This paper combines semantic web technology with business modeling and yields semantic business model that is semantically described in terms of roles and relationships. The semantic business model can be used to disc...This paper combines semantic web technology with business modeling and yields semantic business model that is semantically described in terms of roles and relationships. The semantic business model can be used to discover grid services by means of automation tools. The gap between business goals and grid services is bridged by role relationships and compositions of them, so that the virtual organization evolution is supported effectively. Semantic business model can support virtual organization validation at design stage rather than at run-time stage. The designers can animate their business model and make initial assessment of what interactions should occur between roles and in which order. The users can verify whether the grid service compositions satisfy business goals.展开更多
Fundamentally, semantic grid database is about bringing globally distributed databases together in order to coordinate resource sharing and problem solving in which information is given well-defined meaning, and DartG...Fundamentally, semantic grid database is about bringing globally distributed databases together in order to coordinate resource sharing and problem solving in which information is given well-defined meaning, and DartGrid II is the implemented database gird system whose goal is to provide a semantic solution for integrating database resources on the Web. Although many algorithms have been proposed for optimizing query-processing in order to minimize costs and/or response time, associated with obtaining the answer to query in a distributed database system, database grid query optimization problem is fundamentally different from traditional distributed query optimization. These differences are shown to be the consequences of autonomy and heterogeneity of database nodes in database grid. Therefore, more challenges have arisen for query optimization in database grid than traditional distributed database. Following this observation, the design of a query optimizer in DartGrid II is presented, and a heuristic, dynamic and parallel query optimization approach to processing query in database grid is proposed. A set of semantic tools supporting relational database integration and semantic-based information browsing has also been implemented to realize the above vision.展开更多
基金Supported bythe National Basic Research Programof China (973 Program) (1999032710)
文摘This paper combines semantic web technology with business modeling and yields semantic business model that is semantically described in terms of roles and relationships. The semantic business model can be used to discover grid services by means of automation tools. The gap between business goals and grid services is bridged by role relationships and compositions of them, so that the virtual organization evolution is supported effectively. Semantic business model can support virtual organization validation at design stage rather than at run-time stage. The designers can animate their business model and make initial assessment of what interactions should occur between roles and in which order. The users can verify whether the grid service compositions satisfy business goals.
文摘Fundamentally, semantic grid database is about bringing globally distributed databases together in order to coordinate resource sharing and problem solving in which information is given well-defined meaning, and DartGrid II is the implemented database gird system whose goal is to provide a semantic solution for integrating database resources on the Web. Although many algorithms have been proposed for optimizing query-processing in order to minimize costs and/or response time, associated with obtaining the answer to query in a distributed database system, database grid query optimization problem is fundamentally different from traditional distributed query optimization. These differences are shown to be the consequences of autonomy and heterogeneity of database nodes in database grid. Therefore, more challenges have arisen for query optimization in database grid than traditional distributed database. Following this observation, the design of a query optimizer in DartGrid II is presented, and a heuristic, dynamic and parallel query optimization approach to processing query in database grid is proposed. A set of semantic tools supporting relational database integration and semantic-based information browsing has also been implemented to realize the above vision.
