Roadmap for edge AI
| Autor: | 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 |
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| Přispěvatelé: | Department of Computer Science, Content-Centric Structures and Networking research group / Sasu Tarkoma |
| Rok vydání: | 2022 |
| Předmět: |
FOS: Computer and information sciences
I.2.11 Computer Science - Artificial Intelligence Computer Networks and Communications 5G beyond Edge computing 113 Computer and information sciences GeneralLiterature_MISCELLANEOUS Artificial Intelligence (cs.AI) Roadmap Computer Science - Distributed Parallel and Cluster Computing Future Cloud Future cloud 5G Beyond Edge Computing Distributed Parallel and Cluster Computing (cs.DC) Edge AI Software |
| Zdroj: | Computer Communications Review, 52(1) |
| ISSN: | 0146-4833 |
| DOI: | 10.1145/3523230.3523235 |
| Popis: | 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. Comment: for ACM SIGCOMM CCR |
| Databáze: | OpenAIRE |
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