scalable distributed data warehouse von awoyelu iyabo (9 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware -This study attempted to develop a data grid model for a distributed data warehouse using response time, throughput and bandwidth as major characteristics of the system. The model was simulated and evaluated. This was with a view to introducing the concepts of Service-Oriented Architecture (SOA), Web services and semantics into the development of distributed data warehouse. A distributed data warehouse model was formulated using SOA and Web services concept in order to implement the scalable data-grid model. This architecture was modelled as a Binary Tree model. The model was designed using Unified Modeling Language. An interface for the integration of the various data sources to the model was developed in Java Persistence API. The model Web services were created using Java and published using Web Services Description Language (WSDL). The system was simulated using Java programming language. The simulation parameters used in the design were number of clients (ranging from 100 to 1000), response time (measured in milliseconds), throughput and bandwidth consumption (measured in kilobits per seconds).Books on Demand GmbH, Überseering 33, 22297 Hamburg 180 pp. Englisch.

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Paperback. Zustand: Brand New. 180 pages. 8.66x5.91x0.41 inches. In Stock.

Paperback. Zustand: Brand New. 180 pages. 8.66x5.91x0.41 inches. In Stock.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Awoyelu Iyabo OlukemiDr. Iyabo Olukemi Awoyelu holds a BSc in Computer Science with Economics, a MSc in Computer Science and a PhD in Computer Science at the Department of Computer Science & Engineering, Obafemi Awolowo University, I.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This study attempted to develop a data grid model for a distributed data warehouse using response time, throughput and bandwidth as major characteristics of the system. The model was simulated and evaluated. This was with a view to introducing the concepts of Service-Oriented Architecture (SOA), Web services and semantics into the development of distributed data warehouse. A distributed data warehouse model was formulated using SOA and Web services concept in order to implement the scalable data-grid model. This architecture was modelled as a Binary Tree model. The model was designed using Unified Modeling Language. An interface for the integration of the various data sources to the model was developed in Java Persistence API. The model Web services were created using Java and published using Web Services Description Language (WSDL). The system was simulated using Java programming language. The simulation parameters used in the design were number of clients (ranging from 100 to 1000), response time (measured in milliseconds), throughput and bandwidth consumption (measured in kilobits per seconds). 180 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This study attempted to develop a data grid model for a distributed data warehouse using response time, throughput and bandwidth as major characteristics of the system. The model was simulated and evaluated. This was with a view to introducing the concepts of Service-Oriented Architecture (SOA), Web services and semantics into the development of distributed data warehouse. A distributed data warehouse model was formulated using SOA and Web services concept in order to implement the scalable data-grid model. This architecture was modelled as a Binary Tree model. The model was designed using Unified Modeling Language. An interface for the integration of the various data sources to the model was developed in Java Persistence API. The model Web services were created using Java and published using Web Services Description Language (WSDL). The system was simulated using Java programming language. The simulation parameters used in the design were number of clients (ranging from 100 to 1000), response time (measured in milliseconds), throughput and bandwidth consumption (measured in kilobits per seconds).

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