Graphene-Based Acousto-Optic Sensors with Vibrating Resonance Energy Transfer and Applications

Graphene as a two-dimensional planar material has numerous advantages for realizing high-performance nano-electromechanical systems (NEMS) such as nanoscale sensors including strain sensors, optical modulators or energy harvesters. Large Young’s modulus (1 TPa for single layer graphene), ultra-low weight, low residual stress and large breaking strength properties are important properties as two-dimensional (2D) ultrathin resonators. Graphene resonators are recently utilized for low complexity design of nanoscale acousto-optic sensors based on a novel theoretical model describing vibrating Förster resonance energy transfer (VFRET) mechanism. Proposed system combines the advantages of graphene with quantum dots (QDs) as donor and acceptor pairs with broad absorption spectrum, large cross-sections, tunable emission spectra, size-dependent emission wavelength, high photochemical stability and improved quantum yield. Device structure supporting wide-band resonance frequencies including acoustic and ultrasound ranges promises high-performance applications for challenging environments. Remote sensors and acousto-optic communication channels are formed for in-body applications, wireless body area sensor networks (WBASNs), space and interplanetary systems, microfluidics and visible light communication (VLC)-based architectures

An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks

A high degree of reliability for critical data transmission is required in body sensor networks (BSNs). However, BSNs are usually vulnerable to channel impairments due to body fading effect and RF interference, which may potentially cause data transmission to be unreliable. In this paper, an adaptive and flexible fault-tolerant communication scheme for BSNs, namely AFTCS, is proposed. AFTCS adopts a channel bandwidth reservation strategy to provide reliable data transmission when channel impairments occur. In order to fulfill the reliability requirements of critical sensors, fault-tolerant priority and queue are employed to adaptively adjust the channel bandwidth allocation. Simulation results show that AFTCS can alleviate the effect of channel impairments, while yielding lower packet loss rate and latency for critical sensors at runtime.Comment: 10 figures, 19 page

Wireless body sensor networks for health-monitoring applications

This is an author-created, un-copyedited version of an article accepted for publication in Physiological Measurement. The publisher is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs