Enterprise systems are frequently built by combining a

number of discrete Web services together, a process termed

composition. There are a number of architectural configurations or distribution patterns, which express how a composed system is to be deployed. Previously, we presented a Model Driven Architecture using UML 2.0, which took existing service interfaces as its input and generated an executable Web service composition, guided by a distribution pattern model. In this paper, we propose using Web service semantic descriptions in addition to Web service interfaces, to assist in the semi-automatic generation of the distribution pattern model. Web services described using semantic languages, such as OWL-S, can be automatically assessed for compatibility and their input and output messages can be mapped to each other

Barrett, Ronan

Pahl, Claus

English

Enterprise systems are frequently built by combining a\ud
number of discrete Web services together, a process termed\ud
composition. There are a number of architectural configurations or distribution patterns, which express how a composed system is to be deployed. Previously, we presented a Model Driven Architecture using UML 2.0, which took existing service interfaces as its input and generated an executable Web service composition, guided by a distribution pattern model. In this paper, we propose using Web service semantic descriptions in addition to Web service interfaces, to assist in the semi-automatic generation of the distribution pattern model. Web services described using semantic languages, such as OWL-S, can be automatically assessed for compatibility and their input and output messages can be mapped to each other

Name not available

Semi-Automatic Distribution Pattern Modelingof Web Service Compositions using SemanticsRonan BarrettSchool of ComputingDublin City UniversityDublin 9, Irelandrbarrett@computing.dcu.ieClaus PahlSchool of ComputingDublin City UniversityDublin 9, Irelandcpahl@computing.dcu.ieAbstractEnterprise systems are frequently built by combining anumber of discrete Web services together, a process termedcomposition. There are a number of architectural configu-rations or distribution patterns, which express how a com-posed system is to be deployed. Previously, we presenteda Model Driven Architecture using UML 2.0, which tookexisting service interfaces as its input and generated an ex-ecutable Web service composition, guided by a distributionpattern model. In this paper, we propose using Web servicesemantic descriptions in addition to Web service interfaces,to assist in the semi-automatic generation of the distribu-tion pattern model. Web services described using semanticlanguages, such as OWL-S, can be automatically assessedfor compatibility and their input and output messages canbe mapped to each other.1. IntroductionEnterprise systems are often built by combining a num-ber of Web services together to realise some novel func-tionality. This practice of combining Web services togetheris termed composition. Web service composition is oftenad-hoc, where no architectural models are drawn, and con-siderable low level coding effort is required for realisation.Model Driven Architecture (MDA) is an emerging ap-proach for building software [5]. In MDA, the model is theprimary software artifact, and is used to generate the pro-gram code. Rich, well specified, high level models, oftendefined in the Unified Modeling Language (UML), allowfor the auto-generation of a fully executable system basedentirely on the model [4]. Web service compositions can bemodeled, using an MDA based approach, from a number ofaspects. In [13], service and workflow modeling aspects ofWeb service compositions are investigated. Service model-ing considers interfaces and their operations, while work-flow modeling considers control and data flows from oneWeb service to another. Our previous work [1], introducedan additional aspect, distribution pattern modeling, whichexpresses how the composed system is to be deployed us-ing UML. Two well known distribution patterns are cen-tralised and decentralised. Distribution patterns address aconsiderable shortcoming of fixed centralised coordinationidentified by Siren et al. [14].In this paper we introduce the use of Web service se-mantics to assist in the generation of a distribution patternmodel. This approach assumes that all the Web servicesto be composed, are semantically annotated using OWL-S, and have already been discovered by a system. Thesesemantics enable the automated matchmaking and subse-quent sequencing of the order in which the pre-selectedWeb services will be composed. They also enable the au-tomatic integration of inputs and outputs for each Web ser-vice. This automation effort, using semantics, reduces themanual modeling workload of the system architect.The paper is structured as follows: section two providesbackground material on our approach and the technologiesunderlying it; section three introduces our modeling andtransformation technique; section four investigates our toolimplementation; section five presents related work; finally,section six considers future work and concludes the paper.2. BackgroundOntologies are often used to define the vocabulary ofa domain. These definitions must be sharable, interoper-able and standards compliant to enable the expression ofmachine interpretable semantics. Creating an ontology isanalogous to domain modeling, where the different dis-crete components that make up a system are investigated.The Web Ontology Language (OWL), is a language forcapturing the conceptual data of a domain and their inter-relationships, for use in the description of resources [11].This technology enables the semantic description of Web re-sources such as Web pages and Web services. Semantic de-scriptions enable unambiguous, computer interpretable doc-umentation of resources. OWL-S is an ontology based onOWL which is used for defining the properties and capabil-ities of Web services [10].Distribution patterns express, using models, how a com-posed system is to be assembled and subsequently de-ployed. In MDA terms, distribution pattern models area form of platform-independent model (PIM), as the pat-terns are not tied to any specific