WO2016112999A1

WO2016112999A1 - Number of revisions of file to store based on category

Info

Publication number: WO2016112999A1
Application number: PCT/EP2015/061390
Authority: WO
Inventors: Saurabh Gupta; Reuti Raman Babu
Original assignee: Longsand Limited
Priority date: 2015-01-16
Filing date: 2015-05-22
Publication date: 2016-07-21

Abstract

Examples provide way to determine a number of revisions of a file to store based on a category. For example, a rule may categorize a file based on characteristics of the file. A number of revisions of the file to store may be determined based on the categorization of the file. The categorization may relate to an importance of the file.

Description

N UMBER OF REVISIONS OF FILE TO STORE BASED ON CATEGORY

BACKGROUND

[0001 ] Device or systems may provide a backup feature. A backup, or the process of backing up may refer to the copying and archiving of computer data so it may be used to restore the original after a data loss event. Oftentimes, multiple copies of the data are stored, where each of the copies may represent a different version of the data. Manufacturers, vendors, and/or service providers are challenged to provide improved backup features to better assist the user.

BRIEF DESCRIPTION OF THE DRAWINGS

[0002] The following detailed description references the drawings, wherein:

[0003] FIG. 1 is an example block diagram of a device to determine a number of revisions of a file to store based on a category;

[0004] FIG. 2 is another example block diagram of a device to determine a number of revisions of a file to store based on a category;

[0005] FIG. 3 is an example block diagram of a computing device including instructions for determining a number of revisions of a file to store based on a category; and

[0006] FIG. 4 is an example flowchart of a method for determining a number of revisions of a file to store based on a category. DETAILED DESCRIPTION

[0007] Specific details are given in the following description to provide a thorough understanding of embodiments. However, it will be understood that embodiments may be practiced without these specific details. For example, systems may be shown in block diagrams in order not to obscure embodiments in unnecessary detail. In other instances, well-known processes, structures and techniques may be shown without unnecessary detail in order to avoid obscuring embodiments.

[0008] Information generation is increasing exponentially today. In conjunction, so is the need for efficient backup software. There are multiple types of backup solutions. Some solutions just provide syncing functionality. Other solutions may retain multiple revisions of the files backed up based upon rules configured by the administrator. However, such rules are applicable to all the files in the same light.

[0009] Thus, current backup solutions are not intelligent enough to determine how many revisions of a file need to be retained. These solutions only retain a fixed number of revisions that are configured by the administrator, which is neither efficient nor suitable to all kinds of files.

[0010] Examples may dynamically determine a number of revisions of a file to retain based on characteristics of the file. An example device may include a rule unit and a revision unit. The rule unit may include a rule to categorize a file based on characteristics of the file. The revision unit may determine a number of revisions of the file to store based on the categorization of the file. The categorization may relate to an importance of the file. [001 1 ] Thus, examples may provide a backup solution to the users where they can retain as many revisions of files as may be required based upon the level of importance of that file to the user. Hence, more important files may have a greater number of the revisions retained and less important files may have a lessor number of the revisions retained. Also, examples may save storage space by retaining a fewer number of revisions of files that are not as important.

[0012] Referring now to the drawings, FIG. 1 is an example block diagram of a device 100 to determine a number of revisions of a file to store based on a category. The device 100 may be a microprocessor, a controller, a memory module or device, a notebook computer, a desktop computer, an all-in-one system, a server, a network device, a wireless device, or any other type of device capable of interacting with a storage device and/or intercepting a file along a network.

[0013] The device 100 is shown to include a rule unit 1 10 and a revision unit 120. The rule and revision units 1 10 and 120 may include, for example, a hardware device including electronic circuitry for implementing the functionality described below, such as control logic and/or memory. In addition or as an alternative, the rule and revision units 1 10 and 120 may be implemented as a series of instructions encoded on a machine-readable storage medium and executable by a processor.

[0014] A user may have a file that is to be backed up. The file may be a document, image, audio, video, source code, compressed file, disk volume image (such as a disc or virtual machine image), software and the like.

[0015] The rule unit 1 10 may include a rule to categorize a file based on characteristics of the file. The revision unit 120 may determine a number of revisions 122 of the file to store based on the categorization of the file. The categorization may relate to an importance of the file.

[0016] Together, the rule and revision units 1 10 and 120 may be part of a backup system that takes care of managing the various revisions of a particular file, including dynamically assigning the rules that govern the number of revisions to retain for that file. The rule and revision units 1 10 and 120 are explained in greater detail below with respect to FIG. 2.

