CN109451017A - Dynamic cloud managing computing resources method under cloud environment based on Granular Computing - Google Patents
Dynamic cloud managing computing resources method under cloud environment based on Granular Computing Download PDFInfo
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- CN109451017A CN109451017A CN201811314632.XA CN201811314632A CN109451017A CN 109451017 A CN109451017 A CN 109451017A CN 201811314632 A CN201811314632 A CN 201811314632A CN 109451017 A CN109451017 A CN 109451017A
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- H—ELECTRICITY
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- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
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Abstract
The present invention discloses a kind of dynamic cloud managing computing resources method based on Granular Computing under cloud environment, includes the following steps: that S101. establishes intelligentized composite grain dynamic cloud resource tissue model；S102. the dynamic calculation model of the composite grain cloud user service request of scale is established；S103. the discovery of dynamic cloud Service Source and dispatching algorithm based on semantic computation are designed.Present invention introduces the characteristics of Granular Computing divided and rule to lower the complexity that user requests under dynamic cloud computing resources and cloud environment, introduce semantic computation thought, sufficiently extract the semanteme of cloud resource and cloud user request, design semantic-based resource discovering and dispatching algorithm, realize the efficient shared of cloud computing service resource, all have great importance and be worth in terms of theoretical research and practical application, it is applied in cloud computing service enterprise, application effect will improve about 30%, greatly cloud computing pushed to advance.
Description
Technical field
The present invention relates to the dynamic cloud computing resources based on Granular Computing under field of cloud calculation more particularly to a kind of cloud environment
Management method.
Background technique
A new service form of the cloud computing as information technology field, is counted as generation information technology application mould
The core of formula and technological change is increasingly subject to the concern of industry and various countries, has high application value.Ministry of Industry and Information's starting is directed to
Emphasis is cultivated leading enterprise by the planning of cloud computing, is played its radiation effects to industry development, is made cloud computing industrial chain.
As it can be seen that cloud computing is increasingly becoming the research hotspot of message area, to the research of cloud computing researching value with higher and pole
High application value.
Cloud computing service resource is the hard core control object of cloud computing system, and resource management is the core function of cloud computing system
Can, how to have managed cloud computing service resource is the key that the application of cloud computing system success.But current cloud computing money
The problem of source control is there is also in terms of following five:
(1) cloud resource manages the less variation for considering resource node ability, this must satisfy " adaptive with cloud computing system
Should in the relation between supply and demand of cloud resource dynamic change and can dynamic adjustresources management online " original intention run counter to.
(2) the generally existing flexibility of the tissue model of cloud computing resources and the poor phenomenon of scalability.The number of cloud resource
Mesh at geometric progression growth, and existing cloud resource tissue to resource extent be provided with the upper limit, lead to the urgency of cloud system performance
Play decline.
(3) cloud resource discovery method the problems such as that there are resource discovery efficiencies is low, poor reliability.Cloud resource has stronger wide
Domain distributivity, and the limitation of the unreliability of existing network and bandwidth etc., so that the search of resource is time-consuming and laborious, resource is fixed
The efficiency of position directly affects the performance of whole system.Further, since the diversity of cloud resource, frequently results in find and use with cloud
The resource that family mission requirements do not match that.
(4) scheduling of resource generally has the problems such as larger communication overhead, single point failure, lower task scheduling algorithm efficiency.
In addition, the diversity of cloud computing resources and complexity determine in cloud computing system and meet cloud user task need there may be multiple
The available cloud resource asked, and the cost that this cloud user task operates in performance obtained in different cloud resources and paid
It is all different.
(5) shortcoming Qos security mechanism is compared in resource management.User can find multiple satisfactory resources, it is necessary to adopt
With Qos come quality assurance.Current resource management is difficult to ensure that the response time of cloud task is reduced to some reasonable degree, only
The service done one's best can be provided to cloud user, compare and lack Qos pledge system.
