Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: Basi6 International, Irving, TX, U.S.A.
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Published by H N H International Limited, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: Majestic Books, Hounslow, United Kingdom
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by H N H International Limited, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 248 1st Editin NO-PA16APR2015-KAP.
Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: Grand Eagle Retail, Fairfield, OH, U.S.A.
Hardcover. Condition: new. Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketHardback. Condition: New. New copy - Usually dispatched within 4 working days. 526.
Published by H N H International Limited, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: Biblios, Frankfurt am main, HESSE, Germany
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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Published by Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031803000 ISBN 13: 9783031803000
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This essential book bridges the gap between cutting-edge artificial intelligence and the dynamic world of renewable energy systems. Embark on a journey to the forefront of sustainable energy innovation with this groundbreaking collection of research papers and expert insights.Designed for curious minds and industry leaders alike, this comprehensive resource offers:- A deep dive into the latest advancements in smart computing for sustainable energy.- Exploration of AI-driven techniques revolutionizing energy efficiency and management.- Real-world applications showcasing the transformative power of intelligent systems in renewables.- Insights into futuristic energy infrastructures powered by artificial intelligence.- A perfect blend of theoretical foundations and practical implementations.To a seasoned researcher pushing the boundaries of knowledge, a graduate student aspiring to make a mark, or an industry professional staying ahead of the curve, this book is a gateway to the future of energy.Discover how machine learning is reshaping solar forecasting, uncover the potential of autonomous systems in energy storage, and explore the role of AI in crafting smarter, more sustainable cities. From predictive maintenance that ensures uninterrupted power to intelligent control systems optimizing energy generation, this book covers it all.Don't just witness the renewable energy revolution-be part of it. This book equips readers with the knowledge and inspiration to drive innovation in this critical field. It is more than a collection of papers; it is a roadmap to a sustainable future where smart computing and renewable energy converge.Prepare to challenge your assumptions, expand your expertise, and contribute to a greener tomorrow. Order your copy today and position yourself at the vanguard of the smart energy movement!
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: CitiRetail, Stevenage, United Kingdom
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Add to basketHardcover. Condition: new. Hardcover. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketBuch. Condition: Neu. Neuware - The book offers cutting-edge insights into AI-driven optimization algorithms and their crucial role in enhancing real-time applications within fog and Edge IoT networks and addresses current challenges and future opportunities in this rapidly evolving field.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. XVIII, 861 349 illus., 239 illus. in color. 1st ed. 2020 edition NO-PA16APR2015-KAP.
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketHardcover. Condition: Brand New. 400 pages. In Stock.
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Add to basketHardcover. Condition: Brand New. 280 pages. French language. 9.18x6.12x8.66 inches. In Stock.
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032600071 ISBN 13: 9781032600079
Language: English
Seller: AussieBookSeller, Truganina, VIC, Australia
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Add to basketHardcover. Condition: new. Hardcover. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Springer-Nature New York Inc, 2025
ISBN 10: 3031803000 ISBN 13: 9783031803000
Language: English
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketPaperback. Condition: Brand New. 460 pages. 9.25x6.10x9.21 inches. In Stock.
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Add to basketCondition: New. 2025. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.