University of Oulu

6G white paper on edge intelligence

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Author: Peltonen, Ella1; Bennis, Mehdi1; Capobianco, Michele2;
Organizations: 1University of Oulu, 6G Flagship
4TU Delft
5University of Vigo
6VTT Technical Research Centre of Finland
7Poznan University of Technology
8University of Helsinki
9Pengcheng Laboratory
Format: ebook
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 13.8 MB)
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Language: English
Published: Oulu : University of Oulu, 2020
Publish Date: 2020-06-30


In this white paper, we provide a vision for 6G edge intelligence. Moving toward 5G and beyond future 6G networks, intelligent solutions utilizing data-driven machine learning and artificial intelligence will become crucial for several real-world applications, including but not limited to more efficient manufacturing, novel personal smart device environments and experiences, urban computing, and autonomous traffic settings. We sent edge computing with other 6G enablers as a key component to establish the future 2030 intelligent Internet technologies shown in this series of 6G white papers.

In this white paper, we focus on the domains of edge-computing infrastructure and platforms, data and edge network management, software development for edge, and real-time and distributed training of ML/AI algorithms, as well as security, privacy, pricing, and end-user aspects. We discuss the key enablers and challenges, and identify the key research questions for the development of intelligent edge services. As the main outcome of this white paper, we envision a transition from the Internet of Things to the Intelligent Internet of Intelligent Things and provide a roadmap for the development of the 6G intelligent edge.

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Series: 6G research visions
ISSN: 2669-9621
ISSN-E: 2669-963X
ISSN-L: 2669-9621
ISBN: 978-952-62-2677-4
Issue: 8
Type of Publication: D4 Published development or research report or study
Field of Science: 213 Electronic, automation and communications engineering, electronics
Copyright information: © University of Oulu, 2020. This publication is copyrighted. You may download, display and print it for your own personal use. Commercial use is prohibited.