Low-Latency Federated Learning and Blockchain for Edge Association in Digital Twin Empowered 6G Networks
Beijing University of Posts and Telecommunications · University of Electronic Science and Technology of China · +2 more institutions
Abstract
Emerging technologies, such as digital twins and 6th generation (6G) mobile networks, have accelerated the realization of edge intelligence in industrial Internet of Things (IIoT). The integration of digital twin and 6G bridges the physical system with digital space and enables robust instant wireless connectivity. With increasing concerns on data privacy, federated learning has been regarded as a promising solution for deploying distributed data processing and learning in wireless networks. However, unreliable communication channels, limited resources, and lack of trust among users hinder the effective application of federated learning in IIoT. In this article, we introduce the digital twin wireless networks…
Citation impact
- FWCI
- 35.63
- Percentile
- 100%
- References
- 32
Authors
5- YLYunlong LuCorresponding
Beijing University of Posts and Telecommunications
- XHXiaohong Huang
Beijing University of Posts and Telecommunications
- KZKe Zhang
University of Electronic Science and Technology of China
- SMSabita Maharjan
University of Oslo, Simula Metropolitan Center for Digital Engineering
- YZYan Zhang
University of Oslo, Simula Metropolitan Center for Digital Engineering
Topics & keywords
- Computer science
- Exploit
- Reinforcement learning
- Distributed computing
- Wireless network
- Edge device
- Wireless
- Edge computing
- Industry, innovation and infrastructure