6G White Paper on Edge Intelligence

Abstract

In this white paper we provide a vision for 6G Edge Intelligence. Moving towards 5G and beyond the future 6G networks, intelligent solutions utilizing data-driven machine learning and artificial intelligence 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 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 in 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 the key enablers and challenges and identify the key 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 development of 6G Intelligent Edge.

References in corpus (6)

• Distilling the Knowledge in a Neural Network
• Federated Optimization: Distributed Machine Learning for On-Device Intelligence
• Split learning for health: Distributed deep learning without sharing raw patient data
• Edge Intelligence: Architectures, Challenges, and Applications
• Extreme URLLC: Vision, Challenges, and Key Enablers
• Towards an Intelligent Edge: Wireless Communication Meets Machine Learning

Cited by in corpus (11)

• 6G Internet of Things: A Comprehensive Survey
• Security and privacy for 6G: A survey on prospective technologies and challenges
• AI based Service Management for 6G Green Communications
• Edge Intelligence: Architectures, Challenges, and Applications
• Coordinated Sum-Rate Maximization in Multicell MU-MIMO with Deep Unrolling
• Research and Education Towards Smart and Sustainable World
• Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning
• A Comprehensive Survey of 6G Wireless Communications
• Towards characterization of edge-cloud continuum
• Survey on Aerial Radio Access Networks: Toward a Comprehensive 6G Access Infrastructure
• Edge Learning with Timeliness Constraints: Challenges and Solutions