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Optimized Cloud Based Scheduling by Tan Rong (29 results)
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Optimized Cloud Based Scheduling.
Book 274 of 538: Studies in Computational IntelligenceSeller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Association Member: GIAQ ILAB VDA
Seller rating 4 out of 5 stars
25 cm. XIII, 99 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Studies in Computational Intelligence. Volume 759. Sprache: Englisch.
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Condition: As New. Unread book in perfect condition.
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Optimized Cloud Based Scheduling (Studies in Computational Intelligence, 759)
Book 274 of 538: Studies in Computational IntelligenceSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 70.54
US$ 16.15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Optimized Cloud Based Scheduling (Data, Semantics and Cloud Computing)
Book 274 of 538: Studies in Computational IntelligenceSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 70.54
US$ 16.15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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US$ 65.80
US$ 20.88 shipping
Ships from United Kingdom to U.S.A.Quantity: 10 available
Add to basketPF. Condition: New.
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Condition: New. pp. 116.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 70.01
US$ 20.22 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceSeller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceSeller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 77.10
US$ 20.22 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Optimized Cloud Based Scheduling (Studies in Computational Intelligence)
Book 274 of 538: Studies in Computational IntelligenceUS$ 88.43
US$ 13.48 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketPaperback. Condition: Brand New. reprint edition. 116 pages. 9.25x6.10x0.43 inches. In Stock.
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US$ 90.69
US$ 13.48 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketHardcover. Condition: Brand New. 99 pages. 9.25x6.25x0.50 inches. In Stock.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceLanguage: English
Published by Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 3030103331 ISBN 13: 9783030103330
Taschenbuch. Condition: 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.
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Taschenbuch. Condition: Neu. Optimized Cloud Based Scheduling | Rong Kun Jason Tan (u. a.) | Taschenbuch | xiii | Englisch | 2019 | Springer | EAN 9783030103330 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceLanguage: English
Published by Springer, Berlin, Springer, 2018
ISBN 10: 3319732129 ISBN 13: 9783319732121
Buch. Condition: 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.
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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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Condition: new. Questo è un articolo print on demand.
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Condition: new. Questo è un articolo print on demand.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceLanguage: English
Published by Springer International Publishing Feb 2019, 2019
ISBN 10: 3030103331 ISBN 13: 9783030103330
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceLanguage: English
Published by Berlin Springer International Publishing Springer Mrz 2018, 2018
ISBN 10: 3319732129 ISBN 13: 9783319732121
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: 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.
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Condition: New. Print on Demand pp. 116.
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Condition: New. PRINT ON DEMAND pp. 116.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceLanguage: English
Published by Springer International Publishing, 2019
ISBN 10: 3030103331 ISBN 13: 9783030103330
Condition: 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.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceLanguage: English
Published by Springer International Publishing, 2018
ISBN 10: 3319732129 ISBN 13: 9783319732121
Gebunden. Condition: 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.
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Optimized Cloud Based Scheduling
Book 274 of 538: Studies in Computational IntelligenceLanguage: English
Published by Springer, Palgrave Macmillan Feb 2019, 2019
ISBN 10: 3030103331 ISBN 13: 9783030103330
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 116 pp. Englisch.
