Signal processing techniques for synchronization of wireless sensor networks

Plenary PaperClock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated. © 2010 SPIE.published_or_final_versio

Clock Synchronization in Wireless Sensor Networks: An Overview

The development of tiny, low-cost, low-power and multifunctional sensor nodes equipped with sensing, data processing, and communicating components, have been made possible by the recent advances in micro-electro-mechanical systems (MEMS) technology. Wireless sensor networks (WSNs) assume a collection of such tiny sensing devices connected wirelessly and which are used to observe and monitor a variety of phenomena in the real physical world. Many applications based on these WSNs assume local clocks at each sensor node that need to be synchronized to a common notion of time. This paper reviews the existing clock synchronization protocols for WSNs and the methods of estimating clock offset and clock skew in the most representative clock synchronization protocols for WSNs

Diffusion-based clock synchronization for molecular communication under inverse Gaussian distribution

Nanonetworks are expected to expand the capabilities of individual nanomachines by allowing them to cooperate and share information by molecular communication. The information molecules are released by the transmitter nanomachine and diffuse across the aqueous channel as a Brownian motion holding the feature of a strong random movement with a large propagation delay. In order to ensure an effective real-time cooperation, it is necessary to keep the clock synchronized among the nanomachines in the nanonetwork. This paper proposes a model on a two-way message exchange mechanism with the molecular propagation delay based on the inverse Gaussian distribution. The clock offset and clock skew are estimated by the maximum likelihood estimation (MLE). Simulation results by MATLAB show that the mean square errors (MSE) of the estimated clock offsets and clock skews can be reduced and converge with a number of rounds of message exchanges. The comparison of the proposed scheme with a clock synchronization method based on symmetrical propagation delay demonstrates that our proposed scheme can achieve a better performance in terms of accuracy

Fully Distributed Clock Skew And Offset Estimation In Wireless Sensor Networks

In this paper, we propose a fully distributed algorithm for joint clock skew and offset estimation in wireless sensor networks. With the proposed algorithm, each node can estimate its clock skew and offset by communicating only with its neighbors. Such algorithm does not require any centralized information processing or coordination. Simulation results show that estimation mean-square-error at each node converge to the centralized Cramér-Rao bound with only a few number of message exchanges.published_or_final_versio

Cooperative Synchronization in Wireless Networks

Synchronization is a key functionality in wireless network, enabling a wide variety of services. We consider a Bayesian inference framework whereby network nodes can achieve phase and skew synchronization in a fully distributed way. In particular, under the assumption of Gaussian measurement noise, we derive two message passing methods (belief propagation and mean field), analyze their convergence behavior, and perform a qualitative and quantitative comparison with a number of competing algorithms. We also show that both methods can be applied in networks with and without master nodes. Our performance results are complemented by, and compared with, the relevant Bayesian Cram\'er-Rao bounds

Low-complexity maximum-likelihood estimator for clock synchronization of wireless sensor nodes under exponential delays

In this paper, the clock synchronization for wireless sensor networks in the presence of unknown exponential delay is investigated under the two-way message exchange mechanism. The maximum-likelihood estimator for joint estimation of clock offset, clock skew and fixed delay is first cast into a linear programming problem. Based on novel geometric analyses of the feasible domain, a low-complexity maximum likelihood estimator is then proposed. Complexities of the proposed estimators and existing algorithms are compared analytically and numerically. Simulation results further demonstrate that our proposed algorithms have advantages in terms of both performance and computational complexities. © 2011 IEEE.published_or_final_versio