CN105208076B - A kind of multiple target service combining method perceived based on correlation - Google Patents
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Abstract
The present invention relates to a kind of multiple target service combining method based on correlation, including：By candidate service set CiIn there is no the first candidate service set for matching of candidate service deposit of service quality correlationIt is rightIn candidate service compare to obtain winning candidate service and be stored in winning candidate service set two-by-twoFrom CiIt is middle to delete corresponding non-winning candidate service to obtain the sub-services set C to matchi′；By all Ci' combine to form new Services Composition solution space S '；Multiple Services Composition solution formation are randomly selected from S ' and represent Xie JiheIt calculatesIn each Services Composition solution SpRough service quality value and be layered；It is exhaustive it is selected it is s layer first in whole Services Composition solutions correlation information, to obtain the active service mass value of the whole Services Composition solutions；Corresponding Services Composition solution is ranked up according to active service mass value, K Services Composition solution is to obtain suboptimum Services Composition solution set before selection.The present invention can quickly obtain suboptimal solution, improve solution efficiency.
Description
Technical field
The present invention relates to cloud computing management and control technology field more particularly to a kind of multiple targets perceived based on correlation
Service combining method.
Background technology
As SOA (Service-Oriented Architecture, Services Oriented Achitecture) technologies and web take
More and more being served by with package interface occurs on internet in the appearance of business technology.With interconnection web-based applications
Number drastically increases, and many service industry standards occurs, such as：WSDL(Web Services Description
Language, web services definition language) and UDDI (Universal Description Discovery and
Integration, universal description are found and integrated service) etc..Business process usually requires a series of sub-services and is assisted
Make, to complete the function of needing, this process is called Services Composition.Services Composition allows developer according to pre-defining
Demand sub-services are combined into a workflow.
Different suppliers, which provide the same or similar mystery of function, has the candidate service of different non-functional features.It is non-functional
Feature is mainly embodied with service quality, when a service request reaches, since service quality has the attribute of multidimensional, such as
The problem of including response time, throughput and availability etc., being a multiple-objection optimization, therefore how to select suitable son clothes
It is engaged in realizing that optimal end-to-end quality of service becomes research hotspot.
In order to handle the tradeoff and compromise between different service quality attribute, in the prior art by multiple-objection optimization the problem of
The problem of being converted into single object optimization is broadly divided into linear weighted function and target is converted to two class of constraints.Wherein, it is linear to add
Power normalizes different target, and corresponding weight is then set to be added again.On the one hand, it needs to know target during normalization
Maximum value, minimum value or average value, however be not easy to obtain these values in practical application；On the other hand, weight is set also
Need to know the priority of different target, priority data is also not easy to know, and how to set constraints in practical application
It does not solve yet.
Also, many existing Services Composition solutions do not account for the service quality phase between service in the prior art
Guan Xing, the service quality value of one sub-services may rely on other sub-services during practical application.Such as：Selection by two or
The sub-services of certain multiple company of person are placed in same workflow, the Service Quality of the sub-services of two or more certain companies
Amount can give a discount.For another example, the predetermined company of aviation is in charging process, if user uses Credit Card Payments, it is extra to receive
Expense；If user uses debit payments, without extra expense.For another example, it selects two sub-services being placed on same clothes
It is engaged on device, transmission time will greatly reduce between the two, and the response time of composite services also accordingly reduces.If do not consider Service Quality
The correlation of amount can then influence to obtain the service solution of Services Composition；But service quality correlation is taken into account into Services Composition, can also
So that Services Composition problem becomes extremely complex.Therefore, the technical issues of how improving solution efficiency, be urgent need to resolve.
Invention content
One of the objects of the present invention is to provide a kind of multiple target service combining method based on correlation, to provide one kind
Solution efficiency is high, considers the multiple target service combining method of correlation.
