Jaehan Lee

Bio: Jaehan Lee is an academic researcher from Texas A&M University. The author has contributed to research in topics: Clock synchronization & Wireless sensor network. The author has an hindex of 5, co-authored 9 publications receiving 280 citations.

Clock Synchronization in Wireless Sensor Networks: An Overview

Abstract: 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.

Robust Clock Synchronization in Wireless Sensor Networks Through Noise Density Estimation

Abstract: Assuming that the network delays are normally distributed and the network nodes are subject to clock phase offset errors, the maximum likelihood estimator (MLE) and the Kalman filter (KF) have been recently proposed with the goal of maximizing the clock synchronization accuracy in wireless sensor networks (WSNs). However, because the network delays may assume any distribution and the performance of MLE and KF is quite sensitive to the distribution of network delays, designing clock synchronization algorithms that are robust to arbitrary network delay distributions appears as an important problem. Adopting a Bayesian framework, this paper proposes a novel clock synchronization algorithm, called the Iterative Gaussian mixture Kalman particle filter (IGMKPF), which combines the Gaussian mixture Kalman particle filter (GMKPF) with an iterative noise density estimation procedure to achieve robust performance in the presence of unknown network delay distributions. The Kullback-Leibler divergence is used as a measure to assess the departure of estimated observation noise density from its true expression. The posterior Cramer-Rao bound (PCRB) and the mean-square error (MSE) of IGMKPF are evaluated via computer simulations. It is shown that IGMKPF exhibits improved performance and robustness relative to MLE. The prior information plays an important role in IGMKPF. A MLE-based method for obtaining reliable prior information for clock phase offsets is presented and shown to ensure the convergence of IGMKPF.

Clock Offset Estimation in Wireless Sensor Networks Using Bootstrap Bias Correction

Abstract: Wireless sensor networks have become an important and promising research area during the last recent years. Clock synchronization is one of the areas that play a crucial role in the design, implementation, and operation of wireless sensor networks. Under the assumption that there is no clock skew between sensor nodes, the Maximum Likelihood Estimate (MLE) of clock offset was proved by [1] for clock synchronization protocols that assume exponential random delays and a two-way message exchange mechanism such as TPSN (Timing-sync Protocol for Sensor Networks [2]). This MLE is asymptotically unbiased. However, the estimator is biased in the presence of a finite number of samples and much more biased in asymmetric random delay models, where the upstream delay characteristics are different from the downstream delay characteristics, and thus its performance is deteriorated. This paper proposes clock offset estimators based on the bootstrap bias correction approach, which estimates and corrects the bias of the MLE in the exponential delay model, and hence it results in better performances in mean squared error (MSE).

A robust approach for clock offset estimation in wireless sensor networks

Abstract: The maximum likelihood estimators (MLEs) for the clock phase offset assuming a two-way message exchange mechanism between the nodes of a wireless sensor network were recently derived assuming Gaussian and exponential network delays. However, the MLE performs poorly in the presence of non-Gaussian or nonexponential network delay distributions. Currently, there is a need to develop clock synchronization algorithms that are robust to the distribution of network delays. This paper proposes a clock offset estimator based on the composite particle filter (CPF) to cope with the possible asymmetries and non-Gaussianity of the network delay distributions. Also, a variant of the CPF approach based on the bootstrap sampling (BS) is shown to exhibit good performance in the presence of reduced number of observations. Computer simulations illustrate that the basic CPF and its BSbased variant present superior performance than MLE under general random network delay distributions such as asymmetric Gaussian, exponential, Gamma, Weibull as well as various mixtures.

Clock Synchronization of Wireless Sensor Networks

Abstract: Clock synchronization is a critical component in the operation of wireless sensor networks (WSNs), 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 coordinated sleep wake-up node scheduling mechanisms. Early studies on clock synchronization for WSNs mainly focused on protocol design. However, the clock synchronization problem is inherently related to parameter estimation, and, recently, studies on clock synchronization began to emerge by adopting a statistical signal processing framework. In this article, a survey on the latest advances in the field of clock synchronization of WSNs is provided by following a signal processing viewpoint. This article illustrates that many of the proposed clock synchronization protocols can be interpreted and their performance assessed using common statistical signal processing methods. It is also shown that advanced signal processing techniques enable the derivation of optimal clock synchronization algorithms under challenging scenarios.

Re-evaluation of RF electromagnetic communication in underwater sensor networks

Abstract: Most underwater wireless networks use acoustic waves as the transmission medium nowadays, but the chances of getting much more out of acoustic modems are quite remote. Optical links are impractical for many underwater applications. Given modern operational requirements and digital communications technology, the time is now ripe for re-evaluating the role of electromagnetic signals in underwater environments. The research presented in this article is motivated by the limitations of current and established wireless underwater techniques, as well as the potential that electromagnetic waves can offer to underwater applications. A case study is presented that uses electromagnetic technology in a small-scale underwater wireless sensor network. The results demonstrate the likely effectiveness of the designated network.

Design of a Water Environment Monitoring System Based on Wireless Sensor Networks

Abstract: A water environmental monitoring system based on a wireless sensor network is proposed. It consists of three parts: data monitoring nodes, data base station and remote monitoring center. This system is suitable for the complex and large-scale water environment monitoring, such as for reservoirs, lakes, rivers, swamps, and shallow or deep groundwaters. This paper is devoted to the explanation and illustration for our new water environment monitoring system design. The system had successfully accomplished the online auto-monitoring of the water temperature and pH value environment of an artificial lake. The system's measurement capacity ranges from 0 to 80 °C for water temperature, with an accuracy of ±0.5 °C; from 0 to 14 on pH value, with an accuracy of ±0.05 pH units. Sensors applicable to different water quality scenarios should be installed at the nodes to meet the monitoring demands for a variety of water environments and to obtain different parameters. The monitoring system thus promises broad applicability prospects.

Clock Synchronization in Wireless Sensor Networks: An Overview

Abstract: 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.

Collaborative Sensor Network Localization: Algorithms and Practical Issues

Abstract: Emerging communication network applications including fifth-generation (5G) cellular and the Internet-of-Things (IoT) will almost certainly require location information at as many network nodes as possible. Given the energy requirements and lack of indoor coverage of Global Positioning System (GPS), collaborative localization appears to be a powerful tool for such networks. In this paper, we survey the state of the art in collaborative localization with an eye toward 5G cellular and IoT applications. In particular, we discuss theoretical limits, algorithms, and practical challenges associated with collaborative localization based on range-based as well as range-angle-based techniques.