Optimizing Edge and Fog Computing with AI by Madhusudhan H S (.ePUB)+
File Size: 23.9 MB
Optimizing Edge and Fog Computing Applications with AI and Metaheuristic Algorithms by Madhusudhan H S, Punit Gupta, Dinesh Kumar Saini
Requirements: .ePUB, .PDF reader, 23.9 MB
Overview: 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 resources
Resource-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
Implementing secure ML algorithms and models to prevent adversarial attacks and ensure data privacy
Securing the communication channels between edge devices, fog nodes, and the cloud to protect model updates and inferences
Kubernetes container orchestration for fog computing
Federated learning that enables model training across multiple edge devices without the need to share raw data
Genre: Non-Fiction > Tech & Devices
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