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Documents authored by Peltonen, Ella

Document
DOI: 10.4230/DagRep.13.10.130
Edge-AI: Identifying Key Enablers in Edge Intelligence (Dagstuhl Seminar 23432)

Authors: Aaron Ding, Eyal de Lara, Schahram Dustdar, Ella Peltonen, and Tobias Meuser

Published in: Dagstuhl Reports, Volume 13, Issue 10 (2024)

Abstract
Edge computing promises to decentralize cloud applications while providing more bandwidth and reducing latency. Based on the discussion of our first Dagstuhl Seminar and the continuation work that took place after the seminar, we continued our work on identified challenges that need to be further addressed within the community. These challenges included 1) large-scale deployment of the edge-cloud continuum, 2) energy optimization and sustainability of such large-scale AI/ML learning and modelling, and 3) trustworthiness, security, and ethical questions related to the whole continuum. In this seminar, we discussed the current state of Edge Intelligence and shaped a holistic view of its challenges and applications. The main concerns were 1) the assessment and applicability of Edge Intelligence solutions, 2) energy consumption and sustainability, and 3) the new trend of Large-Language Models.
Cite as

Aaron Ding, Eyal de Lara, Schahram Dustdar, Ella Peltonen, and Tobias Meuser. Edge-AI: Identifying Key Enablers in Edge Intelligence (Dagstuhl Seminar 23432). In Dagstuhl Reports, Volume 13, Issue 10, pp. 130-138, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{ding_et_al:DagRep.13.10.130,
  author =	{Ding, Aaron and de Lara, Eyal and Dustdar, Schahram and Peltonen, Ella and Meuser, Tobias},
  title =	{{Edge-AI: Identifying Key Enablers in Edge Intelligence (Dagstuhl Seminar 23432)}},
  pages =	{130--138},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2024},
  volume =	{13},
  number =	{10},
  editor =	{Ding, Aaron and de Lara, Eyal and Dustdar, Schahram and Peltonen, Ella and Meuser, Tobias},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.10.130},
  URN =		{urn:nbn:de:0030-drops-198376},
  doi =		{10.4230/DagRep.13.10.130},
  annote =	{Keywords: cloud computing, edge computing, edge intelligence}
}
Document
DOI: 10.4230/DagRep.11.7.76
Identifying Key Enablers in Edge Intelligence (Dagstuhl Seminar 21342)

Authors: Aaron Ding, Ella Peltonen, Sasu Tarkoma, and Lars Wolf

Published in: Dagstuhl Reports, Volume 11, Issue 7 (2021)

Abstract
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.
Cite as

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)

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@Article{ding_et_al:DagRep.11.7.76,
  author =	{Ding, Aaron and Peltonen, Ella and Tarkoma, Sasu and Wolf, Lars},
  title =	{{Identifying Key Enablers in Edge Intelligence (Dagstuhl Seminar 21342)}},
  pages =	{76--88},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2021},
  volume =	{11},
  number =	{7},
  editor =	{Ding, Aaron and Peltonen, Ella and Tarkoma, Sasu and Wolf, Lars},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.11.7.76},
  URN =		{urn:nbn:de:0030-drops-155906},
  doi =		{10.4230/DagRep.11.7.76},
  annote =	{Keywords: artificial intelligence, communication networks, edge computing, intelligent networking}
}
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