CN110222043A - Data monitoring method, device and the equipment of cloud storage service device - Google Patents
Data monitoring method, device and the equipment of cloud storage service device Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
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Abstract
This application discloses data monitoring method, device, equipment and the computer readable storage mediums of a kind of cloud storage service device, can obtain the customer attribute information of data to be uploaded；It determines the similarity between the customer attribute information of data to be uploaded and the customer attribute information of the copy data of data to be uploaded, obtains similarity set；It determines in similarity set more than the total quantity of the similarity of similarity threshold；Finally when determining that total quantity is more than amount threshold, it is updated according to popularity numerical value of the growth curve function model to data to be uploaded, and store data to be uploaded.It can be seen that, the program is when user uploads data, the user property can be calculated and uploaded the similitude between the attribute of the user of the data, according to the update mode of similitude determination data popularity numerical value, this mode that data stream degree value is adaptively adjusted based on user property, the single bring leaking data problem of popularity numerical value adjustment mode is avoided, the safety of data is improved.
Description
Technical field
This application involves data deduplication field, in particular to a kind of data monitoring method of cloud storage service device, is set device
Standby and computer readable storage medium.
Background technique
Data deduplication technology is a kind of reduction skill that can be identified and eliminate redundant data, only store single copy data
Art is widely used in cloud storage field.
Cloud storage service device is responsible for storing the data that a large number of users uploads, when cloud storage service device executes data deduplication,
Shared data encryption key or parameter among different users are needed, guarantees user data peace while to improve storage efficiency
Entirely, cloud storage service generallys use the De-weight method for dividing popularity, that is, defines a popularity threshold value, when a certain data of upload
Number of users up to or over given threshold, then the data are considered as prevalence data, are otherwise non-prevalence data.Server
Right pop data carry out deduplication operation, to improve the safety of non-prevalence data.
It is main currently based on the De-weight method of popularity are as follows: cloud storage service device is the given threshold of data distributing uniform,
Whenever having a user to upload certain data, server is that the popularity numerical value of the data adds 1.When the copy amount of data reaches
Or be more than given threshold, then the data are considered as prevalence data, are otherwise non-prevalence data.
The defect of this method is: in practical application scene, the uploader of certain data from the same group, such as
Company will lead to popularity numerical value of these data on cloud storage service device and reach quickly if the said firm's headcount is more
To even more than given threshold.And in fact these data are not real " prevalence ", that is to say, that these data are not by net
Many independent users on network are possessed, these data are only possessed by the said firm.Since data deduplication is needed in different use
The data sharing encryption key or parameter at family, thus deduplication operation may result in internal data leakage or encryption key and
Parameter to external leakage.In this case, if gone using traditional popularity numerical value update method to such data
The problems such as handling again, may cause internal data leakage.
As it can be seen that the popularity computation mode of traditional data duplicate removal method based on popularity is single, data is caused to exist
The possibility of leakage, safety are lower.
Summary of the invention
Data monitoring method, device, equipment and the computer that the purpose of the application is to provide a kind of cloud storage service device can
Storage medium is read, the popularity numerical value update mode to solve traditional data duplicate removal method based on popularity is single, leads
The problem for causing Information Security lower.Concrete scheme is as follows:
In a first aspect, this application provides a kind of data monitoring methods of cloud storage service device, comprising:
Obtain the customer attribute information of data to be uploaded；
Determine the user property of the customer attribute information of the data to be uploaded and the copy data of the data to be uploaded
Similarity between information obtains similarity set；
It determines in the similarity set more than the total quantity of the similarity of similarity threshold；
When the total quantity is more than amount threshold, according to growth curve function model to the prevalence of the data to be uploaded
Degree value is updated, and stores the data to be uploaded.
Optionally, described when the total quantity is more than amount threshold, according to growth curve function model to described to upper
The popularity numerical value for passing data is updated, comprising:
When the total quantity is more than amount threshold, determine that the upload user of the data to be uploaded is group user, and
It is updated according to popularity numerical value of the growth curve function model to the data to be uploaded；
When the total quantity is less than the amount threshold, determine that the upload user of the data to be uploaded is used to be personal
Family, and the popularity numerical value of the data to be uploaded is added one.
