Smarter at the Edge: Evaluating Decentralized AI Deployment Models in Federated,Hierarchical, Microservices and Serverless edge AI Architectures
Abstract: The advent of edge computing and artificial intelligence (AI) has spurred the development of decentralized architectures to address privacy, latency, scalability, and cost challenges in AI deployment. This paper provides an in-depth examination of four architectures—Federated Learning (FL), Edge-Cloud Hierarchical, Microservices-Based Edge AI, and Serverless Edge AI—focusing on their components, workflows, advantages, challenges, and […]