Event-Triggered Time Synchronization With Varying Skews for Wireless Sensor Networks Based on Average Consensus

Existing event-triggered consensus-based time synchronization algorithms are proposed under the ideal wireless sensor networks without communication delays and varying skews of clocks. Nevertheless, delays and varying skews have a serious impact on the accuracy and reliability of time synchronization. Considering a more practical and challenging scenario with the above uncertainties, we investigate the average-consensus-based time synchronization algorithm. Specifically, a new triggering policy based on the event-triggered node interactions mechanism is presented, giving a threshold to constrain communication overhead. Furthermore, a memory-efficient relative skew estimator is utilized to counteract the influence of communication delays, which reduces storage requirements while achieving highly accurate estimation. To guarantee convergence under time-varying clock skews, a proportional-integral consensus skew estimator is considered to make compensation for skews. In addition, the convergence analysis of the proposed algorithm is proved theoretically. Simulation results demonstrate the effectiveness of the proposed algorithm, meanwhile, our proposed algorithm outperforms other existing algorithms in terms of energy consumption.