Optionally, the copy data of the customer attribute information of the determination data to be uploaded and the data to be uploaded
Customer attribute information between similarity, comprising:
Corresponding similarity calculation mode is arranged in the customer attribute information of respectively different information types；
During calculating similarity, target similarity calculation is determined according to the information type of active user's attribute information
Mode, and according to the target similarity calculation mode, determine active user's attribute informations of the data to be uploaded with it is described
The similarity of the copy data of data to be uploaded worked as between customer attribute information.
Optionally, the information type includes following any one or more: determining numeric type, determines character type, determination
Interval type, fuzzy interval type, Fuzzy Number Valued type, fuzzy semantics type.
Second aspect, present invention also provides a kind of data monitoring devices of cloud storage service device, comprising:
Attribute information obtains module: for obtaining the customer attribute information of data to be uploaded；
Similarity determining module: for determine the data to be uploaded customer attribute information and the data to be uploaded
Similarity between the customer attribute information of copy data obtains similarity set；
Quantity determining module: for determining in the similarity set more than the total quantity of the similarity of similarity threshold；
Update module: for the total quantity be more than amount threshold when, according to growth curve function model to it is described to
The popularity numerical value for uploading data is updated, and stores the data to be uploaded.
Optionally, the update module includes:
Group user updating unit: for determining the data to be uploaded when the total quantity is more than amount threshold
Upload user is group user, and is carried out more according to popularity numerical value of the growth curve function model to the data to be uploaded
Newly；
Personal user's updating unit: for determining described to be uploaded when the total quantity is less than the amount threshold
The upload user of data is personal user, and the popularity numerical value of the data to be uploaded is added one.
Optionally, the similarity determining module includes:
Type setting unit: corresponding similarity calculation is arranged in the customer attribute information for being respectively different information types
Mode；
Similarity calculated: it is used for during calculating similarity, according to the info class of active user's attribute information
Type determines target similarity calculation mode, and according to the target similarity calculation mode, determines working as the data to be uploaded
The similarity of preceding customer attribute information and the copy data of the data to be uploaded worked as between customer attribute information.
The third aspect, present invention also provides a kind of data monitoring devices of cloud storage service device, comprising:
Memory: for storing computer program；
Processor: for executing the computer program, to realize a kind of data of cloud storage service device as described above
The step of monitoring method.
Fourth aspect, this application provides a kind of computer readable storage medium, on the computer readable storage medium
It is stored with computer program, for realizing a kind of cloud storage service as described above when the computer program is executed by processor
The step of data monitoring method of device.
It the data monitoring method of cloud storage service device provided herein a kind of, device, equipment and computer-readable deposits
Storage media can obtain the customer attribute information of data to be uploaded；Determine the customer attribute informations of data to be uploaded with it is to be uploaded
Similarity between the customer attribute information of the copy data of data obtains similarity set；Then it determines in similarity set
More than the total quantity of the similarity of similarity threshold；Finally when determining that total quantity is more than amount threshold, according to growth curve letter
Exponential model is updated the popularity numerical value of data to be uploaded, and stores data to be uploaded.As it can be seen that the program is uploaded in user
When data, the attribute of the user can be calculated and uploaded the similitude between the attribute of the user of the data, and then according to similar
The update mode of property determination data popularity numerical value, this side that data stream degree value is adaptively adjusted based on user property
Formula avoids the single bring leaking data problem of popularity numerical value adjustment mode, has been obviously improved the safety of data.
Detailed description of the invention
It, below will be to embodiment or existing for the clearer technical solution for illustrating the embodiment of the present application or the prior art
Attached drawing needed in technical description is briefly described, it should be apparent that, the accompanying drawings in the following description is only this Shen
Some embodiments please for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is a kind of implementation process of the data monitoring method embodiment one of cloud storage service device provided herein
Figure；
Fig. 2 is a kind of implementation process of the data monitoring method embodiment two of cloud storage service device provided herein
Figure；
Fig. 3 is a kind of functional block diagram of the data monitoring Installation practice of cloud storage service device provided herein；
Fig. 4 is a kind of structural schematic diagram of the data monitoring device embodiment of cloud storage service device provided herein.