implementation technol-ogy. These patterns are considered compositional chore-ographies, where only the message flow between services ismodeled. As such, a choreography can express how a sys-tem would be deployed. The workflow logic between theseservices are not modeled here, as there are many approachesto modeling the branch flows of such services [3, 6].There are three pattern categories, core patterns, auxil-iary patterns and complex patterns. Core patterns are thefundamental distribution patterns, most commonly encoun-tered in Web service compositions. Auxiliary patterns aredistribution patterns which by themselves cannot facilitateWeb service compositions, and are often used in conjunc-tion with core patterns to create complex patterns. Finally,complex patterns combine two or more core or auxiliarypatterns. Complex patterns often resolve fundamental prob-lems evident within core patterns. The patterns, organisedby category, are listed below.• Core patterns– Centralised Dedicated-Hub– Centralised Shared-Hub– Decentralised Dedicated-Peer– Decentralised Shared-Peer• Auxiliary patterns– Ring• Complex patterns– Hierarchical– Ring + Centralised– Centralised + Decentralised– Ring + DecentralisedUML & UML Profiles: Distribution patterns are mod-eled using a UML activity diagram in association with ournovel distribution pattern UML profile, DPLProfile. UMLis a standards based graphical language for the modeling ofsoftware systems [12]. Activity diagrams illustrate the se-quential flow of actions within a system, capturing actionsand their results [4].These diagrams consist of actions, which are the ba-sic unit of behaviour within an activity, and control flows,which illustrate the transitions through the system. Activ-ity partitions, also known as swim lanes, are often used togroup actions together. Rich models, such as those neces-sary for modeling distribution patterns, can make use of aparticular type of UML action to model Web service oper-ations defined in a WSDL interface. These actions, calledCallBehaviorActions, model process invocations along withthe flow of control through the system, using ControlFlowconnectors. CallBehaviorActions have an additional mod-eling constructs called pins. There are two types of pins,InputPins and OutputPins, which map directly to the partsof the WSDL message parts going into and out of a WSDLoperation. ObjectFlow connectors are used to connect pinstogether. Figure 1 illustrates the use of an activity dia-gram used to model the decentralised distribution pattern.The UML pins and associated connectors have been omit-ted from the diagram for clarity.DecentralisedPeer Peer Peer PeerUML ActionsUML Control FlowsUML PartitionsFigure 1. Decentralised distribution patternUML profiles are a standard extension mechanism ofUML [5]. Profiles define stereotypes and tagged values thatextend a number of UML constructs. Each time one of thesederived constructs is used in a model it may have attributesassigned to its tagged values. Our distribution pattern pro-file, called DPLProfile, is outlined in detail in [2].3. Modeling and Transformation TechniqueOur semi-automated distribution pattern modeling andsubsequent executable system generation, comprises foursteps, each is illustrated in Figure 2.Step 1 - From Interface To Model: The first step in-volves taking a number of Web service interfaces, WSDLdocuments, as input to a generator. These interfaces rep-WSDLUML 2.0 ModelUML 2.0ModelStep # 1 Step # 2ActorDistribution PatternStep # 4Generator DefinitionExecutable SystemGeneratorUML 2.0ModelUML 2.0ModelStep # 3Semantic MatchingEngineUML 2.0ModelOWL-SExecutableSystemFigure 2. Overview of modeling approachresent the services which are to be composed. These in-terfaces are transformed automatically, using the UML 2.0model generator, into a UML 2.0 activity diagram. Finally,our novel distribution pattern profile, DPLProfile, is auto-matically applied to the model by the generator. The soft-ware architect does not need to manipulate the model in anyway at this step. The output from the UML 2.0 generatorcan be seen in Figure 3. The figure illustrates that the DPL-Profile, UML profile, has been applied to the model.CoreBankinggetAccoutName getRiskAssessment getCreditCardRiskManagement CreditCard<<DPLParticipant>> <<DPLParticipant>> <<DPLParticipant>>Figure 3. Output from the model generatorStep 2 - Distribution Pattern Definition: The UMLmodel produced in step 1, requires additional modeling.The architect must select a distribution pattern and then as-sign appropriate values for the tagged values of the distribu-tion pattern profile, which was applied automatically to themodel in the previous step. The complete list of tagged val-ues are outlined in [2]. Values that must be assigned includeWeb service namespaces, participant roles, choice of collab-oration language and distribution pattern type. Previouslyat this step, the architect had to connect CallBehaviorAc-tions to one another, and also connect up UML InputPinsand OutputPins together. However, this requirement is nownegated by the use of semantics to automate the connectionsin the following step.Step 3 - Semantic Matching and Integration: We as-sume all of the Web services to be composed, are seman-tically annotated using OWL-S. The semantic documentsfor each service are passed to the semantic matching en-gine for processing. Each service must have an atomic pro-cess model describing, using an ontology, the message inputand output parts. OWL-S atomic process models are analo-gous to WSDL operations. These semantic descriptions en-able the automated sequencing of actions and connection ofCallBehaviorActions to one another, in our distribution pat-tern model, using UML ControlFlow connectors. Servicesare matched together based on their level of compatibility.Each service is checked against every other participant ser-vice to assess if their process models are compatible. Com-patibility here is defined as one participant having outputmessage part(s) which match the input message part(s) re-quirements of another participant. If a sufficiently similarmatch is found, a UML ControlFlow connector is createdbetween the two compatible services in the model. Sub-sequently the inputs and output parts of