Optimizing edge fog computing (16 Ergebnisse)
Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (EDT); Gupta, Punit (EDT); Saini, Dinesh Kumar (EDT)
- Hardcover
Anbieter: GreatBookPrices, Columbia, MD, USAGreatBookPrices
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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)
- Hardcover
Anbieter: GreatBookPrices, Columbia, MD, USAGreatBookPrices
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Anbieter: Books Puddle, New York, NY, USABooks Puddle
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EUR 186,51
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Zustand: New. 1st edition NO-PA16APR2015-KAP.
- Hardcover
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EUR 190,74
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Zustand: New.
Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (EDT); Gupta, Punit (EDT); Saini, Dinesh Kumar (EDT)
- Hardcover
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes KönigreichGreatBookPricesUK
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EUR 180,21
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- Hardcover
Anbieter: California Books, Miami, FL, USACalifornia Books
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EUR 213,31
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- Hardcover
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
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HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (EDT); Gupta, Punit (EDT); Saini, Dinesh Kumar (EDT)
- Hardcover
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes KönigreichGreatBookPricesUK
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EUR 200,18
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- Hardcover
Anbieter: PBShop.store US, Wood Dale, IL, USAPBShop.store US
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HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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Zustand: New. In.
- Hardcover
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EUR 217,61
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Hardback. Zustand: 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)
- Hardcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
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EUR 261,05
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Hardcover. Zustand: Brand New. 248 pages. 9.18x6.12x9.21 inches. In Stock.
- Hardcover
- Print-on-Demand
Anbieter: Grand Eagle Retail, Bensenville, IL, USAGrand Eagle Retail
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EUR 190,00
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Hardcover. Zustand: 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 di…fferences 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.
- Hardcover
- Print-on-Demand
Anbieter: Biblios, frankfurt am main, HESSE, DeutschlandBiblios
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EUR 199,48
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Zustand: New. PRINT ON DEMAND.
- Hardcover
- Print-on-Demand
Anbieter: CitiRetail, Stevenage, Vereinigtes KönigreichCitiRetail
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EUR 222,01
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Hardcover. Zustand: 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 di…fferences 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.
- Hardcover
- Print-on-Demand
Anbieter: AussieBookSeller, Truganina, VIC, AustralienAussieBookSeller
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EUR 249,15
EUR 31,93 VersandVersand von Australien nach USAAnzahl: 1 verfügbar
Hardcover. Zustand: 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 di…fferences 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.