Specific embodiment
In order to make those skilled in the art more fully understand application scheme, with reference to the accompanying drawings and detailed description
The application is described in further detail.Obviously, described embodiments are only a part of embodiments of the present application, rather than
Whole embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not making creative work premise
Under every other embodiment obtained, shall fall in the protection scope of this application.
Currently, the popularity numerical value adjustment mode of the data deduplication scheme based on popularity are as follows: whenever having on a user
When passing data, the popularity numerical value of the data adds 1.The adjustment mode of this popularity numerical value is excessively single, is easy to cause data
Leakage, reduces the safety of data.For this problem, this application provides a kind of data monitoring sides of cloud storage service device
Method, device, equipment and computer readable storage medium are realized and are adaptively adjusted data stream degree value based on user property
Purpose has been obviously improved the safety of data.
A kind of data monitoring method embodiment one of cloud storage service device provided by the present application is introduced below, referring to
Fig. 1, embodiment one include:
Step S101: the customer attribute information of data to be uploaded is obtained；
In the present embodiment, customer attribute information refers to the reference information for measuring correlation degree between user, the user
Attribute information may include a variety of attribute informations, can specifically include the information such as lan address, age, gender, personal preference,
The present embodiment does not limit which kind of information specifically chosen.The present embodiment is according to copy data in active user and cloud storage service device
Upload user between correlation degree, determine to adjust the popularity numerical value of the data in which way.As a kind of specific
Active user is divided into two classes, respectively personal user and group user according to above-mentioned correlation degree by embodiment, the present embodiment,
When determining active user is personal user, according to traditional popularity numerical value adjustment mode to the popularity numerical value of the data into
Row adjustment, i.e. popularity numerical value add 1；When determining active user is group user, then according to popularity provided in this embodiment
Numerical value adjustment mode is adjusted the popularity numerical value of the data.
Specifically, before the customer attribute information for obtaining data to be uploaded, it can be determined that data to be uploaded whether headed by
The data of secondary upload can be directly according to traditional popularity numerical value after determining that data to be uploaded are the data uploaded for the first time
Adjustment mode determines the popularity numerical value of the data, i.e. popularity numerical value is 1；Determining that data to be uploaded are non-to upload for the first time
Data after, then execute the operation of the present embodiment.
Step S102: the customer attribute information of the data to be uploaded and the copy data of the data to be uploaded are determined
Similarity between customer attribute information obtains similarity set；
When being stored with the multiple copies data of data to be uploaded in cloud storage service device, current embodiment require that determining respectively
Similarity between the customer attribute information of data to be uploaded and the attribute information of each copy data obtains similarity set,
It include the similarity between active user and the upload user of each copy data in similarity set.
As described above, customer attribute information may include a variety of attribute informations in the present embodiment, in practical application scene,
If customer attribute information includes a variety of attribute informations, then, in the customer attribute information and copy data for determining data to be uploaded
Customer attribute information between similarity when, the distance between each attribute information can be sought respectively, and then according to each
The distance between a attribute information determines whole similarity.As a preferred embodiment, can be respectively each use
Weighted value is arranged in family attribute, when determining whole similarity, the distance of comprehensive each attribute information and corresponding power
Weight values determine whole similarity.
Step S103: it determines in the similarity set more than the total quantity of the similarity of similarity threshold；
Step S104: when the total quantity is more than amount threshold, according to growth curve function model to described to be uploaded
The popularity numerical value of data is updated, and stores the data to be uploaded.
As described above, pre-set two threshold values are utilized in the present embodiment when judging user type, respectively
Similarity threshold and amount threshold, specifically, be first more than the total quantity of the similarity of similarity threshold in determining similarity set,
Judge whether total quantity is more than amount threshold again, if being more than, determines that active user for group user, and mentions according to the present embodiment
The similarity adjustment mode of confession is adjusted the similarity of the data.As a kind of specific embodiment, in active user
When being judged as group user, the present embodiment is adjusted according to popularity numerical value of the growth curve function model to data to be uploaded
It is whole, wherein growth curve function model refers mainly to the Pearl model of growth curve function.
