CN102033909B - Outsourcing method for supporting development of elastic cloud computing platform - Google Patents
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Abstract
The invention discloses an outsourcing method for supporting development of an elastic cloud computing platform. In the method, after functional demands and non-functional demands of users of a cloud computing platform terminal are determined, the following steps of functional demands matching, non-functional demands matching, non-functional quality indexes converging, matched candidate resources evaluating and optical outsourcing resources determining are performed, wherein in the step of non-functional quality indexes converging, for matched candidate resources, a converging matching domain of reference indexes is determined according to the dependence relationship between the reference indexes and subordinate indexes; in the step of matched candidate resources evaluating, a priority sequence of the matched candidate resources is determined according to an evaluation criterion of the cloud computing platform and the converging matching domain of the reference indexes; and in the step of optimal outsourcing resource determining, the optimal matched candidate resources in the evaluation sequencing are taken as the optimal outsourcing resource of the cloud computing platform. The method can be widely applied to the large-scale scientific research problem-solving environment, resource optimal distribution of the medium-sized and small enterprises, electronic commerce and individualized terminal application; and the method supports the configuration selection of the outsourcing resources and the development deployment of the elastic cloud computing platform.
Description
Technical field
The present invention relates to a kind of resource outsourcing method of supporting the exploitation of elasticity cloud computing platform; When being particularly useful for a cloud computing platform and not possessing the required part or all of resource of terminal user; Cloud computing platform is selected suitable outsourcing resource from its external resource registration body, with the resource requirement of satisfying the terminal user and the resource elasticity that guarantees cloud computing platform.
Background technology
The theory of reusing for resource for a long time and sharing constantly promotes the lasting evolution of computation schema.From early stage Distributed Calculation, grid computing finally, service compute, to the cloud computing of today, the use of IT resource and configuration mode are experiencing unprecedented change again.Under cloud computing environment; All IT resources (comprising hardware resource, software resource, architecture resource and platform resource) can be used by the user as the computing power that can supply call; Thereby make the IT resource become the convenient energy at a kind of similar electric power, water source; Be convenient to using as required and by with paying, greatly having improved the IT efficiency of resource and reduced use and maintenance cost [Michael Armbrust, the et al..Above the Clouds:A Berkeley View of Cloud Computing.Technical Report of resource of terminal user; UCB/EECS, 2009].Yet terminal user's resource requirement is unlimited and ever-increasing, and a limited cloud computing platform can not be held the required unlimited IT resource of terminal user.Therefore; When a cloud computing platform does not possess that the required IT resource of terminal user or cloud computing platform possess required IT resource but the trace utilization cost of resource when too high; The terminal user can then seek other cloud computing platforms to satisfy its resource requirement; Thereby cause the customer churn of current cloud computing platform, make it in intense market competition, be in unfavorable position.In addition, the resource outsourcing under the cloud computing environment relates to the tripartite interests of terminal user, resource provider and cloud computing platform, and the interests of each side are often inconsistent, and this makes resource outsourcing face new predicament.
Summary of the invention
Goal of the invention: technical matters to be solved by this invention is the deficiency to prior art; A kind of resource outsourcing method of supporting the exploitation of elasticity cloud computing platform is provided, thus the robustness that realizes the outsourcing stock assessment and under cloud computing environment, improve resource transfer.
In order to solve the problems of the technologies described above, the invention discloses a kind of resource outsourcing method of supporting the exploitation of elasticity cloud computing platform, after the terminal user's who has confirmed cloud computing platform functional requirement and nonfunction requirement, may further comprise the steps:
Functional requirement coupling step, through subscribing to cloud computing platform terminal user's functional requirement, candidate's resource of terminal user function demand is satisfied in search in cloud computing platform resource external registration body;
Nonfunction requirement coupling step, through subscribing to cloud computing platform terminal user's nonfunction requirement, candidate's resource of terminal user's nonfunction requirement is satisfied in search in above-mentioned functions demand matched candidate resource, is called the matching candidate resource;
NOT-function quality index polymerization procedure for the matching candidate resource, is confirmed its polymerization matching domain with reference to index according to it with reference to the dependence between index and the subordinate index;
Matching candidate stock assessment step according to the evaluation criteria of cloud computing platform and with reference to the polymerization matching domain of index, is confirmed the quality ordering of matching candidate resource; The quality that the dependence with reference between index and the subordinate index of said resource derives from the resource provider appointment relies on model, and different dependences will trigger dissimilar dependence conversion regimes;
Confirm best outsourcing resource step, get the best outsourcing resource of matching candidate resource optimum in the assessment ordering, thereby accomplish the resource outsourcing process in the exploitation of elasticity cloud computing platform as cloud computing platform.
