CN102521659A - Method for judging incidence relation between services orienting to cloud manufacturing - Google Patents
Method for judging incidence relation between services orienting to cloud manufacturing Download PDFInfo
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Abstract
The invention relates to a method for judging an incidence relation between services orienting to cloud manufacturing. Specifically, in order to more accurately construct and optimize the service combination in a cloud manufacturing mode, the invention relates to a method for designing effective incidence relation judging algorithms to find the incidence relation between two services. A combined incidence relation judging algorithm is mainly used for judging whether two services can be combined with each other according to a front-order and post-order relation; an entity incidence relation judging algorithm is mainly used for judging whether the two services have an entity cooperating or competitive relation by searching for an attribute-value pair of services in a service tree; and a statistic cooperating incidence relation judging algorithm is mainly used for judging whether the two services are bound to cooperatively execute a task by extracting the historic log information of the services. The method has the advantages that the judging method is simple, the applicability and the operability are high and the expandability is excellent.
Description
Technical field
The present invention relates to a kind of towards incidence relation decision method between the service of cloud manufacturing; It is a kind of black box theory that is similar to; Only need import each information on services that candidate service is concentrated; Just can find out the incidence relation that is had between any two services automatically through the decision algorithm of incidence relation between service, with structure and the preferable methods that is applied to Services Combination.This invention belongs to distributed manufacturing system information integration technical field.
Background technology
Though networking manufacturing has had bigger development; But no matter still be that operation mode also exists certain problem technically; As lack the centralized management and the operation of service; Do not solve well and make dynamically sharing and smart allocation and the security in network service, data transmission etc. of resource, these problems have seriously hindered applying of networked manufacturing.To the bottleneck problem that runs in current manufacturing informatization development and the application process; In conjunction with theory and new technologies such as cloud computing, Internet of Things, service-oriented technology, high-performance calculation technology; Brave academician of uncle Li Chinese Academy of Engineering and team thereof have proposed a kind of networking based on the cloud computing service mode and have made new model---cloud manufacturing (Cloud manufacturing; CMfg), and all obtained approval widely in academia and industry member.The cloud manufacturing is a kind of service-oriented, efficient low-consume and makes new model based on the network-enabled intelligent of knowledge, is extension and the change that existing network manufacturing and service technology are carried out.It is with all kinds of manufacturing resources and manufacturing capacity is virtual, serviceization; Constitute and make resource and manufacturing capacity pond; And the intelligent management and the operation of unifying, concentrate; Realize intellectuality, all-win, generalization and share efficiently and collaborative, through network and cloud manufacturing system for make lifecycle process provide can obtain at any time, the service of use, safe and reliable, high-quality cheapness as required.
In virtual enterprise application process based on the web service; Service is considered to most important component units; Mutual through ISP (Service Provider), service requester (Service Requester) and three basic roles of service register center (Service Registry); Accomplish service encapsulation, activity such as issue, search, make up, bind and call, and then realize concrete application.But the service in the registration center is generally keeping less granularity, and promptly the form with simple relatively single service of function or atomic service occurs.When service requester proposed the complex task demand, single service often can not be satisfied user's demand, just need several services be made up, and formed composite services with better function to realize the purpose of service value-adding, i.e. Services Combination.To pass through task of the incompatible completion of service groups; On the one hand be that a series of services are configured to the execution route of Services Combination according to certain flow process and rule, want from a large amount of services that same function is provided, to select one group of service (being the preferred of Services Combination) on the other hand with favorable service quality (QoS), higher user satisfaction.
Yet; It between the actual network service separate existence; Between them often ubiquity interactional incidence relation, and the existence meeting of these incidence relations exerts an influence to the overall process of Services Combination, especially whole Services Combination quality (QoS) played key effect.But, make service centre at cloud and registered a large amount of services, how to find out the incidence relation that is had in these services, promptly the decision problem of incidence relation between the service is a critical difficult problem.
