{"product_id":"9781041003540-optimizing-edge-fog-computin","title":"Optimizing Edge and Fog Computing Applications with AI and Metaheuristic Algorithms","description":"\u003cmeta content=\"text\/html; charset=utf-8\" http-equiv=\"Content-Type\"\u003e\u003cp\u003e\u003cspan\u003e\u003cp\u003eThe 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. \u003c\/p\u003e\n\u003cbr\u003e\u003cp\u003eFog 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 \u003ci\u003eOptimizing Edge and Fog Computing Applications with AI and Metaheuristic Algorithms\u003c\/i\u003e. Other subjects covered in the book include:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eDesigning machine learning (ML) algorithms that are aware of the resource constraints at the edge and fog layers ensures efficient use of computational resources\u003c\/li\u003e\n\u003cli\u003eResource-aware models using ML and deep leaning models that can adapt their complexity based on available resources and balancing the load, allowing for better scalability\u003c\/li\u003e\n\u003cli\u003eImplementing secure ML algorithms and models to prevent adversarial attacks and ensure data privacy\u003c\/li\u003e\n\u003cli\u003eSecuring the communication channels between edge devices, fog nodes, and the cloud to protect model updates and inferences\u003c\/li\u003e\n\u003cli\u003eKubernetes container orchestration for fog computing\u003c\/li\u003e\n\u003cli\u003eFederated learning that enables model training across multiple edge devices without the need to share raw data\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eThe 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.\u003c\/p\u003e\n\u003cbr\u003e\u003cbr\u003e\u003c\/span\u003e\u003c\/p\u003e","brand":"Rarewaves","offers":[{"title":"Default Title","offer_id":56290070069622,"sku":"9781041003540","price":184.41,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0092\/7504\/8033\/files\/stand_36099737_9e230e51-f874-4ca2-9e34-0360f80b376b.jpg?v=1758145141","url":"https:\/\/www.rarewaves.com\/products\/9781041003540-optimizing-edge-fog-computin","provider":"Rarewaves.com","version":"1.0","type":"link"}