It is noted that the present embodiment also uses pre-set popularity threshold value in addition to above-mentioned two threshold value, stream
Row degree threshold value executes data deduplication operation for judging whether.The model parameter of growth curve function model includes the popularity threshold
Value, therefore, according to growth curve function model rule it is found that according to growth curve function model adjustment popularity numerical value it
Afterwards, popularity numerical value does not exceed preset popularity threshold value, therefore will not trigger data deduplication operation.
The present embodiment provides a kind of data monitoring method of cloud storage service device, can obtain the user of data to be uploaded
Attribute information；It determines between the customer attribute information of data to be uploaded and the customer attribute information of the copy data of data to be uploaded
Similarity, obtain similarity set；Then it determines in similarity set more than the total quantity of the similarity of similarity threshold；Most
Eventually when total quantity is more than amount threshold, carried out more according to popularity numerical value of the growth curve function model to data to be uploaded
Newly, and data to be uploaded are stored.As it can be seen that the program when user uploads data, can calculate the attribute of the user and upload this
Similitude between the attribute of the user of data, and then according to the update mode of similitude determination data popularity numerical value, it is this
The mode that data stream degree value is adaptively adjusted based on user property avoids the single bring of popularity numerical value adjustment mode
Leaking data problem has been obviously improved the safety of data.
Start that a kind of data monitoring method embodiment two of cloud storage service device provided by the present application is discussed in detail below, it is real
It applies example two one to realize based on the above embodiment, and has carried out expansion to a certain extent on the basis of example 1.Specifically,
Embodiment two divides the type of attribute information, and gives specific attributive distance calculating side to each type attribute
Method.
Referring to fig. 2, embodiment two specifically includes:
Step S201: initialization system parameter；
The present embodiment realizes that cloud storage service device is mainly handed over the client of active user based on cloud storage service device
Mutually.In practical application scene, active user A0Ciphertext F and inquiry tag H is generated, wherein ciphertext F, that is, above-mentioned data to be uploaded,
And the upload request including the two is sent to cloud storage service device, then cloud storage service device is judged by inquiry tag to upper
It passes whether data are the data uploaded for the first time, and when determining data to be uploaded is the non-data uploaded for the first time, executes this implementation
Example subsequent step.
Above-mentioned initialization procedure includes:
(1) popularity threshold value T is set；
(2) it defines data stream degree: indicating that the comprehensive of data F to be uploaded counts with count (F), as count (F) < T
When, definition F is non-prevalence data；Otherwise, defining F is prevalence data；
(3) bilinear map label generating function e (Y, Hash (F)) is definedX, the function export F corresponding to label H,
As the unique identification of data F to be uploaded, wherein Y is encrypted public key, and X is auxiliary key, and Hash (F) is the cryptographic Hash of data；
(4) size of similarity threshold f, amount threshold z are set, wherein f value range is (0,1), and z is fixed integer；
(5) content of customer attribute information, including a variety of attribute informations are defined, and the type for defining these attribute informations is
It [determines numeric type with one in Types Below, determines character type, determination section type, fuzzy interval or fuzzy number type, fuzzy semantics
Type].
Step S202: the customer attribute information of data to be uploaded is obtained；
Above-mentioned customer attribute information specifically includes a variety of attribute informations, and the information type of attribute information can be aforementioned information
Any one in type, the similarity in the present embodiment between customer attribute information be the similarity of each attribute information plus
Result after power summation.