To achieve the above object, the present invention proposes a kind of multiple target service combining method based on correlation, including：
Candidate service set CiIn each candidate service include multiple attributes, if an optional candidate service is candidate with residue
At least one corresponding attribute of candidate service has correlation in service, then corresponding candidate service has service quality phase
Guan Xing；If the corresponding attribute of a candidate service and every other candidate service is all without correlation, the candidate service
There is no service quality correlation, and there is no the candidate service of service quality correlation to be stored in the first candidate service to match this
Set
To the first candidate service setIn candidate service compared two-by-two with obtain winning candidate service with
Acquired winning candidate service is stored in winning candidate service set by non-winning candidate serviceAnd from described first
Candidate service setDelete non-winning candidate service；
From the candidate service set CiIt is middle to delete corresponding non-winning candidate service to obtain the sub-services to match
Set C 'i；
By all sub-services set C 'iIt combines to form new Services Composition solution space S '；From Services Composition solution sky
Between multiple Services Composition solutions formation randomly selected in S ' represent Xie JiheIt calculates and described represents Xie JiheIn each service group
Close solution SpRough service quality value and be layered；
It is exhaustive it is selected it is s layer first in whole Services Composition solutions correlation information, to obtain the whole Services Composition solutions
Active service mass value；
Corresponding Services Composition solution is ranked up according to active service mass value, before selection K Services Composition solution with
Obtain suboptimum Services Composition solution set.
Optionally, the candidate service set CiIn each candidate service include multiple attributes, if optional one candidate clothes
Business has correlation at least one corresponding attribute of candidate service in remaining candidate service, then corresponding candidate service tool
There is service quality correlation；If the corresponding attribute of a candidate service and every other candidate service all without correlation,
Then the candidate service does not have service quality correlation, and this is not had what the candidate service deposit of service quality correlation matched
First candidate service setThe step of in using equation below judge each candidate service whether have service quality correlation：
In formula,Represent the candidate service for completing sub-services i,Represent candidate serviceR-th
Whether attribute has correlation；Represent candidate serviceWhether there is service quality correlation；" ∨ " representative is asked and is transported
It calculates.
Optionally, the candidate service set CiIn each candidate service include multiple attributes, if optional one candidate clothes
Business has correlation at least one corresponding attribute of candidate service in remaining candidate service, then corresponding candidate service tool
There is service quality correlation；If the corresponding attribute of a candidate service and every other candidate service all without correlation,
Then the candidate service does not have service quality correlation, and this is not had what the candidate service deposit of service quality correlation matched
First candidate service setThe step of after, further include：
Calculate each candidate service setIn each candidate service Grade values, candidate taken to described according to Grade values
Business setMiddle whole candidate service carries out ascending sort.
Optionally, it is described from the candidate service set CiIt is middle to delete corresponding non-winning candidate service to obtain phase
The sub-services set C ' matchediThe step of in sub-services set C ' obtained according to equation belowi：
In formula, C 'iFor sub-services set, CiFor candidate service set,For winning candidate service set,To wait
Select set of service.
Optionally, it is described by whole sub-services set C 'iIn the step of combination is to form new Services Composition solution space S '
Services Composition solution space S ' is obtained using equation below：
S '=C '1×C′2×…×C′m
In formula, C 'iRepresent sub-services set, i=1,2,3 ..., m, symbol "×" represents cartesian product.
Optionally, it is described the formation of multiple Services Composition solutions is randomly selected from the Services Composition solution space S ' to represent disaggregation
It closesIt calculates and described represents Xie JiheIn each Services Composition solution SpRough service quality value and the step of being layered wrap
It includes：
Choose the middle any two Services Composition solution S of Services Composition solution space S 'piAnd SpjCompared two-by-two, if clothes
Business combination solution SpiWinning Services Composition solution Spj, by Services Composition solution SpjIt is added to the Services Composition solution SpiQueueIn,
And by Services Composition solution SpiAdd in the Services Composition solution SpjQueueIn；
DefinitionUtilize LiRepresent i-th layer of Services Composition solution set；Since first layer i=1,
InitializationWhenWhen, it finds allServices Composition solution Spj, and by the SpjIt adds in
LiIn, then find queueIn all Services Composition solutionFrom each queueMiddle deletion Services Composition solution Spj, then
By Services Composition solutionIt is deleted from RemainingSet；
It repeats the above process, untilSo as to obtain the shared q layers of services of Services Composition solution space S '
Combination solution；
Wherein, queueBe it is all can be with winning Services Composition solution SpServices Composition solution set,It is all SpIt is excellent
The set of the solution of victory.
