Optimization of Synchronization Frequencies and Offloading Strategies in MEC-Assisted Digital Twin Networks

The integration of Digital Twin (DT) technology with Mobile Edge Computing (MEC) offers a promising solution for real-time system monitoring and optimization in smart industrial environments. To fully exploit the advantages of their integration, the allocation of MEC resources should carefully consider the application requirements of DT scenarios. This paper focuses on MEC-assisted DT scenarios and proposes a framework to model the dynamic interaction between device states, synchronization demands, and resource allocation, considering the varying synchronization frequency required by different device operational states. Under constraints of communication, computation, and storage resources, we perform joint optimization of the synchronization frequency and task offloading strategies. From both theoretical analysis and practical application perspectives, an optimal strategy based on solving an Integer Linear Programming (ILP) problem and a low-complexity heuristic algorithm are proposed. Extensive simulations in a smart factory scenario demonstrate significant advantages in improving the value of the utility function. This paper provides new insights into the deep integration of MEC and DT technologies and offers valuable references for applications in resource-constrained industrial environments.