these matched ser-vices can be mapped. This integration results in the connec-tion of UML InputPins and OutputPins in the model, usingUML ObjectFlows connectors, so data can flow through thecomposition. In some cases, additional pins may be addedautomatically to the output of CallBehaviorActions, to meetdata input requirements of other services. Existing servicesare wrapped to support the new connections. Without se-mantic annotation this entire step would have to be com-pleted manually by the software architect. At this stage themodel is complete and fully expresses the distribution pat-tern selected by the software architect. Sample output fromthe matching engine can be seen in Figure 4.CoreBankinggetAccoutName getRiskAssessment getCreditCardRiskManagement CreditCard<<DPLParticipant>> <<DPLParticipant>> <<DPLParticipant>><<DPLMessage>>accoutNumber<<DPLMessage>><<DPLMessage>><<DPLMessage>><<DPLMessage>><<DPLMessage>><<DPLMessage>><<DPLMessage>>getCreditCardReturnisRiskaccoutNamegetRiskAssessmentReturnaccountNameaccoutNamegetAccountNameReturnFigure 4. Semantic matching engine outputStep 4 - Model to Executable System: The executablesystem generator takes the finished model and generates allthe interaction logic required to realise the distribution pat-tern. Interaction logic documents describe the message flowbetween the participants in the distribution pattern as wellas input and output variable mappings. The generator alsocreates interfaces which expose the new interaction logicprocessing capability as a wrapper to the existing Web ser-vice functionality of the participant. A deployment descrip-tor document describing each participants is also created.Once deployed, these documents will realise the Web ser-vice composition, driven by the distribution pattern mod-eled by the software architect, see [2] for more details.4. ImplementationTOPMAN (TOPology MANager) is our solution for dis-tribution pattern modeling using UML 2.0 and subsequentWeb service composition generation. The tool implementa-tion is illustrated in Figure 5.UML 2.0 Model GeneratorWSDLModel as XMIProfile as XMIManipulateActorWS-BPEL(s)WSDL(s)Executable System GeneratorXSLT/DOMXSLT/DOMRSAUML2OWL-SSemantic MatchingEngineJENAModel as XMIProfile as XMIFigure 5. Overview of TOPMAN toolA non-semantically enabled version of our tool is de-scribed in [2]. The only modification made to the tool hereis the use of the Jena semantic web framework to assist inthe generation of the distribution model. The tool assessesthe compatibility of the participant Web services input andoutput messages, based on their OWL-S atomic processmodels [8].5. Related WorkUsing semantics to assist in the composition of Web ser-vices is considered by Siren et al. [14]. Here semanticallyannotated services can be combined, semi-automaticallybased on their input and other non-functional requirements.Two additional systems devised by Timm et al. and Grønmoet al. use MDA based techniques to assist in the creation ofontologies for semantically enriching services which are tobe composed [7, 9]. However, these systems do not con-sider the distribution pattern of the resultant composition,resulting in a fixed centralised distribution pattern.6. ConclusionMechanisms to assist in the generation of Web service-based compositions are desirable. We have combined exist-ing techniques based on architectural modeling and pattern-based development, with the emerging areas of MDA andsemantic descriptions. Our contribution is the novel appli-cation of semantics to distribution pattern modeling. Webservices described using semantic languages, such as OWL-S, can be automatically assessed for compatibility, and theirinput and output messages can be mapped to each other.Semantics enable the semi-automatic generation of a distri-bution pattern model, which is subsequently used to guidethe generation of an executable system.7. AcknowledgmentsThe authors would like to thank the Irish Research Coun-cil for Science, Engineering and Technology IRCSET.References[1] R. Barrett and C. Pahl. Semi-Automatic Distribution PatternModeling of Web Service Compositions using Semantics.In Proc. Tenth IEEE International EDOC Conference, HongKong, China, October 2006.[2] R. Barrett, C. Pahl, L. Patcas, and J. Murphy. Model DrivenDistribution Pattern Design for Dynamic Web Service Com-positions. In Proc. Sixth International Conference on WebEngineering, Palo Alto, California, July 2006.[3] D. Skogan and R. Grønmo and I. Solheim. Web servicecomposition in uml. In Proc. 8th International IEEE Enter-prise Distributed Object Computing Conference, pages 47–57, Monterey, California, September 2004.[4] H. E. Eriksson, M. Penker, B. Lyons, and D. Fado. UML 2Toolkit. Wiley, 2003.[5] D. S. Frankel. Model Driven Architecture: Applying MDAto Enterprise Computing. Wiley, 2004.[6] T. Gardner. UML Modeling of Automated Business Pro-cesses with a mapping to BPEL4WS. In Proc. First Eu-ropean Workshop on Object Orientation and Web Service(EOOWS), Darmstadt, Germany, July 2003.[7] R. Grønmo and M. Jaeger. Model-driven semantic web ser-vice composition. In Proc. 12th Asia-Pacific Software Engi-neering Conference (APSEC 2005), Taipei, Taiwan, 2005.[8] Jena. A semantic web framework for java, 2006.[9] J.T.E. Timm and G.C. Gannod. A model-driven approachfor specifying semantic web services. In Proc. InternationalConference on Web Services, Orlando, Florida, USA, 2005.[10] D. Martin, M. Burstein, O. Lassila, M. Paolucci, T. Payne,and S. McIlraith. Describing Web Services using OWL-Sand WSDL. DAML-S Coalition working document., 2003.[11] D. McGuinness and F. van Harmelen. OWL Web Ontol-ogy Language Overview. W3C Recommendation 10 Febru-ary 2004., 2004.[12] OMG. Unified Modeling Language (UML), version 2.0.Technical report, OMG, 2003.[13] R. Grønmo and I. Solheim. Towards modeling web servicecomposition in uml. In Proc. 2nd International Workshopon Web Services: Modeling, Architecture and Infrastructure(WSMAI-2004), pages 72–86, Porto, Portugal, April 2004.[14] E. Sirin, J. Hendler, and B. Parsia. Semi-automatic compo-sition of web services using semantic descriptions. In Proc.Workshop on Web Services: Modeling, Architecture and In-frastructure (WSMAI), pages 17–24, Angers, France, 2003.

Semi-automatic distribution pattern modeling of web service compositions using semantics

Enterprise systems are frequently built by combining a number of discrete Web services together, a process termed composition. There are a number of architectural configurations or distribution patterns, which express how a composed system is to be deployed. Previously, we presented a Model Driven Architecture using UML 2.0, which took existing service interfaces as its input and generated an executable Web service composition, guided by a distribution pattern model. In this paper, we propose using Web service semantic descriptions in addition to Web service interfaces, to assist in the semi-automatic generation of the distribution pattern model. Web services described using semantic languages, such as OWL-S, can be automatically assessed for compatibility and their input and output messages can be mapped to each other. 1

Ronan Barrett

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Semi-Automatic Distribution Pattern Modeling of Web Service Compositions using Semantics

Enterprise systems are frequently built by combining a
number of discrete Web services together, a process termed
composition. There are a number of architectural configurations or distribution patterns, which express how a composed system is to be deployed. Previously, we presented a Model Driven Architecture using UML 2.0, which took existing service interfaces as its input and generated an executable Web service composition, guided by a distribution pattern model. In this paper, we propose using Web service semantic descriptions in addition to Web service interfaces, to assist in the semi-automatic generation of the distribution pattern model. Web services described using semantic languages, such as OWL-S, can be automatically assessed for compatibility and their input and output messages can be mapped to each other

Irish Universities

DCU Online Research Access Service

A model-driven approach for specifying semantic web services.

A semantic web framework for java,

Describing Web Services using OWL-S and WSDL. DAML-S Coalition working document.,

F r a n k e l . Model Driven Architecture: Applying MDA to Enterprise Computing.

Model Driven Distribution Pattern Design for Dynamic Web Service Compositions. In

Model-driven semantic web service composition.

Semi-automatic composition of web services using semantic descriptions.

Semi-Automatic Distribution Pattern Modeling of Web Service Compositions using Semantics. In

Towards modeling web service composition in uml.

UML Modeling of Automated Business Processes with a mapping to BPEL4WS. In

Uniﬁed Modeling Language (UML), version 2.0.

Web service composition in uml.

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Semi-automatic distribution pattern modeling of web service compositions using semantics

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