The embodiment of the present invention is layered by calculating the rough service quality of Services Composition solution, and corresponding selected by calculating
The correlation information of candidate service in layer, to obtain active service mass value, so as to handle real system with correlation
Services Composition situation, the suboptimal solution of real system can be quickly obtained, so as to improve solution efficiency.
Description of the drawings
The features and advantages of the present invention can be more clearly understood by reference to attached drawing, attached drawing is schematically without that should manage
It solves to carry out any restrictions to the present invention, in the accompanying drawings：
Fig. 1 is a kind of multiple target service combining method block diagram based on correlation provided in an embodiment of the present invention；
Fig. 2 is relatively flow diagram winning to candidate service in one embodiment of the invention；
Fig. 3 is solution Services Composition solution flow diagram in one embodiment of the invention.
Specific embodiment
With reference to the accompanying drawings and examples, the specific embodiment of the present invention is described in further detail.Implement below
Example is used to illustrate the present invention, but be not limited to the scope of the present invention.
An embodiment of the present invention provides the multiple target service combining method based on correlation, as shown in Figure 1, including：
S100, candidate service set CiIn each candidate service include multiple attributes, if an optional candidate service with it is surplus
At least one corresponding attribute of candidate service has correlation in remaining candidate service, then corresponding candidate service has service
Quality correlation；If the corresponding attribute of a candidate service and every other candidate service is all without correlation, the time
Choosing service does not have service quality correlation, and does not have the candidate service of service quality correlation to be stored in the first time to match this
Select set of service
S200, to the first candidate service setIn candidate service compared two-by-two with obtain winning candidate service with
Acquired winning candidate service is stored in winning candidate service set by non-winning candidate serviceIt is and candidate from first
Set of serviceDelete non-winning candidate service；
S300, from candidate service set CiIt is middle to delete corresponding non-winning candidate service to obtain the sub-services to match
Set C 'i；
S400, by all sub-services set C 'iIt combines to form new Services Composition solution space S '；From Services Composition solution sky
Between multiple Services Composition solutions formation randomly selected in S ' represent Xie JiheCalculating represents Xie JiheIn each Services Composition solution
SpRough service quality value and be layered；
S500, it is exhaustive it is selected it is s layer first in whole Services Composition solutions correlation information, to obtain the whole service groups
Close the active service mass value of solution；
S600, corresponding Services Composition solution is ranked up according to active service mass value, K Services Composition before selection
Solution is to obtain suboptimum Services Composition solution set.
Explanation is unfolded in the step of below in conjunction with the accompanying drawings and embodiment is to institute of embodiment of the present invention providing method.
In the embodiment of the present invention, represent m sub-services with set I={ 1,2 ..., m }, have for each sub-services i
niA candidate service can be completed.The niA candidate service candidate service setTo represent；Service group
Close solutionRepresent some specific Services Composition solution, whereinIt represents to complete sub-services i
Candidate service；S=C1×C2×…×CmRepresent solution space.arRepresent the attribute of r-th of service quality, all Service Qualities
Measure attribute vector A=(a1,a2,…,al) represent.From the service quality value of sub-services to the service quality value of composite services
Aggregate function useIt represents, aggregate function has addition, multiplication, maximization, minimum and and hands over
Deng.