Also do not have at present much can reference research work be used to solve the decision problem of incidence relation between two services; Existing great majority research major side overweights the excavation framework of incidence relation between service and the ins and outs of mining process, does not also have a Feasibility Study for what how to design that suitable algorithm judges incidence relation between two services.In view of the deficiency in the existing research,, provide that the decision method of incidence relation is problem demanding prompt solution in the present Network Manufacturing Technology between service for the decision problem of incidence relation between the service of solving.
Summary of the invention
The present invention relates to a kind of towards incidence relation decision method between the Services Combination of cloud manufacturing; Being a kind of need import each information on services that candidate service is concentrated; Just can find out the incidence relation that is had between any two services through the decision algorithm of incidence relation between service, with structure and the preferable methods that is applied to Services Combination.The decision algorithm of incidence relation capable of being combined is designed to mainly judge that two services whether can be according to preorder, postorder composition of relations together, to realize the automatic structure in Services Combination path; The decision algorithm of entity associated relation mainly is designed for judges whether two services have the relation of entity cooperation or competition; The decision algorithm of statistics cooperation incidence relation mainly is to be designed for to judge whether two services often are bundled in and cooperate together to execute the task; With the influence that exists of discovery entity associated relation and statistics cooperation incidence relation, thereby better realize the preferred of Services Combination scheme to the QoS of Services Combination.
A kind of towards incidence relation decision method between the service of cloud manufacturing; Be a kind of to three kinds of different incidence relations between service; Through the decision algorithm of incidence relation between service, find out the method for the incidence relation that is had between two services, this method specifically may further comprise the steps:
Step 1) is treated two services of judgement, extracts respectively to can be used for incidence relation between follow-up service and judge the descriptor of required service and the history log information of executing the task.The descriptor of service partly need be extracted (the ontology web language for services with OWL-S; Web service ontology language) is the descriptor on basis, the functional descriptions information and QoS (quality of service, the service quality) descriptor of service.Wherein, the functional descriptions information of service is used for the judgement of incidence relation capable of being combined, is the descriptor on basis and the judgement that the QoS descriptor is used for the entity associated relation with OWL-S.The history log informational needs of service execution task extracts service name, the task-set of execution, and the response task start time, deadline and the situation of finally finishing the work are for use in the judgement of statistics cooperation incidence relation.
Therefore the process of the Interface Matching between step 2) incidence relation capable of being combined between two services is actually and serves according to the functional descriptions of service, becomes two services functionality information structurings to be judged the form of weighting bipartite graph.Bipartite graph is such figure; Can classify two and gather X and Y in its summit, all limits are associated in two summits, and just what a belongs to set X; Another belongs to set Y, and resulting figure just is the weighting bipartite graph after giving certain weight for each limit of bipartite graph.When the function information that utilizes the weighting bipartite graph to represent to serve, the output set of two services and input set respectively as two vertex sets of weighting bipartite graph, are calculated the weight of the similarity of element in two set as the limit of weighting bipartite graph.Find the solution the optimum matching of two vertex sets of weighting bipartite graph.If this optimum matching exists, calculate the similarity of two vertex sets again, if the similarity value judges then that greater than the property threshold value capable of being combined that the user sets two services have incidence relation capable of being combined.
Step 3) will be served is that the rule that descriptor and the QoS descriptor on basis described standard according to " attribute-value to " is converted into the form of setting of serving with OWL-S; To the conditional attribute-value that qos value relied on of a certain service to the attribute-value of another service to shining upon, be used to the QoS property value of the service of searching except that default value.If these two services one of them or both all can find the QoS property value except that default value, judge that then two services have entity associated and concern.
Step 4) user selectes the phase of history time, extracts the history log information of two service execution tasks during this period of time, calculates two service bindings through the mode that adds up and cooperates the number of times of executing the task together.If the number of times of two service cooperations reaches the threshold value of " regular ", judge that then two services are to have statistics cooperation incidence relation.
