Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and focus on edge AI for resource orchestration. We claim that to support the constantly growing requirements of intelligent applications in the device-edge-cloud computing continuum, resource orchestration needs to embrace edge AI and emphasize local autonomy and intelligence. To justify the claim, we provide a general definition for continuum orchestration, and look at how current and emerging orchestration paradigms are suitable for the computing continuum. We describe certain major emerging research themes that may affect future orchestration, and provide an early vision of an orchestration paradigm that embraces those research themes. Finally, we survey current key edge AI methods and look at how they may contribute into fulfilling the vision of future continuum orchestration.
@article{arxiv.2205.01423,
title = {Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration},
author = {Henna Kokkonen and Lauri Lovén and Naser Hossein Motlagh and Abhishek Kumar and Juha Partala and Tri Nguyen and Víctor Casamayor Pujol and Panos Kostakos and Teemu Leppänen and Alfonso González-Gil and Ester Sola and Iñigo Angulo and Madhusanka Liyanage and Mehdi Bennis and Sasu Tarkoma and Schahram Dustdar and Susanna Pirttikangas and Jukka Riekki},
journal= {arXiv preprint arXiv:2205.01423},
year = {2023}
}