6G White Paper on Edge Intelligence
In this white paper, we provide a vision for 6G Edge Intelligence. Moving beyond 5G and towards the future 6G networks, intelligent solutions utilizing data-driven machine learning and artificial intelligence become crucial for uncountable 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 present edge computing, along with other 6G enablers, as a key component to establish the future 2030 intelligent Internet technologies as 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, along with security, privacy, pricing, and end-user aspects. We discuss key enablers and challenges and identify essential research questions for the development of the Intelligent Edge services. As a main outcome of this white paper, we envision a transition from Internet of Things to Intelligent Internet of Intelligent Things and provide a roadmap for the development of 6G Intelligent Edge.
This white paper has been written by an international expert group, led by the Finnish 6G Flagship program at the University of Oulu, within a series of twelve 6G white papers published in their final format in 2020.
Read the Full Paper in Jultika
- Similarly to the transition from cloud to Cloud Intelligence, we are constantly assisting at an evolution from the “Internet of Things” to the “Internet of Intelligent Things”. There is a need for an “Intelligent Internet of Intelligent Things” to make such internet more reliable, more efficient, more resilient, and more secure. This is exactly the area where 6G communication with edge-driven artificial intelligence can play a fundamental role.
- Artificial intelligence on the wireless communication nodes can enable a number of advanced services and quality of service functionalities. We claim that performance, cost, security, efficiency, and reliability are key features and measurable indicators of any Edge Intelligence solutions.
- The evolution to the deployment of a new generation of edge intelligence systems, applications and services will take place during the next ten years, with the completion of different technological steps that will provide new devices, technology, and applications.
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List of Contributors
- Ella Peltonen, University of Oulu, Finland
- Mehdi Bennis, University of Oulu, Finland
- Michele Capobianco, Capobianco, Italy
- Merouane Debbah, Huawei, France
- Aaron Ding, TU Delft, Netherlands
- Felipe Gil-Castiñeira, University of Vigo, Spain
- Marko Jurmu, VTT Technical Research Centre of Finland, Finland
- Teemu Karvonen, University of Oulu, Finland
- Markus Kelanti, University of Oulu, Finland
- Adrian Kliks, Poznan University of Technology, Poland
- Teemu Leppänen, University of Oulu, Finland
- Lauri Lovén, University of Oulu, Finland
- Tommi Mikkonen, University of Helsinki, Finland
- Ashwin Rao, University of Helsinki, Finland
- Sumudu Samarakoon, University of Oulu, Finland
- Kari Seppänen, VTT Technical Research Centre of Finland, Finland
- Paweł Sroka, Poznan University of Technology, Poland
- Sasu Tarkoma, University of Helsinki, Finland
- Tingting Yang, Pengcheng Laboratory, China