Beneficial effect of the present invention is following:
1, the present invention is directed to the existing research that incidence relation between service is judged and mainly be confined to find framework and ins and outs aspect; Provide the decision algorithm of incidence relation between three kinds of services in detail, can effectively find the incidence relation that is had between any two services.
2, the present invention has designed the decision method of incidence relation capable of being combined, can judge effectively that two services whether can be according to certain logical order composition of relations together, thereby can realize the structure in Services Combination path.
3, the present invention has designed the decision method of entity associated relation and statistics cooperation incidence relation, in view of when service has these two kinds of incidence relations to the influence of Services Combination QoS, realization Services Combination that can be more accurate, perfect preferably.
Description of drawings
Fig. 1 is the process synoptic diagram of judging towards incidence relation between the service of cloud manufacturing;
Fig. 2 is the decision flowchart of incidence relation capable of being combined;
Fig. 3 is the decision flowchart of entity associated relation;
Fig. 4 is the decision flowchart of statistics cooperation incidence relation.
Embodiment
Below in conjunction with accompanying drawing the present invention is described in further detail.
The present invention mainly comprises a kind of towards incidence relation decision method between the service of cloud manufacturing.After user's request of offering the challenge, can form the candidate service collection that meets this mission requirements to this task.Be similar to the black box theory; Only need extract the relevant information of concentrated any two services of candidate service; Just can find out the incidence relation that is had between these two services automatically through the decision algorithm of incidence relation between service; Thereby the structure that is applied to Services Combination is with preferred, and its process is referring to Fig. 1.The judgement of incidence relation has related generally to three kinds of incidence relations between service, i.e. the judgement of incidence relation capable of being combined, the judgement of the judgement of entity associated relation and statistics cooperation incidence relation.Concrete performing step is following:
The first step is treated two services of judgement, extracts their descriptor and the history log information of executing the task.
At first, extract the descriptor part of service, comprise with OWL-S being the descriptor on basis, the input and output descriptor and the QoS descriptor of service.
Secondly, choose the time period of service execution task, extract the history log information of two service execution tasks during this period of time; The title that comprises two services; The task-set of carrying out, response task start time, the situation of finishing the work the time and finally finishing the work.
In second step, judge whether two services have incidence relation capable of being combined, and determination flow is seen Fig. 2.
At first, construct the weighting bipartite graph according to the output and the input information of service.Promptly respectively the output set of two services is gathered two vertex sets as the weighting bipartite graph with input; As long as each element during output set is gathered with input has certain similarity on notion, attribute, property value; Then between them, connect a limit, calculate the weight of the similarity of element in two set as the limit of weighting bipartite graph.
Secondly, judge whether output set and the element number of importing in the set equate.If it is unequal; Then in the few set of element number, add some virtual elements; Make the element number in two set equate, and weight of increase is 0 limit between each element in new each element that adds and the relative set, thereby obtains new weighting bipartite graph.
Once more, utilize Kuhn-Munkres (KM) algorithm, obtain the optimum matching of weighting bipartite graph through the complete coupling of authority of finding the solution subgraph of equal value.
At last; According to the optimum matching of trying to achieve; Calculate the similarity of output set and input set; If this similarity value is greater than property threshold value capable of being combined, then these two services have incidence relation capable of being combined, i.e. exist the similarity of data logic that they can be combined between output of two services and the input set.
In the 3rd step, judge whether two services have the entity associated relation, promptly judge to be in the relation that whether has cooperation or competition between the ISP in the alliance, and determination flow is seen Fig. 3.
