that acquires file attribute information of each file in the set of files; The use determination unit determines the use of the set of files based on the access information, the average file size, and the file attribute information. The storage device according to claim 1 .

3. When the use is big data, the cost index calculation unit calculates a cost index based on whether or not a read has occurred, access source information, whether or not data has increased, and an access pattern.

3. The storage device according to claim 1.

4. and an update unit that updates the cost index to a new cost index on a predetermined date. The storage device according to claim 1 .

5. the access pattern is based on periodic reading of data from the storage unit and data that has not yet passed a predetermined time since being stored in the storage unit; The storage device according to claim 3 .

6. an access information acquisition unit that acquires access information indicating, for each file, writing or reading of data to or from the storage unit; an average file size acquisition unit for acquiring an average file size of a set of files; a usage determination unit that determines a usage of the set of files based on the access information and the average file size; a cost index calculation unit that calculates a cost index of the set of files according to the intended use; From a storage device comprising: an acquisition unit that acquires the cost index of the set of files and the amount of data stored in the storage unit; and a cost calculation unit that calculates the cost of the set of files based on the cost index and the amount of data. Equipped with server.

7. As the cost index increases, the unit price per data volume increases quadratically. The server of claim 6.

8. an access information acquisition unit that acquires access information indicating, for each file, writing or reading of data to or from the storage unit; an average file size acquisition unit for acquiring an average file size of a set of files; a usage determination unit that determines a usage of the set of files based on the access information and the average file size; a cost index calculation unit that calculates a cost index of the set of files according to the intended use; a storage device comprising: From the storage device, an acquisition unit that acquires the cost index of the set of files and the amount of data stored in the storage unit; and a cost calculation unit that calculates the cost of the set of files based on the cost index and the amount of data. A server; Equipped with Storage system.

9. obtaining access information indicating, for each file, whether data is written to or read from the storage unit; obtaining an average file size for a set of files; determining a usage of the set of files based on the access information and the average file size; calculating a cost index for the set of files according to the usage; Contains Cost indexation methods.

10. obtaining access information indicating, for each file, whether data is written to or read from the storage unit; obtaining an average file size for a set of files; determining a usage of the set of files based on the access information and the average file size; and calculating a cost index for the set of files according to the intended use.

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