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

Distributed Local Linear Parameter Estimation using Gaussian SPAWN

We consider the problem of estimating local sensor parameters, where the local parameters and sensor observations are related through linear stochastic models. Sensors exchange messages and cooperate with each other to estimate their own local parameters iteratively. We study the Gaussian Sum-Product Algorithm over a Wireless Network (gSPAWN) procedure, which is based on belief propagation, but uses fixed size broadcast messages at each sensor instead. Compared with the popular diffusion strategies for performing network parameter estimation, whose communication cost at each sensor increases with increasing network density, the gSPAWN algorithm allows sensors to broadcast a message whose size does not depend on the network size or density, making it more suitable for applications in wireless sensor networks. We show that the gSPAWN algorithm converges in mean and has mean-square stability under some technical sufficient conditions, and we describe an application of the gSPAWN algorithm to a network localization problem in non-line-of-sight environments. Numerical results suggest that gSPAWN converges much faster in general than the diffusion method, and has lower communication costs, with comparable root mean square errors

Distributed clock synchronization for wireless sensor networks using belief propagation

In this paper, we study the global clock synchronization problem for wireless sensor networks. Based on belief propagation, we propose a fully distributed algorithm which has low overhead and can achieve scalable synchronization. It is also shown analytically that the proposed algorithm always converges for strongly connected networks. Simulation results show that the proposed algorithm achieves better accuracy than consensus algorithms. Furthermore, the belief obtained at each sensor provides an accurate prediction on the algorithm's performance in terms of MSE. © 2011 IEEE.published_or_final_versio

Time synchronization in wireless sensor networks

Time synchronization is basic requirements for various applications in wireless sensor network, e.g., event detection, speed estimating, environment monitoring, data aggregation, target tracking, scheduling and sensor nodes cooperation. Time synchronization is also helpful to save energy in WSN because it provides the possibility to set nodes into the sleeping mode. In wireless sensor networks all of above applications need that all sensor nodes have a common time reference. However, most existing time synchronization protocols are likely to deteriorate or even be destroyed when the WSNs attack by malicious intruders. The recently developed maximum and minimum consensus based time synchronization protocol (MMTS) is a promising alternative as it does not depend on any reference node or network topology. But MMTS is vulnerable to message manipulation attacks. In this thesis, we focus on how to defend the MMTS protocol in wireless sensor networks under message manipulation attacks. We investigate the impact of message manipulation attacks over MMTS. Then, a Secured Maximum and Minimum Consensus based Time Synchronization (SMMTS) protocol is proposed to detect and invalidate message manipulation attacks

A Gossip Algorithm based Clock Synchronization Scheme for Smart Grid Applications

The uprising interest in multi-agent based networked system, and the numerous number of applications in the distributed control of the smart grid leads us to address the problem of time synchronization in the smart grid. Utility companies look for new packet based time synchronization solutions with Global Positioning System (GPS) level accuracies beyond traditional packet methods such as Network Time Proto- col (NTP). However GPS based solutions have poor reception in indoor environments and dense urban canyons as well as GPS antenna installation might be costly. Some smart grid nodes such as Phasor Measurement Units (PMUs), fault detection, Wide Area Measurement Systems (WAMS) etc., requires synchronous accuracy as low as 1 ms. On the other hand, 1 sec accuracy is acceptable in management information domain. Acknowledging this, in this study, we introduce gossip algorithm based clock synchronization method among network entities from the decision control and communication point of view. Our method synchronizes clock within dense network with a bandwidth limited environment. Our technique has been tested in different kinds of network topologies- complete, star and random geometric network and demonstrated satisfactory performance