Accurate Distributed Time Synchronization in Mobile Wireless Sensor Networks from Noisy Difference Measurements

TL;DR

This paper introduces a distributed stochastic approximation algorithm for accurate time synchronization in mobile wireless sensor networks, effectively estimating global time despite noisy measurements and clock variations.

Contribution

It presents a novel distributed algorithm that ensures mean square convergence for time synchronization in mobile sensor networks using noisy difference measurements.

Findings

Achieves highly accurate global time estimates over long durations.

Outperforms competing algorithms with errors that do not increase over time.

Includes a modification to improve initial convergence speed.

Abstract

We propose a distributed algorithm for time synchronization in mobile wireless sensor networks. Each node can employ the algorithm to estimate the global time based on its local clock time. The problem of time synchronization is formulated as nodes estimating their skews and offsets from noisy difference measurements of offsets and logarithm of skews; the measurements acquired by time-stamped message exchanges between neighbors. A distributed stochastic approximation based algorithm is proposed to ensure that the estimation error is mean square convergent (variance converging to 0) under certain conditions. A sequence of scheduled update instants is used to meet the requirement of decreasing time-varying gains that need to be synchronized across nodes with unsynchronized clocks. Moreover, a modification on the algorithm is also presented to improve the initial convergence speed. Simulations indicate that highly accurate global time estimates can be achieved with the proposed algorithm for long time durations, while the errors in competing algorithms increase over time.