Descrizione libro Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such as bioinformatics, astronomy, high-energy physics, and Earth science are generating a tremendous flow of data, commonly known as big data. In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability. However, there are numerous problems associated with the current service provisioning and allocation models, such as inefficient scheduling algorithms, overloaded memory overheads, excessive node delays and improper error handling of tasks, all of which need to be addressed to enhance the performance of big data analytics. 116 pp. Englisch. Codice articolo 9783030103330

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Optimized Cloud Based Scheduling (Studies in Computational Intelligence)

Tan, Rong Kun Jason/ Sidhu, Amandeep S./ Leong, John A.

Editore: Springer (2019)

ISBN 10: 3030103331 ISBN 13: 9783030103330

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Descrizione libro Paperback. Condizione: Brand New. reprint edition. 116 pages. 9.25x6.10x0.43 inches. In Stock. Codice articolo x-3030103331

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Optimized Cloud Based Scheduling

Rong Kun Jason Tan

Editore: Springer International Publishing (2019)

ISBN 10: 3030103331 ISBN 13: 9783030103330

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AHA-BUCH GmbH
(Einbeck, Germania)

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Descrizione libro Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such as bioinformatics, astronomy, high-energy physics, and Earth science are generating a tremendous flow of data, commonly known as big data. In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability. However, there are numerous problems associated with the current service provisioning and allocation models, such as inefficient scheduling algorithms, overloaded memory overheads, excessive node delays and improper error handling of tasks, all of which need to be addressed to enhance the performance of big data analytics. Codice articolo 9783030103330

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Optimized Cloud Based Scheduling

Rong Kun Jason Tan|John A. Leong|Amandeep S. Sidhu

Editore: Springer International Publishing (2019)

ISBN 10: 3030103331 ISBN 13: 9783030103330

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moluna
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Descrizione libro Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents an improved design for service provisioning and allocation models in a hybrid cloud environmentProposes approaches for addressing scheduling and performance issues in big data analytics Showcases new algorithms for hybrid cl. Codice articolo 273276641

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