Summary of the invention
It is an object of the invention to by a kind of dynamic cloud managing computing resources method under cloud environment based on Granular Computing,
To solve the problems, such as that background section above is mentioned.
To achieve this purpose, the present invention adopts the following technical scheme:
A kind of dynamic cloud managing computing resources method based on Granular Computing under cloud environment, this method comprises the following steps:
S101. intelligentized composite grain dynamic cloud resource tissue model is established；
S102. the dynamic calculation model of the composite grain cloud user service request of scale is established；
S103. the discovery of dynamic cloud Service Source and dispatching algorithm based on semantic computation are designed.
Particularly, the intelligentized composite grain dynamic cloud resource tissue model in the step S101 is based on rough set
The composite grain dynamic calculation model combined with Theory of Quotient Space.
Particularly, the step S101 is included: and establishes the composite grain combined based on rough set with Theory of Quotient Space to move
State computation model utilizes data own characteristic driving data for the DYNAMIC COMPLEX data structure object generated under cloud computing
Self-adaptive processing, i.e., intelligent automatic granulation, including automatically selecting basic element and division in message structure, formed granulosa it
Between with the structure inside granulosa.
Particularly, the step S101 include: based on Theory of Quotient Space building the different grain size world between it is mutual convert,
Depend on each other for existence relationship, constructs the expression of granularity based on rough set theory, portrays the dependence between granularity and concept；Pass through
Rough set model is embedded into Theory of Quotient Space model, the object between the different grain size world is indexed by granularity mapping mechanism
Relationship realizes the automatic granulation of DYNAMIC COMPLEX structure.
Particularly, the dynamic calculation model of the composite grain cloud user service request of the scale in the step S102 is
The composite grain computation model combined based on rough set, probability theory and Hypergraph Theory.
Particularly, the step S102 includes: the compound grain established and combined based on rough set, probability theory and Hypergraph Theory
Computation model is spent, for the user's request data generated under cloud environment, hierarchic parallel selection basic element and division is realized, realizes
Scale granulation between granulosa.
Particularly, the step S102 include: for rough set theory domain be object point set, in conjunction with cloud environment
The dynamic and magnanimity of lower data introduce probabilistic model and hypergraph model, according to probability in rough set Model of Granular Computing
Inference rule and hypergraph design feature realize the parallel granulation of complex data structures.
Particularly, the step S103 includes: using semantic computation theory, and using the ontology of semantic WEB, machine is located automatically
The information announced on cloud is managed and be incorporated into, extracts the semantic information of cloud resource and cloud user request respectively, and to the semantic information
Effectively stored.
Particularly, the step S103 further include: use semantic search engine, requested according to cloud user, utilize its semanteme
Information realizes the cloud resource discovery of semantic-based automation by the semantic information of semantic search engine Auto-matching cloud resource
With scheduling.
Dynamic cloud managing computing resources method advantage under cloud environment proposed by the present invention based on Granular Computing is as follows: one,
The features such as in view of the isomery of cloud resource, dynamic, complexity, introduces rough set and Theory of Quotient Space, establishes what two kinds of theories combined
Composite grain dynamic calculation model utilizes data own characteristic for the DYNAMIC COMPLEX data structure object generated under cloud computing
The self-adaptive processing of driving data, i.e., intelligent automatic granulation.Two, the diversity in view of cloud user request, dynamic, complexity
The features such as, rough set, probability theory and Hypergraph Theory are introduced, the composite grain computation model that these three theories combine, needle are established
To the mass users request data generated under cloud environment, realizes hierarchic parallel selection basic element and division, realize between granulosa
Scale granulation.Three, after carrying out granulation modeling to cloud resource and cloud user, for above two model, semantic meter is introduced
The basic thought of calculation, extracts the semantic information of cloud resource and cloud user request, and effectively stores them；Drawn using semantic search
It holds up, after cloud user requests to arrive, using its semantic information, by the semantic information of semantic search engine Auto-matching cloud resource,
To realize the cloud resource discovery and scheduling of semantic-based automation.Present invention introduces the characteristics of Granular Computing divided and rule
Lower the complexity that user under dynamic cloud computing resources and cloud environment requests, on this basis, introduce semantic computation thought,
The semanteme for sufficiently extracting cloud resource and cloud user request, designs semantic-based resource discovering and dispatching algorithm.The present invention realizes
Cloud computing service resource it is efficient shared, in terms of theoretical research and practical application all have great importance and be worth.This
Invent the dynamic cloud Resource Management Model proposed based on Granular Computing and semantic-based resource discovering and dispatching algorithm, application
Into cloud computing service enterprise, application effect will improve about 30%, greatly cloud computing pushed to advance.
