基于本体的服务发现与组合方法研究
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摘要
本文通过对Web服务的服务行为与用户预期的一致性、服务评价的多属性关系、Web服务之间协作上下文的研究，提出了基于本体的服务发现与组合方法，该方法能够通过服务的统一描述、发现与组合，更有效的管理和共享信息并快速构建应用。
首先提出了服务行为模型，该模型形式化的构造了Web服务的服务行为描述，建立了Web服务的服务行为和用户预期之间的一致性计算规则，设计了服务发现原型并对服务行为的目标和任务进行了匹配。服务行为模型从用户的功能需求和主观预期两个方面能够提高服务发现的准确性。
其次针对服务发现的结果中存在着Web服务的处理能力空闲、服务请求过载和功能失效的问题，提出了多属性关系模型的解决方案并形式化的构造了Web服务的服务评价描述，进而构建了多属性关系计算规则并且证明了多属性关系的一致性。多属性关系模型从Web服务的性能方面进一步的优化了服务发现的结果。
最后提出了协作上下文模型，该模型依据业务流程的上下文场景，形式化的构造了Web服务的服务协作描述并构建了协作上下文的计算规则，进而通过计算业务流程中Web服务节点和节点之间关联的上下文，建立了Web服务之间的协作上下文并设计了服务组合原型。协作上下文模型提高了Web服务的可共享性和服务组合的个性化程度。
基于本体的服务发现与组合方法能够提高用户对服务发现的准确性、服务的可用性、服务的共享性及服务组合的个性化选择的满意度。在MSIDP和KaM平台的实验结果表明，该方法能够满足用户的服务需求。
Because of increasing users and individuation of requirements, there are some newchallenges that how to utilize the Internet resources just as information, business, andknowledge and so on effectively, build applications rapidly with a uniform way of servicedescription, discovery and composition, and find a new way of service providing instead ofprogramming again and again. We call it "one-time implementation and multi-times usage",which has become one of the research hotspots in the area of service computing. In this thesis,we proposed an approach of ontology-based service discovery and composition, which isbased on our works on aspects of behavior, evaluation and collaboration of the web services.On the basis of formalized ontology representation, we built three models named ServiceBehavior, Multi-Attribute Relationship and Collaboration Context, to provide a uniformconstruction of service description. We use the Service Behavior model and Multi-AttributeRelationship model to discover web services with a matching and selection between user'sexpectation and performance evaluation, and then use the Collaboration Context model tocompose web services as a service composition for a business process.
Firstly, we designed Service Description Ontology to describe and build web serviceuniformly. The descriptions of service behavior, service evaluation and service collaborationof a web service have been constructed in the Service Description Ontology with a formalizedontology representation. We defined a concept model and a relationship model betweendifferent concepts of the service behavior, service evaluation and service collaboration, andbuilt a conceptual description of the relationships between business function and functionalrequirement, between the actual service behavior and the expected service behavior, and therelationships of an interactive collaboration among different web services. Then we designedan attribute model of these concepts and relationships, and defined an attributes’ computingmodels as executive computing rules for service discovery on demand, service selection onevaluation and service composition on context. We built the ontology axioms of servicebehavior, service evaluation and service collaboration in the construction of ServiceDescription Ontology with the computing model, and designed a service generation prototypewhich creates an OWL-S instance of Service Description Ontology to publish a web service.We do some experiments on the platform named MSIDP (Model Driven based ServiceOriented Integration and Development Platform). We built MSIDP Service Registration andSearch Tool for business objects with this service generation prototype. The result shows thatthe service generation prototype help MSIDP users to create instances of Service DescriptionOntology for describing the services provided by different types of application resources, thenit generated web services of MSIDP business objects, and offered service units for users to share. The Service Description Ontology is on the basis of building the Service Behaviormodel, the Multi-Attribute Relationship model and the Collaboration Context model, andprovides machine-accessed service description uniformly for service discovery andcomposition further.
