2021/11/27 by Aaron Yi Ding, Ding, Aaron Yi, Ella Peltonen +35 · 1 citation
Computer Science · #Age of Information Optimization #Artificial Intelligence (cs.AI) #Distributed #FOS: Computer and information sciences #I.2.11 #IoT and Edge/Fog Computing #Parallel #Privacy-Preserving Technologies in Data #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2112.00616
openalex publication_date 2021/11/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimization, and deployment of distributed AI/ML pipelines with given quality of experience, trust, security and privacy targets. The Edge AI community investigates novel ML methods for the edge computing environment, spanning multiple sub-fields of computer science, engineering and ICT. The goal is to share an envisioned roadmap that can bring together key actors and enablers to further advance the domain of Edge AI.