TY - JOUR
T1 - A Practical Cross-Device Federated Learning Framework over 5G Networks
AU - Yang, Wenti
AU - Wang, Naiyu
AU - Guan, Zhitao
AU - Wu, Longfei
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - The concept of federated learning (FL) was first proposed by Google in 2016. Since then, FL has been widely studied for the feasibility of application in various fields due to its potential to make full use of data without compromising privacy. However, limited by the capacity of wireless data transmission, the employment of FL on mobile devices has been making slow progress in practice. The development and commercialization of the 5th generation (5G) mobile networks has shed some light on this. In this article, we analyze the challenges of existing FL schemes for mobile devices and propose a novel cross-device FL framework that utilizes the anonymous communication technology and ring signature to protect the privacy of participants while reducing the computation overhead of mobile devices participating in FL. In addition, our scheme implements a contribution-based incentive mechanism to encourage mobile users to participate in FL. We also give a case study of autonomous driving. Finally, we present the performance evaluation of the proposed scheme and discuss some open issues in FL.
AB - The concept of federated learning (FL) was first proposed by Google in 2016. Since then, FL has been widely studied for the feasibility of application in various fields due to its potential to make full use of data without compromising privacy. However, limited by the capacity of wireless data transmission, the employment of FL on mobile devices has been making slow progress in practice. The development and commercialization of the 5th generation (5G) mobile networks has shed some light on this. In this article, we analyze the challenges of existing FL schemes for mobile devices and propose a novel cross-device FL framework that utilizes the anonymous communication technology and ring signature to protect the privacy of participants while reducing the computation overhead of mobile devices participating in FL. In addition, our scheme implements a contribution-based incentive mechanism to encourage mobile users to participate in FL. We also give a case study of autonomous driving. Finally, we present the performance evaluation of the proposed scheme and discuss some open issues in FL.
UR - http://www.scopus.com/inward/record.url?scp=85130507373&partnerID=8YFLogxK
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U2 - 10.1109/MWC.005.2100435
DO - 10.1109/MWC.005.2100435
M3 - Article
AN - SCOPUS:85130507373
SN - 1536-1284
VL - 29
SP - 128
EP - 134
JO - IEEE Wireless Communications
JF - IEEE Wireless Communications
IS - 6
ER -