Transactions are an important part of most enterprise computing systems. Sometimes they are supported by DBMS and sometimes by transaction monitors. In either case, they are part of the platform used by application developers. A platform independent model of enterprise computing must abstract away transactions and provide platform independent ways of describing them. This paper shows how "unit of work" can be used to support platform independent descriptions of enterprise computing systems that use transactions. Our paper is in the context of the OMG's model driven architecture so we provide a UML profile for describing unit of work. We have developed a tool, Mercator, that can translate platform independent models using the unit of work profile to platform dependent models using transactions. When added to our previous work on persistence, this provides a general way of handling transparent transaction management in MDA.
{"title":"Transaction support using unit of work modeling in the context of MDA","authors":"Weerasak Witthawaskul, Ralph E. Johnson","doi":"10.1109/EDOC.2005.32","DOIUrl":"https://doi.org/10.1109/EDOC.2005.32","url":null,"abstract":"Transactions are an important part of most enterprise computing systems. Sometimes they are supported by DBMS and sometimes by transaction monitors. In either case, they are part of the platform used by application developers. A platform independent model of enterprise computing must abstract away transactions and provide platform independent ways of describing them. This paper shows how \"unit of work\" can be used to support platform independent descriptions of enterprise computing systems that use transactions. Our paper is in the context of the OMG's model driven architecture so we provide a UML profile for describing unit of work. We have developed a tool, Mercator, that can translate platform independent models using the unit of work profile to platform dependent models using transactions. When added to our previous work on persistence, this provides a general way of handling transparent transaction management in MDA.","PeriodicalId":106387,"journal":{"name":"Ninth IEEE International EDOC Enterprise Computing Conference (EDOC'05)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126791910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper proposes a more formalized definition of UML 2.0 activity diagram semantics. A subset of activity diagram constructs relevant for business process modeling is considered. The semantics definition is based on the original token flow methodology, but a more constructive approach is used. The activity diagram virtual machine is defined by means of a metamodel, with operations defined by a mix of pseudocode and OCL pre- and postconditions. A formal procedure is described which builds the virtual machine for any activity diagram. The relatively complicated original token movement rules in control nodes and edges are combined into paths from an action to action. A new approach is the use of different (push and pull) engines, which move tokens along the paths. Pull engines are used for paths containing join nodes, where the movement of several tokens must be coordinated. The proposed virtual machine approach makes the activity semantics definition more transparent where the token movement can be easily traced. However, the main benefit of the approach is the possibility to use the defined virtual machine as a basis for UML activity diagram based workflow or simulation engine.
{"title":"Semantics of UML 2.0 activity diagram for business modeling by means of virtual machine","authors":"V. Vitolins, A. Kalnins","doi":"10.1109/EDOC.2005.29","DOIUrl":"https://doi.org/10.1109/EDOC.2005.29","url":null,"abstract":"The paper proposes a more formalized definition of UML 2.0 activity diagram semantics. A subset of activity diagram constructs relevant for business process modeling is considered. The semantics definition is based on the original token flow methodology, but a more constructive approach is used. The activity diagram virtual machine is defined by means of a metamodel, with operations defined by a mix of pseudocode and OCL pre- and postconditions. A formal procedure is described which builds the virtual machine for any activity diagram. The relatively complicated original token movement rules in control nodes and edges are combined into paths from an action to action. A new approach is the use of different (push and pull) engines, which move tokens along the paths. Pull engines are used for paths containing join nodes, where the movement of several tokens must be coordinated. The proposed virtual machine approach makes the activity semantics definition more transparent where the token movement can be easily traced. However, the main benefit of the approach is the possibility to use the defined virtual machine as a basis for UML activity diagram based workflow or simulation engine.","PeriodicalId":106387,"journal":{"name":"Ninth IEEE International EDOC Enterprise Computing Conference (EDOC'05)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131568947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Web service selection phase is usually driven only by functional requirements. Non functional requirements, such as quality of service, should be negotiated by the service consumer and the service provider during service invocation in order to produce a contract to manage service provisioning and to monitor the actual fulfilment of negotiated SLAs. In this paper, an automated approach to Web service QoS negotiation is proposed; the negotiation is performed by a negotiation broker to which both the consumer and the service provider can notify their preferences on QoS attributes and negotiation strategies by specifying the value of a relatively small set of parameters. When consumers are unable to specify such parameters or do not trust the service provisioning platform, negotiation can also be automated only on the provider side, allowing the direct interaction of the service consumer with the broker. An architecture to support the above mentioned functionalities is also described.
