Identifying Key Enablers in Edge Intelligence (Dagstuhl Seminar 21342)

Authors Aaron Ding, Ella Peltonen, Sasu Tarkoma, Lars Wolf and all authors of the abstracts in this report

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Author Details

Aaron Ding
  • TU Delft, NL
Ella Peltonen
  • University of Oulu, FI
Sasu Tarkoma
  • University of Helsinki, FI
Lars Wolf
  • TU Braunschweig, DE
and all authors of the abstracts in this report

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Aaron Ding, Ella Peltonen, Sasu Tarkoma, and Lars Wolf. Identifying Key Enablers in Edge Intelligence (Dagstuhl Seminar 21342). In Dagstuhl Reports, Volume 11, Issue 7, pp. 76-88, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


Edge computing, a key part of the 5G networks and beyond, promises to decentralize cloud applications while providing more bandwidth and reducing latencies. The promises are delivered by moving application-specific computations between the cloud, the data-producing devices, and the network infrastructure components at the edges of wireless and fixed networks. However, the current AI/ML methods assume computations are conducted in a powerful computational infrastructure, such as a homogeneous cloud with ample computing and data storage resources available. In this seminar, we discussed and developed presumptions for a comprehensive view of AI methods and capabilities in the context of edge computing, and provided a roadmap to bring together enablers and key aspects for edge computing and applied AI/ML fields.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Distributed architectures
  • Computing methodologies → Artificial intelligence
  • Networks
  • artificial intelligence
  • communication networks
  • edge computing
  • intelligent networking


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