A game theory-based COVID-19 close contact detecting method with edge computing collaboration

Yue Shen; Bowen Liu; Xiaoyu Xia; Lianyong Qi; Xiaolong Xu; Wanchun Dou

doi:10.1016/j.comcom.2023.04.029

A game theory-based COVID-19 close contact detecting method with edge computing collaboration

Comput Commun. 2023 Jul 1:207:36-45. doi: 10.1016/j.comcom.2023.04.029. Epub 2023 May 8.

Authors

Yue Shen^{1

2}, Bowen Liu¹, Xiaoyu Xia³, Lianyong Qi⁴, Xiaolong Xu⁵, Wanchun Dou^{1

2

6}

Affiliations

¹ State Key Laboratory for Novel Software Technology, Nanjing University, China.
² Guangdong Laboratory of Artificia Intelligence and Digita Economy(SZ), Shenzhen, China.
³ School of Computing Technologies, RMIT University, Melbourne, Australia.
⁴ College of Computer and Software, China University of Petroleum (East China), China.
⁵ School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China.
⁶ College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming, China.

Abstract

People all throughout the world have suffered from the COVID-19 pandemic. People can be infected after brief contact, so how to assess the risk of infection for everyone effectively is a tricky challenge. In view of this challenge, the combination of wireless networks with edge computing provides new possibilities for solving the COVID-19 prevention problem. With this observation, this paper proposed a game theory-based COVID-19 close contact detecting method with edge computing collaboration, named GCDM. The GCDM method is an efficient method for detecting COVID-19 close contact infection with users' location information. With the help of edge computing's feature, the GCDM can deal with the detecting requirements of computing and storage and relieve the user privacy problem. Technically, as the game reaches equilibrium, the GCDM method can maximize close contact detection completion rate while minimizing the latency and cost of the evaluation process in a decentralized manner. The GCDM is described in detail and the performance of GCDM is analyzed theoretically. Extensive experiments were conducted and experimental results demonstrate the superior performance of GCDM over other three representative methods through comprehensive analysis.

Keywords: COVID-19; Decentralized method; Edge computing; Game theory.