Communication Patterns in Mean Field Models for Wireless Sensor Networks

Wireless sensor networks are usually composed of a large number of nodes, and with the increasing processing power and power consumption efficiency they are expected to run more complex protocols in the future. These pose problems in the field of verification and performance evaluation of wireless networks. In this paper, we tailor the mean-field theory as a modeling technique to analyze their behavior. We apply this method to the slotted ALOHA protocol, and establish results on the long term trends of the protocol within a very large network, specially regarding the stability of ALOHA-type protocols.Comment: 22 pages, in LNCS format, Submitted to QEST'1

Particle filter-based parameter estimation in a model of the human circadian rhythm

Recent insights into the effects of light on human health call for a more human-centric approach in automatic lighting control systems. We contribute to the provisioning of lighting settings tailored to the needs of individuals by addressing the challenge of predicting the response of an individual’s circadian rhythm to light exposure. Existing models of the human circadian rhythm are not tailored to individual physiological characteristics such as intrinsic circadian period, light sensitivity and age. We propose to improve model accuracy by using Bayesian statistical inference to estimate the values of model parameters that reflect these physiological characteristics. We illustrate our generic method by applying to a combination of two popular models of the circadian rhythm. By processing individual light exposure- and actigraphy data recoded during a field trial with 20 human subjects with a Particle Filter, we estimate each subject’s intrinsic circadian period. When correlating these to the subjects’ Munich Chronotype Questionnaire Midsleep on Free Days time, a significant relationship was found: r > 0.6 and p < 0.01. This shows the proposed method has good potential for improving model accuracy

Communications and sensing of illumination contributions in a power led lighting system

Abstract — In recent years, LED technology emerged as a prime candidate for the future illumination light source, due to high energy efficiency and long life time. In addition, LEDs offer a superior flexibility in terms of colors and shapes, which leads to a potentially infinite variety of available light patterns. In order to create these patterns via easy user interaction, we need to sense the local light contribution of each LED. This measurement could be enabled through tagging of the light of each LED with unique embedded IDs. To this end, we propose a new modulation and multiple access scheme, named as codetime division multiple access- pulse position modulation (CTDMA-PPM): a form of PPM which is keyed according to a spreading sequence, and in which the duty cycle is subject to pulse width modulation (PWM) according to the required lighting setting. Our scheme considers illumination constraints in addition to the communication requirements and, to our best knowledge, it has not been addressed by other optical modulation methods. Based on the proposed modulation method and multiple access schemes, we develop a system structure, which includes illumination sources, a sensor receiver and a control system. Illumination sources illuminate the environment and transmit information, simultaneously. According to our theoretical analysis, this system structure could support a number of luminaries equal to the size of the CDMA codebook times the dimming range. I

The Need for Laboratory Measurements and Ab Initio Studies to Aid Understanding of Exoplanetary Atmospheres

We are now on a clear trajectory for improvements in exoplanet observations that will revolutionize our ability to characterize their atmospheric structure, composition, and circulation, from gas giants to rocky planets. However, exoplanet atmospheric models capable of interpreting the upcoming observations are often limited by insufficiencies in the laboratory and theoretical data that serve as critical inputs to atmospheric physical and chemical tools. Here we provide an up-to-date and condensed description of areas where laboratory and/or ab initio investigations could fill critical gaps in our ability to model exoplanet atmospheric opacities, clouds, and chemistry, building off a larger 2016 white paper, and endorsed by the NAS Exoplanet Science Strategy report. Now is the ideal time for progress in these areas, but this progress requires better access to, understanding of, and training in the production of spectroscopic data as well as a better insight into chemical reaction kinetics both thermal and radiation-induced at a broad range of temperatures. Given that most published efforts have emphasized relatively Earth-like conditions, we can expect significant and enlightening discoveries as emphasis moves to the exotic atmospheres of exoplanets.Comment: Submitted as an Astro2020 Science White Pape