Among the present invention, cloud computing platform terminal user's functional requirement provides with the form of key word.
Among the present invention, cloud computing platform terminal user's nonfunction requirement provides with the form of qualitative restrain.
Among the present invention, be the dependence function with reference to the dependence between index and the subordinate index.
Among the present invention, the evaluation criteria of cloud computing platform is the satisfaction function.Said satisfaction function derives from the quality satisfaction model of cloud computing platform, and it is unique foundation of a cloud computing platform assessment outsourcing resource.(specifically referring to document Mohammad Alrifai; Thomass Risse, " Combining global optimization with local selection for efficient QoS-aware service composition, " 18th International Conference on World WideWeb (WWW); Pp.881-890; 2009) satisfaction is a qualitative description, as: the value of effectiveness type quality index is big more, and satisfaction is big more; The value of cost type quality index is more little, and satisfaction is big more.Exist a kind of functional dependence to concern that this dependence is called the satisfaction function between this qualitative assessment be unfavorable for the cloud platform of describing qualitatively, the size that therefore we suppose satisfaction in this patent and the value of quality index.Illustrate: for cost type quality index " price P ", if P＜100, the cloud platform can be S (P)=1-P/100) about its satisfaction function S (P).
Among the present invention, the foundation that the matching candidate resource is assessed is that the satisfaction function of cloud computing platform is with reference to the maximum occurrences in the polymerization matching domain of index.
Among the present invention, comprise following three kinds of situations: (1) explicit function relation with reference to the dependence between index and the subordinate index; (2) implicit function relation; (3) no funtcional relationship.
Among the present invention, said functional requirement coupling step comprises following substep:
The functional requirement key word that the terminal user of subscription cloud computing platform provides;
According to the functional description explanation of candidate's resource and the similarity of functional requirement key word in the semantic matches technique computes resource registering mechanism; (said semantic matches technology can referring to: Giunchiglia, F., Yatskevich, M., Shvaiko, P.:Semantic matching:Algorithms and implementation.Journal on Data Semantics (2007))
Set similarity threshold, similarity is not less than the result of candidate's resource of threshold value as the functional requirement coupling.
The said nonfunction requirement coupling of semantic matches technology step comprises following substep:
The NOT-function qualitative restrain that the terminal user of subscription cloud computing platform provides;
For functional requirement matched candidate resource, relatively whether its quality table present worth meets corresponding NOT-function qualitative restrain;
If all quality table present worths of candidate's resource all meet the corresponding NOT-function qualitative restrain of terminal user,, otherwise then abandon this candidate's resource then with the result of this candidate's resource as the nonfunction requirement coupling.
Among the present invention, the dependence that said quality has relied on model description between each quality index of resource of resource publisher's issue.When carrying out the resource issue, the publisher can issue multiple different quality level version usually simultaneously, so that the terminal user that attraction has the different quality preference.These different quality level versions have constituted the quality level space of candidate's resource, defined candidate's resource with reference to the quality dependence between index and the subordinate index.Quality relies on model and has portrayed the quality compromise between reference index and the subordinate index through dependence, and it is for cloud computing platform the quality evaluation of matching candidate resource to be served.
Among the present invention, said quality satisfaction model has been portrayed the comprehensive satisfaction of cloud computing platform and the relation between each quality index value of outsourcing resource, for the assessment of matching candidate resource and selection provide the foundation that quantizes.
Cloud computing is as a kind of IT resource application model of paying as required, and the price of resource often occupies an important position in the comprehensive assessment of cloud computing platform, therefore can with price guideline as quality rely on model and quality satisfaction model with reference to index.
Beneficial effect: compared with prior art, effect of the present invention is embodied in: 1) proposed the deficiency that a kind of resource outsourcing mechanism remedies cloud computing platform own resource kind and content, realized " the resource unlimitedness " of cloud computing platform.2) design the appraisal procedure of resource outsourcing under a kind of cloud computing environment, be used for three parts's (terminal user, resource publisher, cloud computing platform) interests that the balancing resources outsourcing relates to.3) through resource outsourcing mechanism, the resource between the different cloud computing platforms has realized farthest sharing, and has improved the extent for multiplexing of resource and has reduced the cloud computing platform development and maintenance cost.
The present invention can be widely used in most optimum distribution of resources, ecommerce and the personalized terminal applies of large-scale scientific research problem solving environment, medium-sized and small enterprises; Support the selection of configuration of outsourcing resource and the exploitation of elasticity cloud computing platform to dispose, belong to computer application field.
