Data Mining in Grid Computing Environments by Werner Dubitzky

By Werner Dubitzky

Dependent round 11 foreign genuine existence case stories and together with contributions from prime specialists within the box this groundbreaking e-book explores the necessity for the grid-enabling of information mining purposes and offers a accomplished learn of the expertise, ideas and administration talents essential to create them. This ebook offers a simultaneous layout blueprint, consumer consultant, and examine schedule for present and destiny advancements and may attract a huge viewers; from builders and clients of information mining and grid know-how, to complicated undergraduate and postgraduate scholars drawn to this box.

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Also the grid provides a framework whereby a great number of services can be dynamically located, balanced and managed, so that applications are always guaranteed to be securely executed, according to the principles of on-demand computing. The grid community has adopted the Open Grid Services Architecture (OGSA) as an implementation of the SOA model within the grid context. In OGSA every resource is represented as a Web service that conforms to a set of conventions and supports standard interfaces.

To realize this logic, the EMS follows a two-step approach: it initially models an abstract execution plan that in a second step is resolved into a concrete execution plan. 2 shows the architecture of the Knowledge Grid. A client application that wants to submit a knowledge discovery computation to the Knowledge Grid does not need to interact with all of these services, but just with a few of them. Inside each group, in fact, there are two layers of services: high-level services and core-level services.

Corsaro, eds, ‘OTM Workshops’, Vol. 3292 of Lecture Notes in Computer Science, Springer, pp. 111–122. , McCourt, D. and Dubitzky, W. (2004), A service-centric perspective for data mining in complex problem solving environments, in H. R. Arabnia and J. Ni, eds, ‘Proceedings of International Conference on Parallel and Distributed Processing Techniques and Applications’, Vol. 2, pp. 780–787. , Kindermann, J. and Dubitzky, W. (2008), ‘Grid-enabling data mining applications with DataMiningGrid: An architectural perspective’, Future Generation Computer Systems 24, 259–279.

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