Step S203: determining target range calculation according to the information type of current attribute information, and according to target away from
From calculation, determine the current attribute information of data to be uploaded and the copy data of data to be uploaded when between attribute information
Distance；
As described above, the present embodiment is in advance classified the type of attribute information, and on this basis, the present embodiment point
Not Wei different information types attribute information be provided with accordingly apart from calculation.The attribute of different information types is believed below
Breath is introduced apart from calculation:
The attribute information indicated for determining numerical value, such as two determining attribute value x1With x2, formula d can be directlyed adoptDN
(x1,x2)=| x1-x2| calculate its distance；
For the attribute information indicated with determining symbol, if the upload of the attribute information of active user and certain copy data
The attribute information of user is identical, then assert that its distance is 0, and otherwise, distance is infinity；
The attribute information indicated for determination section, it is assumed that the attribute value X of two determination sections1With X2, the present embodiment use
Its distance is calculated based on the EW type range formula of width, the formula specifically:
WhereinFor the desired value of section X,For the width of section X, x(L)For area
Between starting point, x(H)For section terminating point；
For fuzzy number or the fuzzy interval of specific value can not be quantified as after attribute number value, it is located in advance first
It manages, fuzzy number or fuzzy interval are indicated with F in the present embodiment, and the α grade section X (α) that pretreatment obtains it is indicated.Then it uses
Following formula carry out attributive distance to it and calculate:
Wherein,
It for the weighting function being defined on [0,1], and is a positive value continuous function；
For fuzzy semantics indicate attribute information, can be calculated by subordinating degree function between the attribute information away from
From.
Step S204: according to the distance between each attribute information, the similar of the entirety between customer attribute information is determined
Degree；
Preceding step has obtained the distance between each attribute information, remembers active user A0With the upload of cloud copy data
User AiThe distance of (subscript i is known i-th of user, 0 < i≤M) on j-th of attribute is dij(1≤j≤m), then A0
Constitute distance matrix C with the attributive distance of the user for possessing identical data known on cloud storage service device, to each in C arrange into
Row normalized obtains canonical matrix R, and process is as follows:
Wherein, di'jFor the numerical value obtained after normalized.
The present embodiment is respectively m attribute information distribution weighted value, and allocation result is denoted as: W={ w1,w2,...,
wm}.Wherein, 0≤wj≤ 1, andPass through formula RWT=(D1,D2,...,DM) obtain active user A0With copy data
Upload user between weighting overall distance Di, wherein WTFor the transposition of weight vectors W, it is final determine customer attribute information it
Between similarity Si, that is to say, that A0With user AiBetween similarity be Si=1-Di。
Step S205: according to the similarity of active user and the customer attribute information of the upload user of each copy data,
Obtain similarity set；
Step S206: it determines in the similarity set more than the total quantity of the similarity of similarity threshold, judges sum
Whether amount is more than that amount threshold enters step S207, otherwise enter step S208 if being more than；
Step S207: determine that active user is group user, and according to growth curve function model to the number to be uploaded
According to popularity numerical value be updated, store the data to be uploaded；
Step S208: it determines that active user is personal user, and the popularity numerical value of the data to be uploaded is added one；
As described above, the present embodiment determines the adjustment mode of popularity numerical value, user type according to the type of active user
Including personal user and group user, the popularity state of data can only change because of the addition of personal user, and then preferably
Guarantee the safety of group internal data.Specifically, working as A0When for personal user, popularity numerical value update mode is as follows:
Count (F)=count (F)+1
Work as A0When for group user, then need to count using dynamic adjustment, mode is as follows:
Wherein a, b are constant.
Step S209: when popularity numerical value in the updated is greater than popularity threshold value, data deduplication behaviour is executed to the data
Make, otherwise stores the data to be uploaded.
In the present embodiment, after active user requests to upload data, if it is determined that the popularity numerical value of the data is more than prevalence
Threshold value is spent, then executes data deduplication operation, guarantees that each copy data only stores portion, cloud storage service in cloud storage service device
Device is the user's creation access link for possessing this data, to achieve the purpose that save network bandwidth and memory space.
To sum up, a kind of data monitoring method of cloud storage service device is present embodiments provided, it is real based on cloud storage service device
Existing, main process includes: the upload request for receiving active user and sending, and upload request includes the data to be uploaded of encryption；It obtains
The customer attribute information of active user；Will it is known in active user and cloud storage service device on be transmitted through all users of the data into
Row attributes similarity calculates；Judge that the user type of active user, user type specifically include a according to similarity calculation result
People user and group user；According to user type, the update mode according to corresponding popularity numerical value is to the popularities of the data
Numerical value is updated；It stores the data or executes data deduplication operation.