Description of drawings
Below in conjunction with accompanying drawing and embodiment the present invention is done specifying further, above-mentioned and/or otherwise advantage of the present invention will become apparent.
Fig. 1 is the resource outsourcing method flow diagram of support elasticity cloud computing platform exploitation of the present invention.
Fig. 2 is a cloud computing platform resource outsourcing instance of the present invention.
Fig. 3 is for resource registering among the embodiment and call model.
Embodiment
Fig. 3 be under the SOA framework resource registering, inquire about and call model.Hold the calling interface of the supplier of resource, mainly comprise I/O parameter (I/O), type of message, operation and functional and the description of non-functional quality etc. to resource registering center releasing resources.Resource provider also need provide the information of self simultaneously, like title, the contact approach of resource provider and the reference address URL that asks this resource.The terminal user carries out resource query according to its functional requirement and nonfunction requirement to the resource registering center, and returns the resource information that meets terminal user's demand, like I/O parameter and reference address etc.According to the resource information that obtains; The terminal user proposes resource request and decides through consultation the relevant contract (like service time, service level and service fee etc.) of calling to the supplier of this resource; Bind terminal user and resource requirement according to calling contract, accomplish the resource transfer process.
Fig. 1 is the resource outsourcing method flow diagram of support elasticity cloud computing platform exploitation of the present invention, and step is following:
Step 1: subscribe to cloud computing platform terminal user's functional requirement, candidate's resource of terminal user function demand is satisfied in search from cloud computing platform resource external registration body, comprises following substep:
(1) subscribe to the functional requirement key word that the cloud computing platform terminal user provides, key word can be single key, also can be the some key combination sequences that provide with " AND " or " OR " or " NOT " form; (2) according to the functional description explanation of candidate's resource and the similarity of functional requirement key word in the semantic matches technique computes resource registering mechanism, confirm the functional description explanation of candidate's resource and incidence relation and the correlation degree between the functional requirement key word through the resource body semantic base that defines in advance; (3) set similarity threshold, if the similarity of the functional description explanation of certain candidate's resource and functional requirement key word is not less than preset threshold, then among the result queue with this candidate's resource adding functional requirement coupling; Otherwise, abandon this candidate's resource.
Step 2: subscribe to cloud computing platform terminal user's nonfunction requirement, in candidate's resource of function match, confirm to satisfy candidate's resource of terminal user's nonfunction requirement, be called the matching candidate resource, comprise following substep:
(1) subscribes to the NOT-function qualitative restrain that the cloud computing platform terminal user provides; Qualitative restrain is the value constraint that is applied on each dimension qualitative attribute; In order to embody terminal user's quality preference; As for a terminal user user, its NOT-function qualitative restrain possibly be { price＜100dollars, execution time＜10s}; (2) for functional requirement matched candidate resource, relatively whether its quality table present worth meets corresponding NOT-function qualitative restrain; (3), then this candidate's resource is added the result queue of nonfunction requirement coupling, otherwise then abandon this candidate's resource if all quality table present worths of candidate's resource all meet the corresponding NOT-function qualitative restrain of terminal user.
Step 3:, confirm that it is with reference to the dependence between index and each the subordinate index for each matching candidate resource that satisfies terminal user function demand and nonfunction requirement.Quality dependence by the resource provider issue can be divided into following three kinds: explicit function relation, implicit function relation, irrelevant.The quality dependence that all are dissimilar is carried out function conversion (the subordinate index will convert the function about the subordinate index to reference to index as independent variable), to confirm by the mapping relations of subordinate mark sense with reference to index.According to mapping relations the matching domain equivalence of subordinate index is converted into the matching domain with reference to index, and then confirms polymerization matching domain with reference to index.
Step 4: satisfy the matching candidate resource of terminal user function demand and nonfunction requirement for each; According to the quality satisfaction model of cloud computing platform and the polymerization matching domain with reference to index of this matching candidate resource, calculate the maximum occurrences of this matching candidate resource on quality satisfaction model.For all matching candidate resources, carry out descending sort according to its maximum satisfaction value of calculating gained, this ordering is the quality ordering of matching candidate resource.
Step 5: according to the good and bad sequence of matching candidate resource, select wherein optimum candidate's resource to feed back to the terminal user of cloud computing platform, accomplish the resource outsourcing process in the exploitation of elasticity cloud computing platform as the outsourcing resource of the best.