Detailed description of the invention
Fig. 1 is the dynamic cloud managing computing resources method stream based on Granular Computing under cloud environment provided in an embodiment of the present invention
Cheng Tu.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples.It is understood that tool described herein
Body embodiment is used only for explaining the present invention rather than limiting the invention.It also should be noted that for the ease of retouching
It states, only some but not all contents related to the present invention are shown in the drawings, it is unless otherwise defined, used herein all
Technical and scientific term has the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.It is used herein
Term be intended merely to description specific embodiment, it is not intended that in limitation the present invention.
It please refers to shown in Fig. 1, Fig. 1 is the dynamic cloud computing based on Granular Computing under cloud environment provided in an embodiment of the present invention
Method for managing resource flow chart.
Dynamic cloud managing computing resources method in the present embodiment under cloud environment based on Granular Computing, this method include as follows
Step:
S101. intelligentized composite grain dynamic cloud resource tissue model is established.
Resource structures under cloud computing environment are relative complex, and highly dynamic variation, have resource to be dynamically added at any time.Cause
This, is reasonably effectively managed and is organized to it, and having to the efficiency of entire cloud computing system greatly improves.For cloud
The characteristic of resource, the intelligentized composite grain dynamic cloud resource tissue model described in the present embodiment are based on rough set and quotient
The composite grain dynamic calculation model that Space Theory combines, for solve dynamically to generate under cloud computing labyrinth object from
Kinetochore problem utilizes data own characteristic driving data for the DYNAMIC COMPLEX data structure object generated under cloud computing
Self-adaptive processing, i.e., intelligent automatic granulation, including automatically selecting basic element and division in message structure, formed granulosa it
Between with the structure inside granulosa, this resource tissue model occupied bandwidth is few, can be improved resource searching efficiency, for cloud computing provide
Feed Discovery has established good organization foundation, and it is effective to provide a kind of new tissue model and one kind for cloud computing resources management
Management method.
Mould is calculated for constructing the composite grain dynamic combined based on rough set with Theory of Quotient Space in the present embodiment
Type: firstly, based on Theory of Quotient Space building the different grain size world between mutually convert, depend on each other for existence relationship, be based on rough set
Theory constructs the expression of granularity, portrays the dependence between granularity and concept；Secondly, by the way that rough set model is embedded into
In Theory of Quotient Space model, the object relationship between the different grain size world is indexed by granularity mapping mechanism, realizes DYNAMIC COMPLEX
The automatic granulation of structure.
S102. the dynamic calculation model of the composite grain cloud user service request of scale is established.
Cloud user request under cloud computing environment is relatively complicated, and the composite grain cloud of scale in the present embodiment is used
The dynamic calculation model of family service request is that the composite grain combined based on rough set, probability theory and Hypergraph Theory calculates mould
Type requests cloud computing user using the model to carry out Classification Management, dynamically generates mass users complexity under solution cloud environment and ask
The parallel granulation problem asked, i.e., for the user's request data generated under cloud environment, realize hierarchic parallel selection basic element and
It divides, realizes the scale granulation between granulosa, accelerate the granulation progress of dynamic cloud computing user request, be cloud computing resource discovery
Good basis is established with scheduling.