As it can be seen that this method is determined between active user and the upload user of each copy data by customer attribute information
Similarity, and then user type is determined according to similarity, and accordingly to the popularity numeric counter mode of data to be uploaded into
The adaptive adjustment of row.This method identifies possible group user according to the similarity degree of user property, ensures group user always
Upload operation will not change the current popularity numeric state of data (i.e. from non-prevalence become popular), ensure that data deduplication
The safety of data and relevant ciphering parameters in system, reduce group internal data close to popularity threshold value speed, effectively
The internal data leakage problem that data may cause is solved, the safety of user data is preferably protected.
A kind of data monitoring device of cloud storage service device provided by the embodiments of the present application is introduced below, is hereafter retouched
A kind of data monitoring device for the cloud storage service device stated and a kind of above-described data monitoring method of cloud storage service device
Reference can be corresponded to each other.
As shown in figure 3, the device includes:
Attribute information obtains module 301: for obtaining the customer attribute information of data to be uploaded；
Similarity determining module 302: for determining the customer attribute information and the number to be uploaded of the data to be uploaded
According to copy data customer attribute information between similarity, obtain similarity set；
Quantity determining module 303: for determining in the similarity set more than the sum of the similarity of similarity threshold
Amount；
Update module 304: it is used for when the total quantity is more than amount threshold, according to growth curve function model to described
The popularity numerical value of data to be uploaded is updated, and stores the data to be uploaded.
As a kind of specific embodiment, the update module 304 includes:
Group user updating unit: for determining the data to be uploaded when the total quantity is more than amount threshold
Upload user is group user, and is carried out more according to popularity numerical value of the growth curve function model to the data to be uploaded
Newly；
Personal user's updating unit: for determining described to be uploaded when the total quantity is less than the amount threshold
The upload user of data is personal user, and the popularity numerical value of the data to be uploaded is added one.
As a kind of specific embodiment, the similarity determining module 302 includes:
Type setting unit: corresponding similarity calculation is arranged in the customer attribute information for being respectively different information types
Mode；
Similarity calculated: it is used for during calculating similarity, according to the info class of active user's attribute information
Type determines target similarity calculation mode, and according to the target similarity calculation mode, determines working as the data to be uploaded
The similarity of preceding customer attribute information and the copy data of the data to be uploaded worked as between customer attribute information.
The data monitoring device of the cloud storage service device of the present embodiment for realizing cloud storage service device above-mentioned data
Monitoring method, therefore the reality of the data monitoring method of the visible cloud storage service device hereinbefore of specific embodiment in the device
A part is applied, for example, attribute information obtains module 301, similarity determining module 302, quantity determining module 303, update module
304, it is respectively used to step S101, S102, S103, S104 in the data monitoring method for realizing above-mentioned cloud storage service device.So
Its specific embodiment is referred to the description of corresponding various pieces embodiment, herein not reinflated introduction.
In addition, due to the present embodiment cloud storage service device data monitoring device for realizing cloud storage service above-mentioned
The data monitoring method of device, therefore its effect is corresponding with the effect of the above method, which is not described herein again.
In addition, present invention also provides a kind of data monitoring devices of cloud storage service device, as shown in Figure 4, comprising:
Memory 401: for storing computer program；
Processor 402: for executing the computer program, to realize a kind of number of cloud storage service device as described above
The step of according to monitoring method.
Finally, being stored on the computer readable storage medium this application provides a kind of computer readable storage medium
There is computer program, for realizing a kind of cloud storage service device as described above when the computer program is executed by processor
The step of data monitoring method.
The data monitoring device of the cloud storage service device of the present embodiment, computer readable storage medium are for realizing above-mentioned
The data monitoring method of cloud storage service device, therefore before the equipment, the specific embodiment of computer readable storage medium are visible
The embodiment part of the data monitoring method of cloud storage service device in text, and the work of the effect of the two and preceding method embodiment
With corresponding, which is not described herein again.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with it is other
The difference of embodiment, same or similar part may refer to each other between each embodiment.For being filled disclosed in embodiment
For setting, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is referring to method part
Explanation.
The step of method described in conjunction with the examples disclosed in this document or algorithm, can directly be held with hardware, processor
The combination of capable software module or the two is implemented.Software module can be placed in random access memory (RAM), memory, read-only deposit
Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology
In any other form of storage medium well known in field.