Dep is used in the embodiment of the present inventionr=<Ssp,vsp>Represent r-th of service quality correlation set, wherein SspGeneration
The sub-services that table has correlation combine, vspRepresent the service quality value of the sub-portfolio.Binary variableRepresent candidate serviceR-th of attribute whether have correlation；Represent candidate serviceWhether there is service quality correlation；" ∨ " generation
Table union；Represent candidate serviceThe default value of r-th of attribute.
V(Sp)=(v1(Sp),…,vr(Sp),…,vl(Sp)) for representing composite services SpService quality value.For appointing
Two composite services of meaning, SpWith S 'pIf following formula is set up, referred to as Sp＞ S 'p, i.e. SpWinning S 'p。
Wherein, >=represent to be better than or equal, ＞ expressions are strictly better than.Optimal Services Composition solution is that own in solution space S
Not by the winning disaggregation of other solutions, i.e. optimal solution setFor
Desired value is maximized quality of service attribute, its service quality value is negated.
First, introduction step S100, candidate service set CiIn each candidate service include multiple attributes, if optional one
Candidate service has correlation at least one corresponding attribute of candidate service in remaining candidate service, then corresponding candidate
Service has service quality correlation；If the corresponding attribute of a candidate service and every other candidate service is all without phase
Guan Xing, then the candidate service does not have service quality correlation, and does not have the candidate service of service quality correlation to be stored in phase this
Matched first candidate service setThe step of.
Candidate service set CiIn comprising multiple candidate services, each candidate service includes multiple attributes.If for wherein
One candidate service, if one of attribute of the candidate service and candidate service set CiIn other at least one candidates
The corresponding attribute of service has correlation, then judges that the candidate service has service quality correlation.If for one of them
Candidate service, if the candidate service with all candidate services in remaining candidate service all without correlation, judge the time
Choosing services no correlation.
In the embodiment of the present invention, judge whether a candidate service has service quality correlation using formula (1)
Wherein, binary variableRepresent candidate serviceWhether there is service quality correlation.
For each candidate service set Ci, find out wherein allCandidate service, and condition will be met
Candidate service is put into candidate service setThe first candidate service setIt is represented using following formula：
Secondly, S200 is introduced, to the first candidate service setIn candidate service compared two-by-two it is winning to obtain
Acquired winning candidate service is stored in winning candidate service set by candidate service and non-winning candidate serviceAnd
From the first candidate service setThe step of deleting non-winning candidate service.
According to the default value of the corresponding attribute of each candidate service, the first candidate service set is calculated using following formula
In each candidate service Grade values：
And according to Grade values to the first candidate service setIn candidate service be ranked up, in the embodiment of the present invention
Using ascending sort.Select the candidate service of Grade value minimumsIt is placed in the first candidate service setFirst, other time
Choosing serviceIt is sequentially placed into corresponding position.
Then from the first candidate service setIt is middle to obtain winning candidate service and non-winning candidate service.
In the embodiment of the present invention, winning candidate service set is definedRepresent the first candidate service setIn most
Excellent candidate service set.Variable ckRepresent the first candidate service setIn k-th of candidate service, binary variable
IsDominated (k)=1 represents candidate service ckBy winning.
As shown in Fig. 2, initialize winning candidate service setFor all candidate service ck, initially
Change binary variable IsDominated (k)=0.From candidate service c1Start to compare, until the last one candidate service ck.For time
Choosing service ckComparison be known as kth wheel and compare, process is as follows：If candidate service ckWinning candidate service cj, then label
IsDominated (j)=1 is further continued for candidate service ckCandidate service belowThan
Compared with；Not so, successively by candidate service ckCandidate service c laterj(j>K, IsDominated (j)=0) compare.It is if candidate
Service cjWinning candidate service ck, label IsDominated (k)=1, and leap to the wheel of kth+1 and compare；Otherwise, if waited
Choosing service ckWith candidate service cjIt is not winning mutually, then by candidate service ckWith with candidate service belowCompare.The comparison procedure continues always, until proceeding to the first candidate service set
In last wheel candidate service comparison.