Be the resource outsourcing method in the example explanation elasticity cloud computing platform with the Map Services resource request among Fig. 2 below.When the user to cloud computing platform request Map Services resource and cloud computing platform self when not possessing this Service Source, the resource outsourcing process starts, its step is following:
Step 1: functional requirement coupling step; The resource searching engine start that cloud computing platform is inner; Search comprises the Service Source of key word " map (map) " in cloud computing platform resource external space, finds and four the candidate service resources of key word similarity greater than defined threshold: Google Maps (GoogleMap), Baidu's map (BaiduMap), Yahoo's map (YahooMap) and Microsoft's map (MicroMap).
Step 2: nonfunction requirement coupling step; Enough high (effective resolution≤30 meter of the bearing accuracy that the cloud computing platform terminal user hopes the Map Services resource; This is a nonfunction requirement), so degree of specialization is higher and Google Maps (GoogleMap) that customer group is bigger and Baidu's map (BaiduMap) are as matching candidate resource to be assessed.
Step 3: NOT-function quality index polymerization procedure; Choose price guideline price (i.e.; P) as in the outsourcing stock assessment with reference to index; (i.e. T) as the subordinate index, sets up the price and the mapping relations between the response time: the T of Google Maps and Baidu's map respectively and with location response time time
G=f
G(P) and T
B=f
B(P).In conjunction with the demand territory of terminal user to resource price and response time, and by the price territory and the response time territory of the resource of resource provider issue itself, definite respectively Google Maps and Baidu's map are at price and the matching domain on the response time.Further, in conjunction with mapping relations T
G=f
G(P) and T
B=f
B(P), confirm that respectively two Map Services resources are with reference to index--the matching domain on the price is designated as Range
G(P) and Range
B(P) (G and B represent GoogleMap and BaiduMap respectively).
Step 4: matching candidate stock assessment step, according to cloud computing platform about with reference to index--the polymerization matching domain Range that obtains in the satisfaction function S (P) of price and the step 3 with reference to index-price
G(P) and Range
B(P), calculate the satisfaction S of cloud computing platform respectively to Google Maps and Baidu's map
GWith satisfaction S
B
Step 5: confirm best outsourcing resource step, if satisfaction S
G＞satisfaction S
B, then Google Maps feeds back to cloud computing platform for best matching candidate resource and with it, feeds back to the terminal user by cloud computing platform again; If satisfaction S
G＜satisfaction S
B, then Baidu's map feeds back to cloud computing platform for best matching candidate resource and with it, feeds back to the terminal user by cloud computing platform again; If satisfaction S
G=satisfaction S
B, then the two is all best matching candidate resource.
Use today of develop rapidly in cloud computing; The terminal user hope from cloud computing platform convenient and cheap obtain required IT resource; And cloud computing platform also hopes to realize its resource unlimitedness by resource outsourcing, and multi-terminal user improves its economic benefit to attract more.The present invention reaches following effect: suitable outsourcing resource is dynamically sought to satisfy terminal user's resource requirement in (1) from the external resource space of cloud computing platform, improve the resource extensibility of cloud computing platform.(2) when resource transfer failure or resource exception generation, locate the outsourcing resource that can supply substitute apace, improve the robustness of resource transfer under the cloud computing environment.
The invention provides a kind of thinking and method of supporting the resource outsourcing method of elasticity cloud computing platform exploitation; The method and the approach of concrete this technical scheme of realization are a lot, and the above only is a preferred implementation of the present invention, should be understood that; For those skilled in the art; Under the prerequisite that does not break away from the principle of the invention, can also make some improvement and retouching, these improvement and retouching also should be regarded as protection scope of the present invention.The all available prior art of each ingredient not clear and definite in the present embodiment realizes.