Secondly, on the basis of the description and generation of a web service, we proposed abehavior centric model named Service Behavior model to build service discovery andmatching. We designed an interactive process among web services, service discoveryprototype and users with the Service Behavior model, built a service discovery process whichis from requirement analysis to result evaluation. The requirement analysis is extracted fromthe service request of a user to present his intention and task. The result evaluation is ameasurement that whether user is satisfied with the service discovery. We designed a servicediscovery prototype based on the Service Behavior model. The users’ intentions and tasks areextracted with an existing Key-phrases Extraction Algorithm and matched with the concept’sattribute of the actual service behavior that has been constructed in the Service DescriptionOntology. We defined the computing rules to prove consistency between the axioms of servicebehavior and service evaluation in the Service Description Ontology. According to thecomputing rules, we designed a service discovery and matching process for the servicediscovery prototype, and experimented on the platform of Knowledge advantage Machine(KaM). We built a discovery Agent for KaM by using the service discovery prototype. Weused the Service Behavior Model to build a service discovery process among the KaM users,KaM Knowledge Objects (named JANs) and KaM discovery Agent. The experimental resultshows that the Service Behavior model promotes the accuracy of the service discovery result,provides a solution of service discovery on demand.
Thirdly, to solve the service evaluation problem of capability idle, request overload andfunctional invalidation of a web service on the runtime, we proposed a Multi-AttributeRelationship model, which is used to analyze and evaluate the actual service behaviorprovided by the web service in the service discovery result, and optimize the result to filterunqualified web services. On the basis of the description of service evaluation, which isconstructed in the Service Description Ontology, we designed an attribute’s computing modelfor each service evaluation concept, made analysis on the scenes of capability idle, requestoverload and functional invalidation and explored the relationships among different serviceevaluation concepts. We defined the computing rules for these concepts’ attributes in theMulti-Attribute Relationship model, computed the consistency of these attributes, and provedthe relationships between consistency and inconsistency of these attributes. We designed aservice evaluation and selection process in the service discovery prototpye based on theMulti-Attribute Relationship model, built service evaluation to optimize the service discoveryresults on the platform of MSIDP and KaM. The exprimental result shows that theMulti-Attribute Relationship model promotes the user’s satification to service discovery resultobviously, so it provides a new way of service selection in accordance with evaluation.
Fourthly, on the basis of description, discovery and evaluation of web services, weproposed a Collaboration Context model, which is used to build a context among differentfunction nodes in a business process through scenario analysis on a special applicationdomain or on different domains across, and then we defined an interactive process betweendifferent web services for service composition on the basis of the description of servicecollaboration in the Service Description Ontology and the collaboration scenario in a businessprocess. We built executive computing rules of service composition using the axioms ofservice collaboration in the Service Description Ontology, and designed a service compositionprototype to execute service composition on the collaboration context which was associatedon different web services in a business process. This proposed Collaboration Context modeland service composition prototype can be used to provide a theoretical model for modelingbusiness processes on the platform of MSIDP for different domains such as electronic power,telecom and government affairs. We built a linking Agent on the platform of KaM by usingthe service composition prototype. The linking Agent executes to link the discovered JANsinto a personal knowledge network or a group knowledge network according to theircollaboration contexts, which were constructed for the scenario of knowledge managementand sharing. It provides a more effective way of personal knowledge management andpromotes knowledge sharing and reusing for knowledge workers. The experimental resultshows that the Collaboration Context model promotes the sharing and reusing ability of webservices, and enhances individuality for service composition.
Our works is on the basis of the models and methods of ontology, web service in the areaof service computing. We used our proposed methods and prototypes to provide a solution forservice description, service discovery and service composition in a uniform way. The methodhas been experimented and tested on the platform of MSIDP and KaM. The results show thatthe Service Description Ontology can provide a useful way to describe service behavior,service evaluation and service collaboration for web services, and then our proposed modelsof Service Behavior, Multi-Attribute Relationship and Collaboration Context can be designedfor building the prototypes, which provide a solution of service discovery and composition forusers to manage and share information more effective and building applications rapidly. Theexperimental results and examples demonstrate the rationality and validity of our proposedmodel and method.