The IsDominated (k) of all candidate services is traversed, if IsDominated (k)=0, by candidate service ck
Add in winning candidate service setI.e. winning candidate service setIn save the first candidate service setIn optimal candidate service.
Again, S300 is introduced, from candidate service set CiIt is middle to delete corresponding non-winning candidate service to obtain phase
The sub-services set C ' matchediThe step of.
If IsDominated (k)=1, candidate service ckFor not preferred candidate service.Son is solved according to equation below
Set of service C 'i：
4th, it introduces multiple sub-services set C 'iIt combines to form new Services Composition solution space S '；From the service
Multiple Services Composition solution formation are randomly selected in combination solution space S ' and represent Xie JiheIt calculates and described represents Xie JiheIn it is every
A Services Composition solution SpRough service quality value and the step of be layered.
Using equation below (4) by multiple sub-services set C 'iIt combines to obtain Services Composition solution space S '.
S '=C '1×C′2×…×C′m (4)
Multiple Services Composition solutions formation are randomly selected from acquisition Services Composition solution space S ' and represent Xie JiheThe present invention
Multiple represent is randomly choosed in one embodiment to solve, such as 10000 are selected in an embodiment and represents solution, for this 10000 generations
Table solution does not first consider correlation information, directly calculates each Services Composition solution S by aggregate functionpRough service quality value Vc
(Sp)。
Shown in aggregate function following formula (5)：
Rough service quality value Vc(Sp) as shown in formula (6)：
Vc(Sp)=(v1c(Sp),…,vrc(Sp),…,vlc(Sp)) (6)
For example, being the attribute being added for aggregate function, the service quality value of composite services solution is equal to each sub-services
The sum of service quality value；It is the attribute being multiplied for aggregate function, the service quality value of composite services solution is equal to each sub-services
Service quality product.
According to rough service quality value Vc(Sp) selected 10000 are represented with Xie Jinhang layerings and sequence, according to representative
The layering of solution represents the fine or not information solved to obtain this 10000.
5th, introduce S500, it is exhaustive it is selected it is s layer first in whole Services Composition solutions correlation information, to obtain entirely
The step of active service mass value of portion's Services Composition solution.
According to Services Composition solution S each in above-mentioned stepspRough service quality value and altogether the number of plies, determine required for
The number of plies s of the Services Composition solution of selection, such as need the Services Composition solution of three first layers, the then exhaustive three first layers Services Composition solution
All correlation informations, so as to obtain the active service mass value of these Services Composition solutions, so as to obtain Services Composition
Solution spaceShare q layers of Services Composition solution.
It is as follows that delaminating process is carried out to selected preceding s layers of Services Composition solution：As shown in figure 3, for each service group
Close solution Sp, two queues are setWithWherein, queueRepresent it is all can be with winning Services Composition solution SpServices Composition
The set of solution, queueRepresent all Services Composition solution SpThe set of winning Services Composition solution.
For representing Xie JiheIn all Services Composition solution Spi, initialization Wherein, it services
Combination solution SpiExpression represents Xie JiheIn i-th of Services Composition solution.
From representing Xie JiheIn in all Services Composition solution optional two Services Composition solutions compared two-by-two, if clothes
Business combination solutionWinning Services Composition solution Spj, then by Services Composition solution SpiAdd in Services Composition solution SpjQueueIn, it will take
Business combination solution SpjAdd in Services Composition solutionQueueIn；If Services Composition solution SpjWinning Services Composition solution Spi, then will clothes
Business combination solution SpiAdd in Services Composition solution SpjQueueIn, Services Composition solution SpjAdd in Services Composition solution SpiQueue
In.
DefinitionUse LiRepresent the set of i-th layer of Services Composition solution.It is opened from first layer (i=1)
Begin, initializationWhenWhen, it finds allServices Composition solution Spj, and by the Spj
Add in LiIn, then find queueIn all Services Composition solutionFrom each queueMiddle deletion Services Composition solution
Spj, then by Services Composition solutionIt is deleted from RemainingSet.It repeats the above process, untilUntil,
It can obtain representing Xie Jihe at this timeOne shared q layers of solution.
