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  1. Ghate, A. ; Krishnaiyer, K. ; Paynabar, K. (Ed.)
    This study presents a two-stage stochastic aggregate production planning model to determine the optimal renewable generation capacity, production plan, workforce levels, and machine hours that minimize a production system’s operational cost. The model considers various uncertainties, including demand for final products, machine and labor hours available, and renewable power supply. The goal is to evaluate the feasibility of decarbonizing the manufacturing, transportation, and warehousing operations by adopting onsite wind turbines and solar photovoltaics coupled with battery systems assuming the facilities are energy prosumers. First-stage decisions are the siting and sizing of wind and solar generation, battery capacity, production quantities, hours of labor to keep, hire, or layoff, and regular, overtime, and idle machine hours to allocate over the planning horizon. Second-stage recourse actions include storing products in inventory, subcontracting or backorder, purchasing or selling energy to the main grid, and daily charging or discharging energy in the batteries in response to variable generation. Climate analytics performed in San Francisco and Phoenix permit to derive capacity factors for the renewable energy technologies and test their implementation feasibility. Numerical experiments are presented for three instances: island microgrid without batteries, island microgrid with batteries, and grid-tied microgrid for energy prosumer. Results show favorablemore »levelized costs of energy that are equal to USD48.37/MWh, USD64.91/MWh, and USD36.40/MWh, respectively. The model is relevant to manufacturing companies because it can accelerate the transition towards eco-friendly operations through distributed generation.« less
  2. The Internet of Things (IoT) devices exchange certificates and authorization tokens over the IEEE 802.15.4 radio medium that supports a Maximum Transmission Unit (MTU) of 127 bytes. However, these credentials are significantly larger than the MTU and are therefore sent in a large number of fragments. As IoT devices are resource-constrained and battery-powered, there are considerable computations and communication overheads for fragment processing both on sender and receiver devices, which limit their ability to serve real-time requests. Moreover, the fragment processing operations increase energy consumption by CPUs and radio-transceivers, which results in shorter battery life. In this article, we propose CATComp -a compression-aware authorization protocol for Constrained Application Protocol (CoAP) and Datagram Transport Layer Security (DTLS) that enables IoT devices to exchange smallsized certificates and capability tokens over the IEEE 802.15.4 media. CATComp introduces additional messages in the CoAP and DTLS handshakes that allow communicating devices to negotiate a compression method, which devices use to reduce the credentials’ sizes before sending them over an IEEE 802.15.4 link. The decrease in the size of the security materials minimizes the total number of packet fragments, communication overheads for fragment delivery, fragment processing delays, and energy consumption. As such, devices can respond tomore »requests faster and have longer battery life. We implement a prototype of CATComp on Contiki-enabled RE-Mote IoT devices and provide a performance analysis of CATComp. The experimental results show that communication latency and energy consumption are reduced when CATComp is integrated with CoAP and DTLS.« less
  3. The increasing use of light emitting diodes (LED) and light receptors such as photodiodes and cameras in vehicles motivates the use of visible light communication (VLC) for inter–vehicular networking. However, the mobility of the vehicles presents a fundamental impediment for high throughput and link sustenance in vehicular VLC. While prior work has explored vehicular VLC system design, yet, there is no clear understanding on the amount of motion of vehicles in real world vehicular VLC use–case scenarios. To address this knowledge gap, in this paper, we present a mobility characterization study through extensive experiments in real world driving scenarios. We characterize motion using a constantly illuminated transmitter on a lead vehicle and a multi–camera setup on a following vehicle. The observations from our experiments reveal key insights on the degree of relative motion of a vehicle along its spatial axis and different vehicular motion behaviors. The motion characterization from this work lays a stepping stone to addressing mobility in vehicular VLC.
  4. Theoretical models estimate visible light communication (VLC) data capacity to be of the order of Tera-bits-per-second (Tbps). However, practical limitations in receiver designs have limited state-of-the-art VLC prototypes to (multiple) orders of magnitude lower data rates. This paper explores a new architecture to realize ultra-high data rates in visible light communication systems by dramatically improving the Signal-to-Interference-Noise-Ratio (SINR) at the receiver. The key idea is to leverage the fast sampling rates of photodiode receivers and integrate a shutter mechanism that filters noise and interference thus creating a high-speed imaging receiver effect. Through adaptive selection of the exact receiver area over which the transmitted light is detected, the SINR can be dramatically increased yet not compromising the high sampling rate achievable using state-of-the-art photoreceptors. In addition to introducing the new hybrid architecture for high SINR reception, in this paper, we study the feasibility of noise and interference reduction through a proof-of-concept experimentation.