首先提出了服务行为模型，该模型形式化的构造了Web服务的服务行为描述，建立了Web服务的服务行为和用户预期之间的一致性计算规则，设计了服务发现原型并对服务行为的目标和任务进行了匹配。服务行为模型从用户的功能需求和主观预期两个方面能够提高服务发现的准确性。
其次针对服务发现的结果中存在着Web服务的处理能力空闲、服务请求过载和功能失效的问题，提出了多属性关系模型的解决方案并形式化的构造了Web服务的服务评价描述，进而构建了多属性关系计算规则并且证明了多属性关系的一致性。多属性关系模型从Web服务的性能方面进一步的优化了服务发现的结果。
最后提出了协作上下文模型，该模型依据业务流程的上下文场景，形式化的构造了Web服务的服务协作描述并构建了协作上下文的计算规则，进而通过计算业务流程中Web服务节点和节点之间关联的上下文，建立了Web服务之间的协作上下文并设计了服务组合原型。协作上下文模型提高了Web服务的可共享性和服务组合的个性化程度。
基于本体的服务发现与组合方法能够提高用户对服务发现的准确性、服务的可用性、服务的共享性及服务组合的个性化选择的满意度。在MSIDP和KaM平台的实验结果表明，该方法能够满足用户的服务需求。
Because of increasing users and individuation of requirements, there are some newchallenges that how to utilize the Internet resources just as information, business, andknowledge and so on effectively, build applications rapidly with a uniform way of servicedescription, discovery and composition, and find a new way of service providing instead ofprogramming again and again. We call it "one-time implementation and multi-times usage",which has become one of the research hotspots in the area of service computing. In this thesis,we proposed an approach of ontology-based service discovery and composition, which isbased on our works on aspects of behavior, evaluation and collaboration of the web services.On the basis of formalized ontology representation, we built three models named ServiceBehavior, Multi-Attribute Relationship and Collaboration Context, to provide a uniformconstruction of service description. We use the Service Behavior model and Multi-AttributeRelationship model to discover web services with a matching and selection between user'sexpectation and performance evaluation, and then use the Collaboration Context model tocompose web services as a service composition for a business process.
Firstly, we designed Service Description Ontology to describe and build web serviceuniformly. The descriptions of service behavior, service evaluation and service collaborationof a web service have been constructed in the Service Description Ontology with a formalizedontology representation. We defined a concept model and a relationship model betweendifferent concepts of the service behavior, service evaluation and service collaboration, andbuilt a conceptual description of the relationships between business function and functionalrequirement, between the actual service behavior and the expected service behavior, and therelationships of an interactive collaboration among different web services. Then we designedan attribute model of these concepts and relationships, and defined an attributes’ computingmodels as executive computing rules for service discovery on demand, service selection onevaluation and service composition on context. We built the ontology axioms of servicebehavior, service evaluation and service collaboration in the construction of ServiceDescription Ontology with the computing model, and designed a service generation prototypewhich creates an OWL-S instance of Service Description Ontology to publish a web service.We do some experiments on the platform named MSIDP (Model Driven based ServiceOriented Integration and Development Platform). We built MSIDP Service Registration andSearch Tool for business objects with this service generation prototype. The result shows thatthe service generation prototype help MSIDP users to create instances of Service DescriptionOntology for describing the services provided by different types of application resources, thenit generated web services of MSIDP business objects, and offered service units for users to share. The Service Description Ontology is on the basis of building the Service Behaviormodel, the Multi-Attribute Relationship model and the Collaboration Context model, andprovides machine-accessed service description uniformly for service discovery andcomposition further.
