Energy-Efficient Digital Twin Placement in Mobile Edge Computing
Lan Wei, Haibin Zhang, Yadong Zhang, Wen Yao Sun, Yan Zhang · 2023
As one of the key enabling technologies, mobile edge computing can considerably reduce system latency and realize ubiquitous computing. The digital twin can constantly learn and update from entities to characterize the working conditions of physical entities. The integration of digital twins with mobile edge computing provides possibility for efficient resource allocation issues in the networks. However, the vast number of connected devices, resource heterogeneity, and dynamic network states are still challenging for the application of digital twins in mobile edge computing. In this paper, we propose a digital twin-empowered mobile edge computing architecture and investigate the energy-efficient digital twin placement. To adapt to the service demands of mobile edge computing, we exploit the Shapley value of the cooperative game theory and develop a Shapley value-based digital twin placement scheme. Numerical results show the efficiency of the proposed scheme in terms of average latency, average communication consumption, and digital twin error.