It is in the present embodiment the point set of object for the domain of rough set theory, in conjunction with the dynamic of data under cloud environment
Property and magnanimity, probabilistic model and hypergraph model are introduced in rough set Model of Granular Computing, according to probability inference rule and super
Graph structure feature realizes the parallel granulation of complex data structures.Complicated cloud user is requested to carry out parallel granulating operation, is reduced
Response time of the cloud system to cloud user, improve the efficiency of service of cloud system.
S103. the discovery of dynamic cloud Service Source and dispatching algorithm based on semantic computation are designed.
On the basis of carrying out cloud computing resources and cloud computing user request based on Granular Computing modeling, counted using semanteme
Theory is calculated, using the ontology of semantic WEB, so that network itself is easier to understand, machine is automatically processed and is incorporated on cloud and announced
Information, extract the semantic information of cloud resource and cloud user request respectively, and the semantic information effectively stored；Further
Cloud resource discovery and dispatching algorithm based on semantic computation are realized using semantic search engine.Semantic information is made full use of,
Most matched resource can be requested with the cloud user for finding out and submitting in cloud resource known, meet optimal scheduling.In this implementation
Semantic search engine described in example uses the semantic search engine of California, USA university Irving branch school semantic computation development in laboratory,
Semantic search engine implementation semantic computation is theoretical, it provides the interface that a friendly problem drives for user to search for
Resource automatically and quickly establishes a solution according to the demand of user.By using semantic-based cloud resource discovery with
Scheduling, improves the efficiency of cloud system, realizes the optimal scheduling to cloud resource.
Technical solution advantage proposed by the present invention is as follows: one, in view of the isomery of cloud resource, dynamic, complexity the features such as, introduce
Rough set and Theory of Quotient Space establish the composite grain dynamic calculation model that two kinds of theories combine, for generating under cloud computing
DYNAMIC COMPLEX data structure object, using the self-adaptive processing of data own characteristic driving data, i.e., intelligent automatic granulation.
Two, in view of diversity, the dynamic, complexity of cloud user request the features such as, rough set, probability theory and Hypergraph Theory is introduced, is built
The composite grain computation model that these three theories combine is found, for the mass users request data generated under cloud environment, is realized
Hierarchic parallel selects basic element and division, realizes the scale granulation between granulosa.Three, to cloud resource and cloud user progress
After granulation modeling, for above two model, the basic thought of semantic computation is introduced, extracts the language of cloud resource and cloud user request
Adopted information, and effectively store them；Using semantic search engine, after cloud user requests to arrive, using its semantic information, by language
The semantic information of adopted search engine Auto-matching cloud resource, to realize the cloud resource discovery of semantic-based automation and adjust
Degree.
Present invention introduces the characteristics of Granular Computing divided and rule to use under dynamic cloud computing resources and cloud environment to lower
The complexity of family request introduces semantic computation thought, sufficiently extracts the semanteme of cloud resource and cloud user request on this basis,
Design semantic-based resource discovering and dispatching algorithm.The present invention realizes the efficient shared of cloud computing service resource, in theory
All have great importance and be worth in terms of research and practical application.Dynamic cloud resource proposed by the present invention based on Granular Computing
Administrative model and semantic-based resource discovering and dispatching algorithm, are applied in cloud computing service enterprise, and application effect will change
Kind about 30%, greatly cloud computing is pushed to advance.
Those of ordinary skill in the art will appreciate that realizing that all parts in above-described embodiment are can to pass through computer
Program is completed to instruct relevant hardware, and the program can be stored in a computer-readable storage medium, the program
When being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the storage medium can for magnetic disk, CD, only
Read storage memory (Read-Only Memory, ROM) or random access memory (Random Access Memory, RAM)
Deng.