{"title":"An architecture for flexible Web service QoS negotiation","authors":"M. Comuzzi, B. Pernici","doi":"10.1109/EDOC.2005.4","DOIUrl":"https://doi.org/10.1109/EDOC.2005.4","url":null,"abstract":"The Web service selection phase is usually driven only by functional requirements. Non functional requirements, such as quality of service, should be negotiated by the service consumer and the service provider during service invocation in order to produce a contract to manage service provisioning and to monitor the actual fulfilment of negotiated SLAs. In this paper, an automated approach to Web service QoS negotiation is proposed; the negotiation is performed by a negotiation broker to which both the consumer and the service provider can notify their preferences on QoS attributes and negotiation strategies by specifying the value of a relatively small set of parameters. When consumers are unable to specify such parameters or do not trust the service provisioning platform, negotiation can also be automated only on the provider side, allowing the direct interaction of the service consumer with the broker. An architecture to support the above mentioned functionalities is also described.","PeriodicalId":106387,"journal":{"name":"Ninth IEEE International EDOC Enterprise Computing Conference (EDOC'05)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116874063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A large enterprise generates millions of purchase orders (PO) each year buying various types of goods and services. Each PO has a cost associated with it. This cost comprises multiple elements including the price of the good or service, the shipping and handling of the purchase, and the overhead in initiating, generating, tracking, and managing the PO. To reduce the cost of doing business, it is imperative to reduce the total cost of POs in enterprise e-procurement in an automated fashion. One way to reduce enterprise procurement cost is to aggregate demands so that the total cost of a bunch of POs is reduced by a better price, a lowered shipping and handling fee, and a reduced overhead. The cost of goods and services often depend on several factors including volume, timing, and other business objectives. This paper describes an intelligent aggregation approach for automatically aggregating demands to reduce procurement cost in enterprise e-procurement. Our aggregation approach for e-procurement consists of an information model for representing products (goods or services) and representing purchase orders for such products, a corporate agreement system, a negotiation engine, and a rule-based aggregation engine. The information model is based on an extension of the classic entity-relationship model. The extension enables association of rules and constraints with and among attributes. These rules and constraints must be satisfied during PO aggregation and thus ensure the aggregate PO to be consistent with original individual POs. A rule-based aggregation engine examines POs as they arrive and interact with other decision aids to determine whether aggregation of a particular bunch of POs makes any business sense. Aggregation can happen in two business scenarios, one for POs constrained by existing corporate agreements and another for POs to be refined by online negotiations. The aggregation engine interacts with a corporate agreement system to obtain supplier policies in the first scenario. For the second scenario, it interacts with the negotiation engine to obtain supplier's policies during iterations of the negotiation process. Relevant policies are those that define product pricing, shipping and handing, and post-sale sendees as well as warranties and returns. Examples are given to demonstrate how automated intelligent aggregation of purchases is performed and how it reduces cost in enterprise e-procurement.
{"title":"Intelligent aggregation of purchase orders in e-procurement","authors":"Guijun Wang, Stephen Miller","doi":"10.1109/EDOC.2005.19","DOIUrl":"https://doi.org/10.1109/EDOC.2005.19","url":null,"abstract":"A large enterprise generates millions of purchase orders (PO) each year buying various types of goods and services. Each PO has a cost associated with it. This cost comprises multiple elements including the price of the good or service, the shipping and handling of the purchase, and the overhead in initiating, generating, tracking, and managing the PO. To reduce the cost of doing business, it is imperative to reduce the total cost of POs in enterprise e-procurement in an automated fashion. One way to reduce enterprise procurement cost is to aggregate demands so that the total cost of a bunch of POs is reduced by a better price, a lowered shipping and handling fee, and a reduced overhead. The cost of goods and services often depend on several factors including volume, timing, and other business objectives. This paper describes an intelligent aggregation approach for automatically aggregating demands to reduce procurement cost in enterprise e-procurement. Our aggregation approach for e-procurement consists of an information model for representing products (goods or services) and representing purchase orders for such products, a corporate agreement system, a negotiation engine, and a rule-based aggregation engine. The information model is based on an extension of the classic entity-relationship model. The extension enables association of rules and constraints with and among attributes. These rules and constraints must be satisfied during PO aggregation and thus ensure the aggregate PO to be consistent with original individual POs. A rule-based aggregation engine examines POs as they arrive and interact with other decision aids to determine whether aggregation of a particular bunch of POs makes any business sense. Aggregation can happen in two business scenarios, one for POs constrained by existing corporate agreements and another for POs to be refined by online negotiations. The aggregation engine interacts with a corporate agreement system to obtain supplier policies in the first scenario. For the second scenario, it interacts with the negotiation engine to obtain supplier's policies during iterations of the negotiation process. Relevant policies are those that define product pricing, shipping and handing, and post-sale sendees as well as warranties and returns. Examples are given to demonstrate how automated intelligent aggregation of purchases is performed and how it reduces cost in enterprise e-procurement.","PeriodicalId":106387,"journal":{"name":"Ninth IEEE International EDOC Enterprise Computing Conference (EDOC'05)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121998598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
OWL-S is an instance of the Web Ontology Language (OWL) that is used to describe and specify semantic Web services. While OWL-S provides a promising mechanism for specification, publication, discovery, integration, and access, the learning curve can be high. Current practices in Web services tend to focus on lightweight specification using automated tools that generate WSDL descriptions. One of the advantages of OWL-S is its flexibility in allowing the creation of many groundings or bindings for a single semantic Web service. In this paper, we propose an approach for generating groundings for a semantic Web service and demonstrate how the use of lightweight interactive tools facilitates creation of groundings for a semantic Web service.
{"title":"An interactive approach for specifying OWL-S groundings","authors":"G. Gannod, Raynette J. Brodie, J. Timm","doi":"10.1109/EDOC.2005.7","DOIUrl":"https://doi.org/10.1109/EDOC.2005.7","url":null,"abstract":"OWL-S is an instance of the Web Ontology Language (OWL) that is used to describe and specify semantic Web services. While OWL-S provides a promising mechanism for specification, publication, discovery, integration, and access, the learning curve can be high. Current practices in Web services tend to focus on lightweight specification using automated tools that generate WSDL descriptions. One of the advantages of OWL-S is its flexibility in allowing the creation of many groundings or bindings for a single semantic Web service. In this paper, we propose an approach for generating groundings for a semantic Web service and demonstrate how the use of lightweight interactive tools facilitates creation of groundings for a semantic Web service.","PeriodicalId":106387,"journal":{"name":"Ninth IEEE International EDOC Enterprise Computing Conference (EDOC'05)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126351978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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