At first, with service be that the rule that descriptor and the QoS descriptor on basis described standard according to " attribute-value to " is converted into the form of setting of serving with OWL-S,
Secondly, the service of fixing one of them service tree, each the conditional attribute node that qos value relied in the service tree is sought corresponding with it identical attribute node in another service tree for this reason.If whole conditional attribute node that qos value relied on all can find corresponding with it identical attribute node in another service tree, then successively recurrence verifies whether the property value node of identical attribute node equates.Judge with this whether whole conditional attribute-value that qos value relied on is to all being satisfied.
Once more, the fixing service of another one service tree, identical method judges whether whole conditional attribute-value that qos value relies on is to all being satisfied.
At last, if these two services one of them or both all can find the QoS property value except that default value, judge that then two services have entity associated and concern.
The 4th step, judge whether two services have statistics cooperation incidence relation, promptly judge the often cooperation execution together of two or more services in the Services Combination, determination flow is seen Fig. 4.
At first, according to the time order and function order, search the situation of two service execution tasks successively.If two service execution identical task, and all run succeeded, then write down them and cooperated once together.
Secondly, carry out adding up of number of times successively, obtain in this period of history daily record of choosing two total degrees that service is cooperated together.
At last, if the total degree of two service cooperations reaches the threshold value of " regular ", judge that then two services have statistics cooperation incidence relation.
Claims (10)
1. incidence relation decision method between a service of making towards cloud; It is characterized in that: to three kinds of different incidence relations between service; Provide the formal description of incidence relation between service respectively; And utilize formal description to come the decision algorithm of incidence relation between design services, thereby find out the incidence relation that is had between two services; Specifically may further comprise the steps:
Step 1) is treated two services of judgement, extracts their descriptor and the history log information of executing the task respectively;
Step 2) function information in the descriptor of two services of step 1 is expressed as the form of weighting bipartite graph;
Step 3) is according to the function information of the weighting bipartite graph form that provides in the step 2, and the optimum matching of two vertex sets through finding the solution bipartite graph is judged the incidence relation capable of being combined between two services;
It serves as to describe the form of standard service tree that step 4) is separately converted to other descriptor except that function information in the descriptor of two services of step 1 with " attribute-value to ";
Step 5) through the right mapping of attribute-value between two service trees, is judged the entity associated relation between two services for the service tree of two services that provide in the step 4;
Step 6) is based on the history log information of two service execution tasks in the step 1, cooperates the number of times of executing the task through calculating two service bindings together, judges the statistics cooperation incidence relation between two services.
2. method according to claim 1 is characterized in that: the descriptor of the service that the needs described in the step 1 extract comprises: be the descriptor of the service on basis, the functional descriptions information and the QoS descriptor of service with OWL-S.
3. method according to claim 1; It is characterized in that: the history log information of the service execution task that the needs described in the step 1 extract comprises: service name, the task-set of execution, response task start time; Deadline, the situation of finally finishing the work.
4. method according to claim 1 is characterized in that: the function information of the service described in the step 2 comprises: the output information and the input information of two services to be judged.
5. method according to claim 1 is characterized in that: two set of the bipartite graph of weighting described in the step 3 are respectively: the output set of two services to be judged and input set.
6. method according to claim 1 is characterized in that: other descriptor except that function information described in the step 4 comprises: the descriptor and the QoS descriptor that with OWL-S are the service on basis.
7. method according to claim 1 is characterized in that: it serve as that the service of description standard is set that service described in the step 4 tree is meant with " attribute-value to ".
8. method according to claim 7; It is characterized in that: serve as that the rule of describing standard comprises with " attribute-value to " in the step 4: the service tree is by the base attribute node, base attribute value node, conditional attribute node; The conditional attribute value node, qos value node 5 category nodes are formed; Base attribute and base attribute value with first mark (zero) and second mark (●) expression service; When decision condition occurring, represent the attribute and the property value of condition respectively with the 3rd mark
and the 4th mark (◆); With the corresponding qos value of the 5th mark (■) expression; The corresponding one or more value nodes of each attribute node, the corresponding attribute node of each value node, attribute node and value node alternately occur; If between a plurality of value nodes of an attribute node be " with " perhaps " or " relation, then use " with-or the tree " represent; When a plurality of decision conditions need satisfy, then a plurality of conditions are placed on the branch in proper order, until arriving leaf node.
