Learn More
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(More)
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(More)
To cope with the Gaussian or non-Gaussian nature of the random network delays, a novel method, referred to as the Gaussian mixture Kalman particle filter (GMKPF), is proposed herein to estimate the clock offset in wireless sensor networks. GMKPF represents a better and more flexible alternative to the symmetric Gaussian maximum likelihood (SGML), and(More)
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,(More)
Clock synchronization plays a crucial role in Wireless Sensor Networks (WSNs). Assuming that there is no clock skew between sensor nodes, the Maximum Likelihood Estimate (MLE) of clock offset was derived by [1] for clock synchronization protocols assuming exponential random delays and a two-way message exchange mechanism as in TPSN (Timing-sync Protocol for(More)
Defect depth profiles of Cu (In1-x,Gax)(Se1-ySy)2 (CIGSS) were measured as functions of pulse width and voltage via deep-level transient spectroscopy (DLTS). Four defects were observed, i.e., electron traps of ~0.2 eV at 140 K (E1 trap) and 0.47 eV at 300 K (E2 trap) and hole traps of ~0.1 eV at 100 K (H1 trap) and ~0.4 eV at 250 K (H2 trap). The open(More)
Recently, the maximum likelihood estimator (MLE) and Cramer-Rao Lower Bound (CRLB) were proposed with the goal of maximizing and assessing the synchronization accuracy in wireless sensor networks (WSNs). Because the network delays may assume any distribution and the performance of MLE is quite sensitive to the distribution of network delays, designing clock(More)
Clock 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(More)
  • 1