[0017] FIG. 2 is another example block diagram of a device 200 to determine a number of revisions of a file to store based on a category. The device 200 may be a microprocessor, a controller, a memory module or device, a notebook computer, a desktop computer, an all-in-one system, a server, a network device, a wireless device, or any other type of device capable of interacting with a storage device and/or intercepting a file along a network.

[0018] The device 200 is shown to interface with a set of files 230 and set of revisions 250. The files 230 and/or revision 250 may be stored, for example, in any electronic, magnetic, optical, or other physical storage device that contains or stores information, such as Random Access Memory (RAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a storage drive, a Compact Disc Read Only Memory (CD-ROM), and the like. While a first file 232 and a second file 234 are shown, examples may include more or less than two files. Similarly, while 3 revisions 232-1 to 232-3 are shown to be retained of the first file 232 and 2 revisions 234-1 and 234-2 are shown to be retained of the second file 234, examples may include more or less number of revisions of the first and second files 232 and 234. [0019] The device 200 of FIG. 2 may include at least the functionality and/or hardware of the device 100 of FIG. 1 . For example, a rule unit 210 of the device 200 of FIG. 2 may include at least the functionality and/or hardware of the rule unit 1 10 of the device 100 of FIG. 1 . The device 200 is also shown to include the revision unit 120.

[0020] Since a set of files to be backed up may consist of different kinds of files 230, the rules 212 governing the number of revisions 122 of a file to keep need not be the same but may instead be dynamically determined by the device 200. The rule unit 210 may include a plurality of rules 212 to categorize the plurality of files 230, based on characteristics of the files 230. The plurality of rules 212 may be used to determine scores 214 for the plurality of files 230. The plurality of rules 212 may classify the file 230 to one of a plurality of categories 216 based on the determined score 214.

[0021 ] Each of the plurality of categories 216 may correspond to a different range of the scores 214. Different categories 216 may correspond to different levels of importance. For example, there may categories 216 such as most important, more important, important, less important, least important, and the like. Each of these categories 216 may correspond to a different number of revisions to retain, such as from any number between one and infinity to one. The types of categories 216, as well as their corresponding number of revisions 122 to be stored, may be configured by an administrator. [0022] The revision unit 120 may determine a number of revisions 122 of the file to store based on the categorization of the file 230. The categorization may relate to an importance of the file. In one example, the revision unit 120 may store a greater number of the revisions for a first file 232 of the plurality of files 230 than a second file 234 of the plurality of files 230, if the rule unit 210 categorizes the first file 232 to have a greater importance than the second file 234. For instance, the first file 232 may be categorized as more important and the second file 234 may be categorized as important. Thus, for example, three revisions 232-1 to 232-3 may be stored for the first file 232 while only two revisions 234-1 and 234-2 may be stored for the second file 234.

[0023] The plurality of rules 212 may determine the scores 214 based on, for example, a number of times the file 230 is modified ("modify rule"), a number of times a relevant keyword is included in the file 230 ("keyword rule"), a number of times the file 230 is downloaded ("download rule"), a number of times the file 230 is shared ("share rule") and the like. For example, a higher score 213 may be attributed to a file 230 that is modified more often by a user or includes more relevant keywords that are relevant to the user or by an administrator based upon specific business needs. A higher score 213 may also be attributed to a file 230 that is downloaded or shared more often by the user. Thus, the score 213 may be proportional to a frequency of the characteristic measured by the corresponding rule 212.

[0024] Each of the plurality of rules 212 may determine a separate score 214 for each of the plurality of files 230. Further, each of the scores 214 may correspond to one of the plurality of categories 216. For example, the each of the above four rules 212 may provide a score 214 for each of the files, such as the first and second files 232 and 234. The rule unit 210 may categorize the first file 232 to a category 216 of greater importance than a category 216 of the second file 234, if a first rule of the plurality of rules 212 determines a score 214 of the first file 232 to be within a higher range than a score 214 of the second file 234.

[0025] For instance, the modify rule 212 may provide a score of 18 for the first file 232 and a score of 9 for the second file 234. The score range of 0-10 may correspond to the least important category for the modify rule 212 and score range of 1 1 -20 may correspond to the less important category for the modify rule 212. Thus, the modify rule 212 may categorize the first file 232 as less important and the second file 234 as least important. However, different score ranges may correspond to different categories 216 for different rules 212. For instance, the score range of 0-50 may correspond to the least important category for the share rule 212.

