Articoli correlati a Optimized Cloud Based Scheduling: 759
- EditoreSpringer-Nature New York Inc
- Data di pubblicazione2018
- ISBN 10 3319732129
- ISBN 13 9783319732121
- RilegaturaCopertina rigida
- Numero di pagine99
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Optimized Cloud Based Scheduling (Studies in Computational Intelligence) by Tan, Rong Kun Jason, Leong, John A., Sidhu, Amandeep S. [Hardcover ]
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Descrizione libro Hardcover. Condizione: new. Codice articolo 9783319732121
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Optimized Cloud Based Scheduling (Studies in Computational Intelligence, 759) [Hardcover] Tan, Rong Kun Jason; Leong, John A. and Sidhu, Amandeep S.
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ISBN 10: 3319732129
ISBN 13: 9783319732121
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Descrizione libro Condizione: new. Codice articolo 85a3da3ec2ff38b7fd2057959caf6e65
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Optimized Cloud Based Scheduling (Studies in Computational Intelligence, 759)
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Descrizione libro Condizione: New. Book is in NEW condition. Codice articolo 3319732129-2-1
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Descrizione libro Condizione: New. Codice articolo ABLIING23Mar3113020104385
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Descrizione libro Hardcover. Condizione: Brand New. 99 pages. 9.25x6.25x0.50 inches. In Stock. Codice articolo __3319732129
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Descrizione libro Condizione: New. New! This book is in the same immaculate condition as when it was published. Codice articolo 353-3319732129-new
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Optimized Cloud Based Scheduling
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Descrizione libro Condizione: New. PRINT ON DEMAND Book; New; Fast Shipping from the UK. No. book. Codice articolo ria9783319732121_lsuk
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Optimized Cloud Based Scheduling
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Berlin Springer International Publishing Springer Mrz 2018
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ISBN 13: 9783319732121
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Descrizione libro Buch. 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. 99 pp. Englisch. Codice articolo 9783319732121
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Optimized Cloud Based Scheduling
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Springer, Berlin, Springer International Publishing, Springer
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ISBN 10: 3319732129
ISBN 13: 9783319732121
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Descrizione libro Buch. 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 9783319732121
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Optimized Cloud Based Scheduling
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Descrizione libro Gebunden. 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 196762098
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