Note that the above is only a better embodiment of the present invention and the applied technical principle.It will be appreciated by those skilled in the art that
The invention is not limited to the specific embodiments described herein, be able to carry out for a person skilled in the art it is various it is apparent variation,
It readjusts and substitutes without departing from protection scope of the present invention.Therefore, although being carried out by above embodiments to the present invention
It is described in further detail, but the present invention is not limited to the above embodiments only, without departing from the inventive concept, also
It may include more other equivalent embodiments, and the scope of the invention is determined by the scope of the appended claims.
Claims (9)
1. a kind of dynamic cloud managing computing resources method under cloud environment based on Granular Computing, which is characterized in that including walking as follows
It is rapid:
S101. intelligentized composite grain dynamic cloud resource tissue model is established；
S102. the dynamic calculation model of the composite grain cloud user service request of scale is established；
S103. the discovery of dynamic cloud Service Source and dispatching algorithm based on semantic computation are designed.
2. the dynamic cloud managing computing resources method under cloud environment according to claim 1 based on Granular Computing, feature
It is, the intelligentized composite grain dynamic cloud resource tissue model in the step S101 is to be managed based on rough set and the quotient space
By the composite grain dynamic calculation model combined.
3. the dynamic cloud managing computing resources method under cloud environment according to claim 2 based on Granular Computing, feature
It is, the step S101 includes: the composite grain dynamic calculation model established and combined based on rough set with Theory of Quotient Space,
For the DYNAMIC COMPLEX data structure object generated under cloud computing, using the self-adaptive processing of data own characteristic driving data,
I.e. intelligent automatic granulation is formed between granulosa and in granulosa including automatically selecting basic element and division in message structure
The structure in portion.
4. the dynamic cloud managing computing resources method under cloud environment according to claim 3 based on Granular Computing, feature
Be, the step S101 include: based on Theory of Quotient Space building the different grain size world between mutually convert, pass of depending on each other for existence
System constructs the expression of granularity based on rough set theory, portrays the dependence between granularity and concept；By by rough set mould
Type is embedded into Theory of Quotient Space model, indexes the object relationship between the different grain size world by granularity mapping mechanism, realizes
The automatic granulation of DYNAMIC COMPLEX structure.
5. the dynamic cloud managing computing resources method under cloud environment according to claim 1 based on Granular Computing, feature
It is, the dynamic calculation model of the composite grain cloud user service request of the scale in the step S102 is based on coarse
The composite grain computation model that collection, probability theory and Hypergraph Theory combine.
6. the dynamic cloud managing computing resources method under cloud environment according to claim 5 based on Granular Computing, feature
It is, the step S102 includes: to establish the composite grain combined based on rough set, probability theory and Hypergraph Theory to calculate mould
Type is realized hierarchic parallel selection basic element and division, is realized between granulosa for the user's request data generated under cloud environment
Scale granulation.
7. the dynamic cloud managing computing resources method under cloud environment according to claim 6 based on Granular Computing, feature
Be, the step S102 include: for rough set theory domain be object point set, in conjunction under cloud environment data it is dynamic
State property and magnanimity introduce probabilistic model and hypergraph model in rough set Model of Granular Computing, according to probability inference rule and
Hypergraph design feature realizes that complex data structures are granulated parallel.
8. the dynamic cloud managing computing resources method under cloud environment according to claim 1 based on Granular Computing, feature
It is, the step S103 includes: using semantic computation theory, and using the ontology of semantic WEB, machine is automatically processed and is incorporated into
The information announced on cloud, extracts the semantic information of cloud resource and cloud user request respectively, and is effectively deposited to the semantic information
Storage.
9. the dynamic cloud managing computing resources method under cloud environment according to claim 8 based on Granular Computing, feature
It is, the step S103 further include: use semantic search engine, requested according to cloud user, using its semantic information, by semanteme
The semantic information of search engine Auto-matching cloud resource realizes the cloud resource discovery and scheduling of semantic-based automation.
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