[0026] The revision unit 120 may determine the number of revisions 122 to store of the first file 232 based on at least one of the plurality of categories 216 determined by the plurality of rules 212 for the first file 232. For example, the modify rule 212 may categorize the first file 232 as less important, the keyword rule 212 may categorize the first file 232 as most important, the download rule 212 may categorize the first file 232 as important and the share rule 212 may categorize the first file 232 as less important. Thus, the number of revisions 122 to store of the first file 232 may be based on a combination of any of these four categorizations.

[0027] The number of revisions 122 to store of the first file 232 may be based on a final category 218. The final category 218 may be determined based on the plurality of determined categories 216. In one example, the final category 218 of the first file 232 may be simply determined by averaging the four categories 216 determined by the four rules 212 for the first file 232. However, all the rules 212 may not have equal importance to a user or administrator. In another example, the final category 218 may be based on a weighted average of the determined categories 216. The weight of each of the determined categories may be based on the corresponding rule 212. For instance, the modify rule 212 may have a weight of "2" while the share rule 212 may only have a weight of "0.5".

[0028] In yet another example, the final category 218 may be based on a combination table (not shown). The combination table may indicate the final category 218 for each combination of categories 216 of the plurality of rules 212. Assuming there are only two rules (such as the modify rule 212 and the keyword rule 212) and two possible categories (Important and Not important) for the sake of simplicity an example combination table may be as follows:

[0029] Here, the final category 218 is shown to be "important" any time either of the Keyword rule 212 and the Modify Rule 212 categorize 216 the file 230 as important. However, examples may include various other types of combination tables with various other types of values for the final category 218. Thus, examples may provide a backup solution that dynamically determines how many revisions of a file need to be retained. Examples may do so by ranking the files based upon their level of importance to the user and then grouping them into various categories.

[0030] FIG. 3 is an example block diagram of a computing device 300 including instructions for determining a number of revisions of a file to store based on a category. In the embodiment of FIG. 3, the computing device 300 includes a processor 310 and a machine-readable storage medium 320. The machine- readable storage medium 320 further includes instructions 322, 324 and 326 for determining a number of revisions of a file to store based on a category.

[0031 ] The computing device 300 may be included in or part of, for example, a microprocessor, a controller, a memory module or device, a notebook computer, a desktop computer, an all-in-one system, a server, a network device, a wireless device, or any other type of device capable of executing the instructions 322, 324 and 326. In certain examples, the computing device 300 may include or be connected to additional components such as memories, controllers, etc.

[0032] The processor 310 may be, at least one central processing unit (CPU), at least one semiconductor-based microprocessor, at least one graphics processing unit (GPU), a microcontroller, special purpose logic hardware controlled by microcode or other hardware devices suitable for retrieval and execution of instructions stored in the machine-readable storage medium 320, or combinations thereof. The processor 310 may fetch, decode, and execute instructions 322, 324 and 326 to implement determining the number of revisions of the file to store based on the category. As an alternative or in addition to retrieving and executing instructions, the processor 310 may include at least one integrated circuit (IC), other control logic, other electronic circuits, or combinations thereof that include a number of electronic components for performing the functionality of instructions 322, 324 and 326.

[0033] The machine-readable storage medium 320 may be any electronic, magnetic, optical, or other physical storage device that contains or stores executable instructions. Thus, the machine-readable storage medium 320 may be, for example, Random Access Memory (RAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a storage drive, a Compact Disc Read Only Memory (CD-ROM), and the like. As such, the machine-readable storage medium 320 can be non-transitory. As described in detail below, machine- readable storage medium 320 may be encoded with a series of executable instructions for determining the number of revisions of the file to store based on the category.

[0034] Moreover, the instructions 322, 324 and 326, when executed by a processor (e.g., via one processing element or multiple processing elements of the processor) can cause the processor to perform processes, such as, the process of FIG. 4. For example, the determine instructions 322 may be executed by the processor 310 to determine a plurality of categories for a file based on a plurality of rules. Each of the rules may measure a different characteristic of the file. Further, each of the rules may determine a separate one of the plurality of categories.

[0035] The assign instructions 324 may be executed by the processor 310 to assign a final category for the file based on the plurality of categories. The calculate instructions 326 may be executed by the processor 310 to calculate a number of revisions of the file to store based on the final category. The stored revisions may relate to a backup system. The file may include a document, image, audio, video, source code, compressed file, disk volume image (such as a disc or virtual machine image), software and the like. Thus, examples may dynamically determine the number of revisions of a file to retain based upon the importance of the document to the user according to certain classification criterion.

