Roadmap for edge AI: A Dagstuhl Perspective

Aaron Yi Ding, Ella Peltonen, Tobias Meuser, Atakan Aral, Christian Becker, Schahram Dustdar, Thomas Hiessl, Dieter Kranzlmüller, Madhusanka Liyanage, Setareh Maghsudi, Nitinder Mohan, Jörg Ott, Jan S. Rellermeyer, Stefan Schulte, Henning Schulzrinne, Gürkan Solmaz, Sasu Tarkoma, Blesson Varghese, Lars Wolf

Tutkimustuotos: ArtikkelijulkaisuArtikkeliTieteellinen

Abstrakti

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, 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 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.

Alkuperäiskielienglanti
LehtiComputer Communication Review
Vuosikerta52
Numero1
Sivut28-33
Sivumäärä6
ISSN0146-4833
DOI - pysyväislinkit
TilaJulkaistu - tammik. 2022
OKM-julkaisutyyppiB1 Kirjoitus tieteellisessä aikakauslehdessä

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