ISBN: 9781032600093 - advanced computing techniques for optimization in cloud (8 risultati)

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  • Lingua: Inglese

    Editore: CRC Press, 2026

    1032600098 / 9781032600093

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    Da: moluna, Greven, Germaniamoluna

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    EUR 79,62

    EUR 48,99 spedizione 
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    Condizione: New. Dr. Madhusudhan H S is currently working as Associate Professor in the Department of computer science and Engineering at Vidyavardhaka College of Engineering, Mysuru, Karnataka, India. He has published scientific research publications in reputed I.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd (Sales) Jul 2026, 2026

    1032600098 / 9781032600093

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 107,76

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    Taschenbuch. Condizione: Neu. Neuware - This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques. - Focuses on virtual machine placement and migration techniques for cloud data centers - Presents the role of machine learning and metaheuristic approaches for optimisation in cloud computing services - Includes application of placement techniques for quality of service, performance, and reliability improvement - Explores data center resource management, load balancing and orchestration using machine learning techniques - Analyses dynamic and scalable resource scheduling with a focus on resource management The text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.…

  • Editore: 7 écrit Editions, 2015

    1032600098 / 9781032600093

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    EUR 105,58

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    Paperback. Condizione: Brand New. 224 pages. French language. 8.66x5.91x0.53 inches. In Stock.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2026

    1032600098 / 9781032600093

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    Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    EUR 58,15

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    Paperback. Condizione: new. Paperback. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and meta-heuristic approaches for placement techniques. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Lingua: Inglese

    Editore: Candh/CRC Press, 2026

    1032600098 / 9781032600093

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    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    EUR 88,00

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    PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Lingua: Inglese

    Editore: Candh/CRC Press, 2026

    1032600098 / 9781032600093

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    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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    EUR 84,08

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    PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2026

    1032600098 / 9781032600093

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    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    EUR 58,10

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    Paperback. Condizione: new. Paperback. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and meta-heuristic approaches for placement techniques. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, 2026

    1032600098 / 9781032600093

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    Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    EUR 95,89

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    Paperback. Condizione: new. Paperback. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques.Focuses on virtual machine placement and migration techniques for cloud data centersPresents the role of machine learning and metaheuristic approaches for optimisation in cloud computing servicesIncludes application of placement techniques for quality of service, performance, and reliability improvementExplores data center resource management, load balancing and orchestration using machine learning techniquesAnalyses dynamic and scalable resource scheduling with a focus on resource managementThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology. This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and meta-heuristic approaches for placement techniques. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…