[0036] FIG. 4 is an example flowchart of a method 400 for determining a number of revisions of a file to store based on a category. Although execution of the method 400 is described below with reference to the device 200, other suitable components for execution of the method 400 can be utilized, such as the device 100. Additionally, the components for executing the method 400 may be spread among multiple devices (e.g., a processing device in communication with input and output devices). In certain scenarios, multiple devices acting in coordination can be considered a single device to perform the method 400. The method 400 may be implemented in the form of executable instructions stored on a machine-readable storage medium, such as storage medium 320, and/or in the form of electronic circuitry.

[0037] At block 410, the device 200 selects one of a plurality of categories 216 for a file 230 according to a first rule 212. At block 420, the device 200 selects one of the plurality of categories 216 for the file 230 according to a second rule 212. The plurality of categories 216 may relate to different levels of importance. The first and second rules 212 may measure different characteristics of the file 230. [0038] At block 430, the device 200 calculates a final category 218 for the file 230 based on the selected categories 216 of the first and second rules 212. At block 440, the device 200 deternnines a number of revisions 122 to store for the file 230 based on the final category 218. A user and/or an administrator may determine the categories 216, the rules 212 and/or a function for calculating the final category 218. Thus, examples may dynamically determine the number of revisions of a file to be retained based on characteristics of the file determined by the rules.

Claims

CLAIMS We claim:

1 . A device, comprising:

a rule unit to include a rule to categorize a file based on characteristics of the file; and

a revision unit to determine a number of revisions of the file to store based on the categorization of the file, wherein

the categorization relates to an importance of the file.

2. The device of claim 1 , wherein,

the rule unit is to categorize a plurality of files, and

the revision unit is to store a greater number of the revisions for a first file of the plurality of files than a second file of the plurality of files, if the rule unit categorizes the first file to have a greater importance than the second file.

3. The device of claim 2, wherein,

the rule unit is to include a plurality of rules to categorize the plurality of files, and

the plurality of rules are used to determine scores for the plurality of files.

4. The device of claim 3, wherein,

the plurality of rules are to classify the file to one of a plurality of categories based on the determined score,

each of the plurality of categories is to correspond to a different range of the scores, and

different categories are to correspond to different levels of importance.

5. The device of claim 4, wherein the plurality of rules are to determine the scores based on a number of times at least one of the file is modified, a relevant keyword is included in the file, the file is downloaded and the file is shared.

6. The device of claim 5, wherein,

each of the plurality of rules are to determine a separate score for each of the plurality of files, and

each of the scores corresponds to one of the plurality of categories.

7. The device of claim 6, wherein the rule unit is to categorize the first file to a category of greater importance than a category of the second file, if a first rule of the plurality of rules determines a score of the first file to be within a higher range than a score of the second file.

8. The device of claim 7, wherein the revision unit is to determine the number of revisions to store of the first file based on at least one of the plurality of categories determined by the plurality of rules for the first file.

9. The device of claim 8, wherein,

the number of revisions to store of the first file is based on a final category, and

the final category is determined based on the plurality of determined categories

10. The device of claim 9, wherein,

the final category is based on a weighted average of the determined categories, and

the weight of each of the determined categories is based on the corresponding rule.

1 1 . The device of claim 9, wherein the final category is based on a combination table, the combination table to indicate the final category for each combination of categories of the plurality of rules.

12. A method, comprising:

selecting one of a plurality of categories for a file according to a first rule; selecting one of the plurality of categories for the file according to a second rule;

calculating a final category for the file based on the selected categories of the first and second rules; and

determining a number of revisions to store for the file based on the final category, wherein

the first and second rules measure different characteristics of the file

13. The method of claim 12, wherein,

the plurality of categories relate to different levels of importance, and at least one of a user and an administrator are to determine at least one of the categories, the rules and a function for calculating the final category.

14. A non-transitory computer-readable storage medium storing instructions that, if executed by a processor of a device, cause the processor to: determine a plurality of categories for a file based on a plurality of rules; assign a final category for the file based on the plurality of categories; and calculate a number of revisions of the file to store based on the final category, wherein

each of the rules is to measure a different characteristic of the file, and each of the rules is to determine a separate one of the plurality of categories.

15. The non-transitory computer-readable storage medium of claim 14, wherein,

the stored revisions relate to a backup system, and

the file includes at least one of a document, image, audio, video, source code, compressed file, disk volume image and software.