Authors: Ding, Aaron Yi; Peltonen, Ella; Meuser, Tobias; Aral, Atakan; Becker, Christian; Dustdar, Schahram; Hiessl, Thomas; Kranzlmüller, Dieter; Liyanage, Madhusanka; Maghsudi, Setareh; Mohan, Nitinder; Ott, Jörg; Rellermeyer, Jan S.; Schulte, Stefan; Schulzrinne, Henning; Solmaz, Gürkan; Tarkoma, Sasu; Varghese, Blesson; Wolf, Lars
Abstract: Based on the collective input of the 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, optimisation, 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 computer science, engineering and ICT sub-fields. The goal is to share an envisioned roadmap that can bring together key actors and enablers to advance the domain of Edge AI further.
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