Produktbild: Optimized Cloud Based Scheduling

Optimized Cloud Based Scheduling

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Studies in Computational Intelligence 759 – Data, Semantics and Cloud Computing

ISBN: 3319732129
ISBN 13: 9783319732121
Autor: Tan, Rong Kun Jason/Leong, John A/Sidhu, Amandeep S
Verlag: Springer Verlag GmbH
Umfang: xiii, 99 S., 33 s/w Illustr., 99 p. 33 illus.
Erscheinungsdatum: 05.03.2018
Auflage: 1/2019
Produktform: Gebunden/Hardback
Einband: Gebunden

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.

Artikelnummer: 3178969 Kategorie:

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