Claims (8)
1. a resource outsourcing method of supporting the exploitation of elasticity cloud computing platform is characterized in that, after the terminal user's who has confirmed cloud computing platform functional requirement and nonfunction requirement, may further comprise the steps:
Functional requirement coupling step, through subscribing to cloud computing platform terminal user's functional requirement, candidate's resource of terminal user function demand is satisfied in search in cloud computing platform resource external registration body;
Nonfunction requirement coupling step, through subscribing to cloud computing platform terminal user's nonfunction requirement, candidate's resource of terminal user's nonfunction requirement is satisfied in search in above-mentioned functions demand matched candidate resource, is called the matching candidate resource;
NOT-function quality index polymerization procedure for the matching candidate resource, is confirmed its polymerization matching domain with reference to index according to it with reference to the dependence between index and the subordinate index;
Matching candidate stock assessment step according to the evaluation criteria of cloud computing platform and with reference to the polymerization matching domain of index, is confirmed the quality ordering of matching candidate resource;
Confirm best outsourcing resource step, get the best outsourcing resource of matching candidate resource optimum in the assessment ordering, thereby accomplish the resource outsourcing process in the exploitation of elasticity cloud computing platform as cloud computing platform;
Said nonfunction requirement coupling step comprises following substep:
The NOT-function qualitative restrain that the terminal user of subscription cloud computing platform provides, qualitative restrain are value constraints that is applied on each dimension qualitative attribute, in order to embody terminal user's quality preference;
For functional requirement matched candidate resource, relatively whether its quality table present worth meets corresponding NOT-function qualitative restrain;
If all quality table present worths of candidate's resource all meet the corresponding NOT-function qualitative restrain of terminal user,, otherwise then abandon this candidate's resource then with the result of this candidate's resource as the nonfunction requirement coupling.
2. the resource outsourcing method of support elasticity cloud computing platform exploitation according to claim 1 is characterized in that cloud computing platform terminal user's functional requirement provides with the form of key word.
3. the resource outsourcing method of support elasticity cloud computing platform exploitation according to claim 1 is characterized in that cloud computing platform terminal user's nonfunction requirement provides with the form of qualitative restrain.
4. the resource outsourcing method of support elasticity cloud computing platform exploitation according to claim 3 is characterized in that, is the dependence function with reference to the dependence between index and the subordinate index.
5. the resource outsourcing method of support elasticity cloud computing platform exploitation according to claim 3 is characterized in that the evaluation criteria of cloud computing platform is the satisfaction function.
6. the resource outsourcing method of support elasticity cloud computing platform according to claim 5 exploitation is characterized in that, the foundation that the matching candidate resource is assessed is that the satisfaction function of cloud computing platform is with reference to the maximum occurrences in the polymerization matching domain of index.
7. the resource outsourcing method of support elasticity cloud computing platform exploitation according to claim 1 is characterized in that, comprises following three kinds of situations with reference to the dependence between index and the subordinate index:
(1) explicit function relation;
(2) implicit function relation;
(3) no funtcional relationship.
8. the resource outsourcing method of support elasticity cloud computing platform exploitation according to claim 2 is characterized in that, said functional requirement coupling step comprises following substep:
The functional requirement key word that the terminal user of subscription cloud computing platform provides;
According to the functional description explanation of candidate's resource and the similarity of functional requirement key word in the semantic matches technique computes resource registering mechanism;
Set similarity threshold, similarity is not less than the result of candidate's resource of threshold value as the functional requirement coupling.
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| US9176773B2 (en) | 2011-06-29 | 2015-11-03 | Microsoft Technology Licensing, Llc | Virtual machine migration tool |
| CN103426040A (en) * | 2012-05-14 | 2013-12-04 | 中国银联股份有限公司 | Research and development management system |
| CN105824756B (en) * | 2016-03-17 | 2019-01-04 | 南京大学 | A kind of out-of-date demand automatic testing method and system based on code dependence |
| CN108737145A (en) * | 2017-04-24 | 2018-11-02 | 中兴通讯股份有限公司 | A kind of matched method and device of system resource application |
| US10831550B2 (en) * | 2018-03-27 | 2020-11-10 | Oracle Financial Services Software Limited | Computerized control of execution pipelines |
| CN108664330B (en) * | 2018-05-16 | 2019-12-10 | 哈尔滨工业大学（威海） | cloud resource allocation method based on variable neighborhood search strategy |
| CN113503897A (en) * | 2021-07-08 | 2021-10-15 | 广州小鹏自动驾驶科技有限公司 | Parking map quality inspection method and device and electronic equipment |
| CN115510331B (en) * | 2022-11-15 | 2023-03-14 | 山东紫菜云数字科技有限公司 | Shared resource matching method based on idle amount aggregation |
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| US20030236822A1 (en) * | 2002-06-10 | 2003-12-25 | Sven Graupner | Generating automated mappings of service demands to server capacites in a distributed computer system |
| CN101777792A (en) * | 2009-12-24 | 2010-07-14 | 深圳先进技术研究院 | Safety communication system and method of electric network |
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| US20030236822A1 (en) * | 2002-06-10 | 2003-12-25 | Sven Graupner | Generating automated mappings of service demands to server capacites in a distributed computer system |
| CN101777792A (en) * | 2009-12-24 | 2010-07-14 | 深圳先进技术研究院 | Safety communication system and method of electric network |
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