9781041003540 - optimizing edge and fog computing applications with ai and metaheuristic algorithms (16 resultados)
Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (EDT); Gupta, Punit (EDT); Saini, Dinesh Kumar (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 180,18
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Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (EDT); Gupta, Punit (EDT); Saini, Dinesh Kumar (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 187,64
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 186,51
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 190,74
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Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (EDT); Gupta, Punit (EDT); Saini, Dinesh Kumar (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 180,21
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 213,31
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 211,80
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Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (EDT); Gupta, Punit (EDT); Saini, Dinesh Kumar (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 200,18
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 219,41
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 208,09
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Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
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EUR 217,61
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Hardback. Condición: New. New copy - Usually dispatched within 4 working days.
Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (Editor)/ Gupta, Punit (Editor)/ Saini, Dinesh Kumar (Editor)
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 261,05
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Hardcover. Condición: Brand New. 248 pages. 9.18x6.12x9.21 inches. In Stock.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 190,00
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Hardcover. Condición: new. Hardcover. Fog and edge computing are two paradigms that have emerged to address the challenges associated with processing and managing data in the era of the Internet of Things (IoT). Both models involve moving computation and data storage closer to the source of data generation, but they have subtle…differences in their architectures and scopes. These differences are one of the subjects covered in Optimizing Edge and Fog Computing Applications with AI and Metaheuristic Algorithms. Other subjects covered in the book include:Designing machine learning (ML) algorithms that are aware of the resource constraints at the edge and fog layers ensures efficient use of computational resourcesResource-aware models using ML and deep leaning models that can adapt their complexity based on available resources and balancing the load, allowing for better scalabilityImplementing secure ML algorithms and models to prevent adversarial attacks and ensure data privacySecuring the communication channels between edge devices, fog nodes, and the cloud to protect model updates and inferencesKubernetes container orchestration for fog computingFederated learning that enables model training across multiple edge devices without the need to share raw dataThe book discusses how resource optimization in fog and edge computing is crucial for achieving efficient and effective processing of data close to the source. It explains how both fog and edge computing aim to enhance system performance, reduce latency, and improve overall resource utilization. It examines the combination of intelligent algorithms, effective communication protocols, and dynamic management strategies required to adapt to changing conditions and workload demands. The book explains how security in fog and edge computing requires a combination of technological measures, advanced techniques, user awareness, and organizational policies to effectively protect data and systems from evolving security threats. Finally, it looks forward with coverage of ongoing research and development, which are essential for refining optimization techniques and ensuring the scalability and sustainability of fog and edge computing environments. The book covers resource management techniques to enhance resource optimization, security mechanisms and predictive computing in fog and edge computing. Machine learning (ML) can leverage the distributed nature of these fog and edge architectures to perform computation and analysis closer to the data source. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 199,48
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Condición: New. PRINT ON DEMAND.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 222,01
Envío por EUR 43,23Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Fog and edge computing are two paradigms that have emerged to address the challenges associated with processing and managing data in the era of the Internet of Things (IoT). Both models involve moving computation and data storage closer to the source of data generation, but they have subtle…differences in their architectures and scopes. These differences are one of the subjects covered in Optimizing Edge and Fog Computing Applications with AI and Metaheuristic Algorithms. Other subjects covered in the book include:Designing machine learning (ML) algorithms that are aware of the resource constraints at the edge and fog layers ensures efficient use of computational resourcesResource-aware models using ML and deep leaning models that can adapt their complexity based on available resources and balancing the load, allowing for better scalabilityImplementing secure ML algorithms and models to prevent adversarial attacks and ensure data privacySecuring the communication channels between edge devices, fog nodes, and the cloud to protect model updates and inferencesKubernetes container orchestration for fog computingFederated learning that enables model training across multiple edge devices without the need to share raw dataThe book discusses how resource optimization in fog and edge computing is crucial for achieving efficient and effective processing of data close to the source. It explains how both fog and edge computing aim to enhance system performance, reduce latency, and improve overall resource utilization. It examines the combination of intelligent algorithms, effective communication protocols, and dynamic management strategies required to adapt to changing conditions and workload demands. The book explains how security in fog and edge computing requires a combination of technological measures, advanced techniques, user awareness, and organizational policies to effectively protect data and systems from evolving security threats. Finally, it looks forward with coverage of ongoing research and development, which are essential for refining optimization techniques and ensuring the scalability and sustainability of fog and edge computing environments. The book covers resource management techniques to enhance resource optimization, security mechanisms and predictive computing in fog and edge computing. Machine learning (ML) can leverage the distributed nature of these fog and edge architectures to perform computation and analysis closer to the data source. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 249,15
Envío por EUR 31,93Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Fog and edge computing are two paradigms that have emerged to address the challenges associated with processing and managing data in the era of the Internet of Things (IoT). Both models involve moving computation and data storage closer to the source of data generation, but they have subtle…differences in their architectures and scopes. These differences are one of the subjects covered in Optimizing Edge and Fog Computing Applications with AI and Metaheuristic Algorithms. Other subjects covered in the book include:Designing machine learning (ML) algorithms that are aware of the resource constraints at the edge and fog layers ensures efficient use of computational resourcesResource-aware models using ML and deep leaning models that can adapt their complexity based on available resources and balancing the load, allowing for better scalabilityImplementing secure ML algorithms and models to prevent adversarial attacks and ensure data privacySecuring the communication channels between edge devices, fog nodes, and the cloud to protect model updates and inferencesKubernetes container orchestration for fog computingFederated learning that enables model training across multiple edge devices without the need to share raw dataThe book discusses how resource optimization in fog and edge computing is crucial for achieving efficient and effective processing of data close to the source. It explains how both fog and edge computing aim to enhance system performance, reduce latency, and improve overall resource utilization. It examines the combination of intelligent algorithms, effective communication protocols, and dynamic management strategies required to adapt to changing conditions and workload demands. The book explains how security in fog and edge computing requires a combination of technological measures, advanced techniques, user awareness, and organizational policies to effectively protect data and systems from evolving security threats. Finally, it looks forward with coverage of ongoing research and development, which are essential for refining optimization techniques and ensuring the scalability and sustainability of fog and edge computing environments. The book covers resource management techniques to enhance resource optimization, security mechanisms and predictive computing in fog and edge computing. Machine learning (ML) can leverage the distributed nature of these fog and edge architectures to perform computation and analysis closer to the data source. 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.
