9783030103330: Optimized Cloud Based Scheduling
Couverture souple
ISBN 10 : 3030103331 ISBN 13 : 9783030103330
Editeur : Springer, 2019

Synopsis

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.

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Éditeur
Springer
Date d'édition
2019
Langue
anglais
ISBN 10 
3030103331
ISBN 13 
9783030103330
Reliure
Broché
Nombre de pages
116
Coordonnées du fabricant
Springer Nature Customer Service Center GmbH
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Heidelberg
69115
Allemagne

Autres éditions populaires du même titre

9783319732121: Optimized Cloud Based Scheduling

Edition présentée

ISBN 10 :  3319732129 ISBN 13 :  9783319732121
Editeur : Springer International Publishin..., 2018
Couverture rigide