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Related Experiment Video

Updated: Jul 29, 2025

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Published on: June 23, 2022

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

Yue Shen^1,2, Bowen Liu¹, Xiaoyu Xia³

¹State Key Laboratory for Novel Software Technology, Nanjing University, China.

Computer Communications

|May 26, 2023

Summary

This summary is machine-generated.

This study introduces a game theory method using edge computing to detect COVID-19 close contacts efficiently. The GCDM approach enhances infection risk assessment while protecting user privacy and minimizing costs.

Keywords:

COVID-19 Decentralized method Edge computing Game theory

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Area of Science:

Computer Science
Public Health
Network Security

Background:

The COVID-19 pandemic necessitates effective methods for identifying close contacts to curb transmission.
Assessing infection risk accurately and promptly remains a significant challenge.
Traditional methods struggle with real-time data processing and privacy concerns.

Purpose of the Study:

To propose a novel method for detecting COVID-19 close contacts using game theory and edge computing.
To enhance the efficiency and privacy of infection risk assessment.
To address the computational and storage demands of contact tracing.

Main Methods:

A game theory-based approach named GCDM (Game theory-based COVID-19 close contact Detecting Method) was developed.
Edge computing collaboration was integrated to manage data processing and storage.
The method utilizes users' location information for decentralized detection.

Main Results:

The GCDM method maximizes close contact detection rates at game equilibrium.
It minimizes evaluation latency and cost in a decentralized system.
Theoretical analysis and extensive experiments confirm GCDM's superior performance over existing methods.

Conclusions:

GCDM offers an efficient and privacy-preserving solution for COVID-19 close contact detection.
Edge computing effectively supports the computational and storage needs of the proposed method.
The game theory framework ensures optimal performance in decentralized environments.