Finally, it introduces S600, corresponding Services Composition solution be ranked up according to active service mass value, K before selection
The step of a Services Composition solution is as suboptimum Services Composition solution set.
According to active service mass value in upper step, to it is selected it is s layers first in whole Services Composition solutions be ranked up, and
K Services Composition solution is as suboptimum service solution set before selecting.
It is provided in an embodiment of the present invention compared with calculating the problems such as complicated when consideration service quality correlation in the prior art
Method can solve the problems, such as the Services Composition of multiple target, can effectively handle tradeoff and folding between different service quality target
In；In addition, the embodiment of the present invention is layered by calculating the rough service quality of Services Composition solution, and corresponding selected by calculating
The correlation information of candidate service in layer, to obtain active service mass value, so as to handle real system with correlation
Services Composition situation, the suboptimal solution of real system can be quickly obtained, so as to improve solution efficiency.
Although being described in conjunction with the accompanying embodiments of the present invention, those skilled in the art can not depart from this hair
Various modifications and variations are made in the case of bright spirit and scope, such modifications and variations are each fallen within by appended claims
Within limited range.
Claims (6)
1. a kind of multiple target service combining method based on correlation, which is characterized in that including：
Candidate service set CiIn each candidate service include multiple attributes, if an optional candidate service and remaining candidate service
In at least one corresponding attribute of candidate service there is correlation, then corresponding candidate service has the service quality related
Property；If all without correlation, which does not have the corresponding attribute of a candidate service and every other candidate service
There is service quality correlation, and there is no the candidate service of service quality correlation to be stored in the first candidate service collection to match this
It closes
To the first candidate service setIn candidate service compared two-by-two with obtain winning candidate service with it is non-winning
Acquired winning candidate service is stored in winning candidate service set by candidate serviceAnd it is taken from the described first candidate
Business setDelete non-winning candidate service；
From the candidate service set CiIt is middle to delete corresponding non-winning candidate service to obtain the sub-services set to match
C′i；
By all sub-services set C 'iIt combines to form new Services Composition solution space S '；From the Services Composition solution space S '
It randomly selects multiple Services Composition solution formation and represents Xie JiheIt calculates and described represents Xie JiheIn each Services Composition solution Sp
Rough service quality value and be layered；
It is exhaustive it is selected it is s layer first in whole Services Composition solutions correlation information, to obtain the reality of the whole Services Composition solutions
Border service quality value；
Corresponding Services Composition solution is ranked up according to active service mass value, K Services Composition solution is to obtain before selection
Suboptimum Services Composition solution set.
2. multiple target service combining method according to claim 1, which is characterized in that the candidate service set CiIn it is every
A candidate service includes multiple attributes, if an optional candidate service is opposite at least one candidate service in remaining candidate service
The attribute answered has correlation, then corresponding candidate service has service quality correlation；If a candidate service is with owning
The corresponding attribute of other candidate services is all without correlation, then the candidate service does not have service quality correlation, and should
There is no the first candidate service set that the candidate service deposit of service quality correlation matchesThe step of in using following public
Formula judges whether each candidate service has service quality correlation：
In formula,Represent the candidate service for completing sub-services i,Represent candidate serviceR-th of attribute be
It is no that there is correlation；Represent candidate serviceWhether there is service quality correlation；" ∨ " represents sum operation.
3. multiple target service combining method according to claim 1, which is characterized in that the candidate service set CiIn it is every
A candidate service includes multiple attributes, if an optional candidate service is opposite at least one candidate service in remaining candidate service
The attribute answered has correlation, then corresponding candidate service has service quality correlation；If a candidate service is with owning
The corresponding attribute of other candidate services is all without correlation, then the candidate service does not have service quality correlation, and should
There is no the first candidate service set that the candidate service deposit of service quality correlation matchesThe step of after, further include：
Calculate each first candidate service setIn each candidate service Grade values, according to Grade values to described first wait
Select set of serviceMiddle whole candidate service carries out ascending sort.
