Time-Constrained Synchronization Protocol for Digital Twins over mMTC-enabled 6G Networks

Digital Twins (DTs) are envisioned to be a key element in the 6G, providing real-time analysis, optimization, and management. However, they do not support synchronization under real-time constraints. In parallel with this, the performance of the current synchronization method degrades with the increasing number of IoT devices due to latency and congestion. To address these, we design a Time-Constrained Synchronization Protocol (TCSP) for DTs over Massive Machine-Type Communication (mMTC)-enabled 6G Networks. Moreover, we propose a Strategy Selection Algorithm (SSA) that explores synchronization decisions proactively using What-If analysis. This module was built using a locally trained multi-layer perception to approximate mMTC network latency. Then, we evaluate the performance comparatively to periodic, selective and predictive synchronization methods. The results show that by utilizing the SSA algorithm, the twining rate reaches 0.98. Moreover, TCSP can perform consistently during congestion and provide up to 5 times the goodput of other synchronization methods. Meanwhile, TCSP also ensures that the time constraint is met and provides a 49% latency decrease.