Low-Overhead Data Synchronization Enabled by Prescheduled Task Period in Time-Sensitive IoT Systems
Haide Wang, Pengyi Jia, Xianbin Wang · 2021
Time-sensitive applications in Internet of Things (IoT) systems rely heavily on the temporal coherence among its distributed constituents during data fusion and analysis. The inconsistent clock output inherent to the unstable and heterogeneous clock oscillator embedded at each IoT device will inevitably lead to inaccurate data processing and deteriorated overall performance. In this paper, a low-overhead data synchronization scheme is proposed to achieve accurate temporal consistency prior to fusing the massive data collected from the distributed IoT devices. More specifically, a task period is scheduled for each sensor device to deliver the sampled data to SN. By comparing the difference between the predefined period and the real observed one, the clock parameters can be estimated accurately so that the misalignment of the data can be compensated accordingly. Simulation results show that the proposed scheme can enhance the data fusion accuracy with significantly reduced network overhead.