Secondly, on the basis of the description and generation of a web service, we proposed abehavior centric model named Service Behavior model to build service discovery andmatching. We designed an interactive process among web services, service discoveryprototype and users with the Service Behavior model, built a service discovery process whichis from requirement analysis to result evaluation. The requirement analysis is extracted fromthe service request of a user to present his intention and task. The result evaluation is ameasurement that whether user is satisfied with the service discovery. We designed a servicediscovery prototype based on the Service Behavior model. The users’ intentions and tasks areextracted with an existing Key-phrases Extraction Algorithm and matched with the concept’sattribute of the actual service behavior that has been constructed in the Service DescriptionOntology. We defined the computing rules to prove consistency between the axioms of servicebehavior and service evaluation in the Service Description Ontology. According to thecomputing rules, we designed a service discovery and matching process for the servicediscovery prototype, and experimented on the platform of Knowledge advantage Machine(KaM). We built a discovery Agent for KaM by using the service discovery prototype. Weused the Service Behavior Model to build a service discovery process among the KaM users,KaM Knowledge Objects (named JANs) and KaM discovery Agent. The experimental resultshows that the Service Behavior model promotes the accuracy of the service discovery result,provides a solution of service discovery on demand.
Thirdly, to solve the service evaluation problem of capability idle, request overload andfunctional invalidation of a web service on the runtime, we proposed a Multi-AttributeRelationship model, which is used to analyze and evaluate the actual service behaviorprovided by the web service in the service discovery result, and optimize the result to filterunqualified web services. On the basis of the description of service evaluation, which isconstructed in the Service Description Ontology, we designed an attribute’s computing modelfor each service evaluation concept, made analysis on the scenes of capability idle, requestoverload and functional invalidation and explored the relationships among different serviceevaluation concepts. We defined the computing rules for these concepts’ attributes in theMulti-Attribute Relationship model, computed the consistency of these attributes, and provedthe relationships between consistency and inconsistency of these attributes. We designed aservice evaluation and selection process in the service discovery prototpye based on theMulti-Attribute Relationship model, built service evaluation to optimize the service discoveryresults on the platform of MSIDP and KaM. The exprimental result shows that theMulti-Attribute Relationship model promotes the user’s satification to service discovery resultobviously, so it provides a new way of service selection in accordance with evaluation.
Fourthly, on the basis of description, discovery and evaluation of web services, weproposed a Collaboration Context model, which is used to build a context among differentfunction nodes in a business process through scenario analysis on a special applicationdomain or on different domains across, and then we defined an interactive process betweendifferent web services for service composition on the basis of the description of servicecollaboration in the Service Description Ontology and the collaboration scenario in a businessprocess. We built executive computing rules of service composition using the axioms ofservice collaboration in the Service Description Ontology, and designed a service compositionprototype to execute service composition on the collaboration context which was associatedon different web services in a business process. This proposed Collaboration Context modeland service composition prototype can be used to provide a theoretical model for modelingbusiness processes on the platform of MSIDP for different domains such as electronic power,telecom and government affairs. We built a linking Agent on the platform of KaM by usingthe service composition prototype. The linking Agent executes to link the discovered JANsinto a personal knowledge network or a group knowledge network according to theircollaboration contexts, which were constructed for the scenario of knowledge managementand sharing. It provides a more effective way of personal knowledge management andpromotes knowledge sharing and reusing for knowledge workers. The experimental resultshows that the Collaboration Context model promotes the sharing and reusing ability of webservices, and enhances individuality for service composition.
Our works is on the basis of the models and methods of ontology, web service in the areaof service computing. We used our proposed methods and prototypes to provide a solution forservice description, service discovery and service composition in a uniform way. The methodhas been experimented and tested on the platform of MSIDP and KaM. The results show thatthe Service Description Ontology can provide a useful way to describe service behavior,service evaluation and service collaboration for web services, and then our proposed modelsof Service Behavior, Multi-Attribute Relationship and Collaboration Context can be designedfor building the prototypes, which provide a solution of service discovery and composition forusers to manage and share information more effective and building applications rapidly. Theexperimental results and examples demonstrate the rationality and validity of our proposedmodel and method.
引文
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