Federated Learning in Mobile Edge Networks: A Comprehensive Survey
Wei Yang Bryan Lim, Nguyen Cong Luong, Dinh Thai Hoang et al.
2020 · IEEE Communications Surveys & Tutorials · 2,388 citations
In recent years, mobile devices are equipped with increasingly advanced sensing and computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up countless possibilities for meaningful applications, e.g., for medical purposes and in vehicular networks. Traditional cloud-based Machine Learning (ML) approaches require the data to be centralized in a cloud server or data center. However, this results in critical issues related to unacceptable latency and communication inefficiency. To this end, Mobile Edge Computing (MEC) has been proposed to bring intelligence closer to…
Explore this paper's citation graph on Constellation.