Download PDF by WERNER DUBITZKY: Data mining techniques in grid computing environments

By WERNER DUBITZKY

ISBN-10: 047051258X

ISBN-13: 9780470512586

Facts MINING concepts IN GRID COMPUTING ENVIRONMENTS-Wiley-WERNER DUBITZKY-2014-EDN-1

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Net/ 8 DATA MINING MEETS GRID COMPUTING: TIME TO DANCE? r Open technology. A grid should use of open protocols and standards. r High quality of service. A grid provides high quality of service in terms of performance, availability and security. Grid solutions are specifically designed to be adaptable and scalable and may involve a large number of machines. Unlike many cluster and Internet computing solutions, a grid should be able to cope with unexpected failures or loss of resources. Commonly used systems (such as clusters) can only grow up to a certain point without significant performance losses.

This trend will result soon in an ecosystem of pervasive applications and services that professionals and end users can exploit everywhere. A long-term perspective can be envisioned where a collection of services and applications will be accessed and used as public utilities, as water, gas and electricity are used today. 0 facilities, Data Mining Techniques in Grid Computing Environments © 2008 John Wiley & Sons, Ltd. Edited by Werner Dubitzky 18 DATA ANALYSIS SERVICES IN THE KNOWLEDGE GRID mashup tools and decentralized programming models.

It manages metadata describing Knowledge Grid resources. Such resources comprise hosts, repositories of data to be mined, tools and algorithms used to extract, analyse and manipulate data, knowledge models obtained as results of mining processes. Such information is stored in a local repository, the Knowledge Metadata Repository (KMR). The KDS exports the publishResource, searchResource and downloadResource operations. As previously noticed, they are invoked by the high-level services DAS or TAAS (to perform operations on data sets or tools respectively).

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Data mining techniques in grid computing environments by WERNER DUBITZKY


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