4. multiple target service combining method according to claim 1, which is characterized in that described from the candidate service set
CiIt is middle to delete corresponding non-winning candidate service to obtain the sub-services set C ' to matchiThe step of according to equation below
Obtain sub-services set C 'i：
In formula, C 'iFor sub-services set, CiFor candidate service set,For winning candidate service set,It is waited for first
Select set of service.
5. multiple target service combining method according to claim 1, which is characterized in that described by whole sub-services set C 'i
Services Composition solution space S ' is obtained using equation below in the step of combination is to form new Services Composition solution space S '：
S '=C '1×C′2×...×C′m
In formula, C 'iRepresent sub-services set, i=1,2,3 ..., m, symbol "×" represents cartesian product.
6. multiple target service combining method according to claim 1, which is characterized in that described from Services Composition solution sky
Between multiple Services Composition solutions formation randomly selected in S ' represent Xie JiheIt calculates and described represents Xie JiheIn each service group
Close solution SpRough service quality value and the step of being layered include：
Choose the middle any two Services Composition solution S of Services Composition solution space S 'piAnd SpjCompared two-by-two, if Services Composition
Solve SpiWinning Services Composition solution Spj, by Services Composition solution SpjIt is added to the Services Composition solution SpiQueueIn, and will clothes
Business combination solution SpiAdd in the Services Composition solution SpjQueueIn；
DefinitionUtilize LiRepresent i-th layer of Services Composition solution set；Since first layer i=1, initially
ChangeWhenWhen, it finds allServices Composition solution Spj, and by the SpjAdd in Li
In, then find queueIn all Services Composition solutionFrom each queueMiddle deletion Services Composition solution Spj, then
By Services Composition solutionIt is deleted from RemainingSet；
It repeats the above process, untilQ layers of Services Composition are shared so as to obtain Services Composition solution space S '
Solution；
Wherein, queueBe it is all can be with winning Services Composition solution SpServices Composition solution set,It is all SpWinning solution
Set.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101808109A (en) * | 2009-10-20 | 2010-08-18 | 清华大学 | Model conversion and formalization verification method of semantic Web service combination |
| CN103207912A (en) * | 2013-04-15 | 2013-07-17 | 武汉理工大学 | Method and device for intelligent service resource combination recommendation based on attribute multilevel association |
| CN104090957A (en) * | 2014-03-10 | 2014-10-08 | 中国科学院软件研究所 | Heterogeneous network interactive visualization method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7730182B2 (en) * | 2003-08-25 | 2010-06-01 | Microsoft Corporation | System and method for integrating management of components of a resource |
-
2015
- 2015-08-13 CN CN201510497795.6A patent/CN105208076B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101808109A (en) * | 2009-10-20 | 2010-08-18 | 清华大学 | Model conversion and formalization verification method of semantic Web service combination |
| CN103207912A (en) * | 2013-04-15 | 2013-07-17 | 武汉理工大学 | Method and device for intelligent service resource combination recommendation based on attribute multilevel association |
| CN104090957A (en) * | 2014-03-10 | 2014-10-08 | 中国科学院软件研究所 | Heterogeneous network interactive visualization method |
Non-Patent Citations (3)
| Title |
|---|
| A Partial Selection Methodology for Efficient QoS-Aware Service Composition;Ying Chen, Jiwei Huang, Chuang Lin, Jie Hu;《IEEE TRANSACTIONS ON SERVICES COMPUTING》;20150630;第8卷(第3期);全文 * |
| Partial Selection: An Efficient Approach for QoS-AwareWeb Service Composition;Ying Chen, Jiwei Huang, Chuang Lin;《2014 IEEE International Conference on Web Services》;20140702;全文 * |
| 计算机网络服务质量优化方法研究综述;林闯，李寅，万剑雄;《计算机学报》;20110131;第34卷(第1期);全文 * |
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