Scheme provided herein is described in detail above, specific case used herein is to the application's
Principle and embodiment is expounded, the present processes that the above embodiments are only used to help understand and its core
Thought；At the same time, for those skilled in the art, according to the thought of the application, in specific embodiment and application range
Upper there will be changes, in conclusion the contents of this specification should not be construed as limiting the present application.
Claims (9)
1. a kind of data monitoring method of cloud storage service device characterized by comprising
Obtain the customer attribute information of data to be uploaded；
Determine the customer attribute information of the customer attribute information of the data to be uploaded and the copy data of the data to be uploaded
Between similarity, obtain similarity set；
It determines in the similarity set more than the total quantity of the similarity of similarity threshold；
When the total quantity is more than amount threshold, according to growth curve function model to the popular degree of the data to be uploaded
Value is updated, and stores the data to be uploaded.
2. the method as described in claim 1, which is characterized in that it is described when the total quantity is more than amount threshold, according to life
Long curvilinear function model is updated the popularity numerical value of the data to be uploaded, comprising:
When the total quantity is more than amount threshold, determine that the upload user of the data to be uploaded is group user, and according to
Growth curve function model is updated the popularity numerical value of the data to be uploaded；
When the total quantity is less than the amount threshold, determine that the upload user of the data to be uploaded is personal user,
And the popularity numerical value of the data to be uploaded is added one.
3. method according to claim 1 or 2, which is characterized in that the user property of the determination data to be uploaded is believed
Similarity between breath and the customer attribute information of the copy data of the data to be uploaded, comprising:
Corresponding similarity calculation mode is arranged in the customer attribute information of respectively different information types；
During calculating similarity, target similarity calculation side is determined according to the information type of active user's attribute information
Formula, and according to the target similarity calculation mode, determine the data to be uploaded active user's attribute information and it is described to
Upload the similarity of the copy data of data worked as between customer attribute information.
4. method as claimed in claim 3, which is characterized in that the information type includes following any one or more: really
Determine numeric type, determine character type, determination section type, fuzzy interval type, Fuzzy Number Valued type, fuzzy semantics type.
5. a kind of data monitoring device of cloud storage service device characterized by comprising
Attribute information obtains module: for obtaining the customer attribute information of data to be uploaded；
Similarity determining module: for determining the customer attribute information of the data to be uploaded and the copy of the data to be uploaded
Similarity between the customer attribute information of data obtains similarity set；
Quantity determining module: for determining in the similarity set more than the total quantity of the similarity of similarity threshold；
Update module: it is used for when the total quantity is more than amount threshold, according to growth curve function model to described to be uploaded
The popularity numerical value of data is updated, and stores the data to be uploaded.
6. device as claimed in claim 5, which is characterized in that the update module includes:
Group user updating unit: for determining the upload of the data to be uploaded when the total quantity is more than amount threshold
User is group user, and is updated according to popularity numerical value of the growth curve function model to the data to be uploaded；
Personal user's updating unit: for determining the data to be uploaded when the total quantity is less than the amount threshold
Upload user be personal user, and the popularity numerical value of the data to be uploaded is added one.
7. device as claimed in claim 5, which is characterized in that the similarity determining module includes:
Type setting unit: corresponding similarity calculation side is arranged in the customer attribute information for being respectively different information types
Formula；
Similarity calculated: for during calculating similarity, the information type according to active user's attribute information to be true
Set the goal similarity calculation mode, and according to the target similarity calculation mode, determines the current use of the data to be uploaded
The similarity of family attribute information and the copy data of the data to be uploaded worked as between customer attribute information.
8. a kind of data monitoring device of cloud storage service device characterized by comprising
Memory: for storing computer program；
Processor: for executing the computer program, to realize a kind of cloud storage as described in claim 1-4 any one
The step of data monitoring method of server.
9. a kind of computer readable storage medium, which is characterized in that be stored with computer on the computer readable storage medium
Program is deposited when the computer program is executed by processor for realizing a kind of cloud as described in claim 1-4 any one
The step of storing up the data monitoring method of server.
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