9. method according to claim 7; It is characterized in that: the right mapping of attribute-value was meant and is respectively a certain service tree between two services described in the step 5 were set, and it is right that the condition that qos value relied on during service is set for this reason in another service tree is sought the attribute-value that satisfies these conditions.
10. method according to claim 1 is characterized in that: the number of times described in the step 6 was meant in a period of time of user's appointment, two sums that add up of serving the number of tasks of institute's cooperation execution together and successful execution.
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| CN103001892A (en) * | 2012-12-12 | 2013-03-27 | 中国联合网络通信集团有限公司 | Network resource distribution method and system based on cloud computing |
| CN104301212A (en) * | 2014-09-26 | 2015-01-21 | 浙江工商大学 | Functional chain combination method |
| CN104519112A (en) * | 2014-04-09 | 2015-04-15 | 丹阳市天恒信息科技有限公司 | Intelligent selecting framework for staged cloud manufacturing services |
| CN105210103A (en) * | 2013-02-13 | 2015-12-30 | Op40后丁斯公司 | Distributed cloud services and uses thereof |
| CN109002965A (en) * | 2018-06-22 | 2018-12-14 | 南京邮电大学 | A kind of cloud manufacturing service cooperative level assessment system and application method |
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| CN103001892A (en) * | 2012-12-12 | 2013-03-27 | 中国联合网络通信集团有限公司 | Network resource distribution method and system based on cloud computing |
| CN105210103B (en) * | 2013-02-13 | 2020-02-18 | Op40后丁斯公司 | Distributed cloud services and uses thereof |
| CN105210103A (en) * | 2013-02-13 | 2015-12-30 | Op40后丁斯公司 | Distributed cloud services and uses thereof |
| CN104519112A (en) * | 2014-04-09 | 2015-04-15 | 丹阳市天恒信息科技有限公司 | Intelligent selecting framework for staged cloud manufacturing services |
| CN104301212A (en) * | 2014-09-26 | 2015-01-21 | 浙江工商大学 | Functional chain combination method |
| CN104301212B (en) * | 2014-09-26 | 2017-05-17 | 浙江工商大学 | Functional chain combination method |
| CN109002965A (en) * | 2018-06-22 | 2018-12-14 | 南京邮电大学 | A kind of cloud manufacturing service cooperative level assessment system and application method |
| WO2021027149A1 (en) * | 2019-08-14 | 2021-02-18 | 平安科技（深圳）有限公司 | Portrait similarity-based information retrieval recommendation method and device and storage medium |
| CN110661875A (en) * | 2019-09-29 | 2020-01-07 | 青岛科技大学 | Cloud manufacturing service cooperation similarity calculation method based on Word2Vec |
| CN110661875B (en) * | 2019-09-29 | 2022-02-25 | 青岛科技大学 | Cloud manufacturing service cooperation similarity calculation method based on Word2Vec |
| CN112883120A (en) * | 2019-11-29 | 2021-06-01 | 南京苏德创新科技有限公司 | Inter-service association relation judgment algorithm for realizing high sharing of manufacturing resources by utilizing information technology |
| CN113472565A (en) * | 2021-06-03 | 2021-10-01 | 北京闲徕互娱网络科技有限公司 | Method, device, equipment and computer readable medium for expanding server function |
| CN113472565B (en) * | 2021-06-03 | 2024-02-20 | 北京闲徕互娱网络科技有限公司 | Method, apparatus, device and computer readable medium for expanding server function |
| CN117171398A (en) * | 2023-11-01 | 2023-12-05 | 浙江大学高端装备研究院 | Method, device and equipment for constructing service tree of industrial Internet platform |
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Application publication date: 20120627 |