A4 Article in conference proceedings
Energy-Efficient and Privacy-Preserved Incentive Mechanism for Federated Learning in Mobile Edge Computing (2023)

Liu, J., Chang, Z., Min, G., & Zhang, Y. (2023). Energy-Efficient and Privacy-Preserved Incentive Mechanism for Federated Learning in Mobile Edge Computing. IEEE International Conference on Communications, 2023, 172-178. https://doi.org/10.1109/ICC45041.2023.10279757

JYU authors or editors

Publication details

All authors or editors: Liu, Jingyuan; Chang, Zheng; Min, Geyong; Zhang, Yan

Place and date of conference: Rome, Italy, 28.5.-1.6.2023

Journal or series: IEEE International Conference on Communications

ISSN: 1550-3607

eISSN: 1938-1883

Publication year: 2023

Publication date: 28/05/2023

Volume: 2023

Pages range: 172-178

Publisher: IEEE

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1109/ICC45041.2023.10279757

Publication open access: Not open

Publication channel open access: 

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/92568

Abstract

In mobile edge computing (MEC)-assisted federated learning (FL), the MEC users can train data locally and send the results to the MEC server to update the global model. However, the implementation of FL may be prevented by the selfish nature of MEC users, as they need to contribute considerable data and computing resources while scarifying certain data privacy for the FL process. Therefore, it is of great importance to design an efficient incentive mechanism to motivate the users to join the FL. In this work, with explicit consideration of the impact of wireless transmission and data privacy, we design an energy-efficient and privacy-preserved incentive scheme to facilitate the FL process by investigating interactions between the MEC server and MEC users in a MEC-assisted FL system. Using a Stackelberg game model, we explore the transmit power allocation and privacy budget determination of MEC users and reward strategy of the MEC server, and then analyze the Stackelberg equilibrium. The simulation results demonstrate the effectiveness of our proposed scheme.

Keywords: data protection; privacy; wireless data transmission

Contributing organizations

Ministry reporting: Yes

VIRTA submission year: 2023

Preliminary JUFO rating: 1