Optimizing Edge Fog Computing (16 results)
Optimizing Edge and Fog Computing Applications With Ai and Metaheuristic Algorithms
S., Madhusudhan H. (EDT); Gupta, Punit (EDT); Saini, Dinesh Kumar (EDT)
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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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
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Hardcover
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Condition: New. 1st edition NO-PA16APR2015-KAP.
- Hardcover
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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
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
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- Hardcover
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- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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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
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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£ 164.18
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Condition: New.
- Hardcover
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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Hardback. Condition: 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
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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£ 208.74
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Hardcover. Condition: Brand New. 248 pages. 9.18x6.12x9.21 inches. In Stock.
- Hardcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Hardcover. Condition: 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.
- Hardcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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£ 120.99
£ 37.00 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Hardcover. Condition: 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.
- Hardcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
Contact seller4-star sellerCondition: New
£ 172.80
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Condition: New. PRINT ON DEMAND.
- Hardcover
- Print on Demand
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contact seller5-star sellerCondition: New
£ 246.51
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Hardcover. Condition: 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.
- Hardcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
£ 233.49
£ 53.58 shippingShips from Germany to U.S.A.Quantity: 1 available
Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 architectur…es to perform computation and analysis closer to the data source.
