  In a wireless sensor network, nodes communicate time-stamped packets in order
to synchronize their clocks, i.e., estimate each other's time display. We
introduce and analyze a parametrized stochastic model for clocks and use it to
calculate, at any given time, the Maximum-Likelihood (ML) estimate of the
relative skew/offset between two communicating nodes. For network
synchronization, event-based Kalman-Bucy filtering gives rise to a centralized
scheme, and we propose an efficient distributed suboptimal algorithm. We study
the performance both analytically and experimentally and provide provable
guarantees. We summarize our findings into defining a new distributed
model-based clock synchronization protocol (MBCSP), and present a comparative
simulation study of its accuracy versus prior art to showcase improvements.
