Intelligent beaconless geographical forwarding for urban vehicular environments

A Vehicular Ad hoc Network is a type of wireless ad hoc network that facilitates ubiquitous connectivity between vehicles in the absence of fixed infrastructure. Source based geographical routing has been proven to perform well in unstable vehicular networks. However, these routing protocols leverage beacon messages to update the positional information of all direct neighbour nodes. As a result, high channel congestion or problems with outdated neighbour lists may occur. To this end, we propose a street-aware, Intelligent Beaconless (IB) geographical forwarding protocol based on modified 802.11 Request To Send (RTS)/ Clear To Send frames, for urban vehicular networks. That is, at the intersection, each candidate junction node leverage digital road maps as well as distance to destination, power signal strength of the RTS frame and direction routing metrics to determine if it should elect itself as a next relay node. For packet forwarding between Intersections, on the other hand, the candidate node considers the relative direction to the packet carrier node and power signal strength of the RTS frame as routing metrics to elect itself based on intelligently combined metrics. After designing the IB protocol, we implemented it and compared it with standard protocols. The simulation results show that the proposed protocol can improve average delay and successful packet delivery ratio in realistic wireless channel conditions and urban vehicular scenarios.     

UAV-IoT collaboration: Energy and time-saving task scheduling scheme

UAVs are capable of providing significant potential to IoT devices through sensors, cameras, GPS systems, and so forth. Therefore, the smart UAV-IoT collaborative system has become a current hot research topic. However, other concerns require in-depth investigation and study, such as resource allocation, security, privacy preservation, trajectory optimization, intelligent decision-making, energy harvesting, and so forth. Here, we suggest a task-scheduling method that splits IoT devices into distinct clusters based on physical proximity and saves time and energy. Cluster heads can apply an auto regressive moving average (ARMA) model to predict intelligently the timestamp of the arrival of the next task and associated estimated payments. Based on the overall expected payment, a cluster head can smartly advise the UAV about its time of next arrival. According to the findings of the simulation, the proposed ETTS algorithm significantly outperforms Task TSIE and TDMA-WS in terms of energy use (67%) and delays (36%).     

Adaptive energy aware cluster-based routing protocol for wireless sensor networks

Wireless sensor networks (WSNs) have grown excessively due to their various applications and low installation cost. In WSN, the main concern is to reduce energy consumption among nodes while maintaining timely and reliable data forwarding. However, most of the existing energy aware routing protocols incur unbalanced energy consumption, which results in inefficient load balancing and compromised network lifetime. Therefore, the main target of this research paper is to present adaptive energy aware cluster-based routing (AECR) protocol for improving energy conservation and data delivery performance. Our proposed AECR protocol differs from other energy efficient routing schemes in some aspects. Firstly, it generates balance sized clusters based on nodes distribution and avoids random clusters formation. Secondly, it optimizes both intra-cluster and inter-cluster routing paths for improving data delivery performance while balancing data traffic on constructed forwarding routes and at the end, in order to reduce the excessive energy consumption and improving load distribution, the role of Cluster Head (CH) is shifted dynamically among nodes by exploit of network conditions. Simulation results demonstrate that AECR protocol outperforms state of the art in terms of various performance metrics.

     

Fabrication and characterization of a low frequency electromagnetic energy harvester

This paper presents the fabrication and characterization of an AA size electromagnetic energy transducer based on vibration. A magnetic spring technique is used to scavenge energy from low frequency external vibration. The output of the harvester is maximized by optimizing the mass of moving and fixed magnets, coil width, coil position and load resistance through a comprehensive experimental analysis. The prototype can generate an open circuit voltage of 3.961 V and 1.18 mW average power at a load resistance of 97 Ω with 9 Hz resonance frequency and 0.5 mm displacement.     

Spectrum Sensing for Cognitive Radio Using Binary Particle Swarm Optimization

Spectrum sensing techniques in cognitive radio are the most important issue to exploit the spectrum efficiently. Several techniques have been proposed recently to estimate the dimension of the received signal from which the vacant frequencies can be determined and made available to the secondary users. These techniques have difficulties in low signal to noise ratio and limited sensing interval cases. It is known that the Maximum Likelihood Estimation (MLE) has an outstanding performance in most practical scenarios. In this paper, we present a Maximum Likelihood Estimate (MLE) to detect the number of vacant channels in the spectrum. The resulting MLE estimate posses several minima and maxima, therefore it needs exhaustive search to be determined accurately. To solve the problem, an evolutionary algorithm called Binary Particle Swarm Optimization (BPSO) is proposed. Simulation results have shown significant improvement of the MLE-BPSO estimate over the conventional techniques by 3–5 dB.     

Projected Mushroom Type Phase-Change Memory

Phase-change memory devices have found applications in in-memory computing where the physical attributes of these devices are exploited to compute in places without the need to shuttle data between memory and processing units. However, nonidealities such as temporal variations in the electrical resistance have a detrimental impact on the achievable computational precision. To address this, a promising approach is projecting the phase configuration of phase change material onto some stable element within the device. Here, the projection mechanism in a prominent phase-change memory device architecture, namely mushroom-type phase-change memory, is investigated. Using nanoscale projected Ge₂Sb₂Te₅ devices, the key attributes of state-dependent resistance, drift coefficients, and phase configurations are studied, and using them how these devices fundamentally work is understood.     

Effect of Se Substitution on Structural and Electrical Transport Properties of Bi0.4Sb1.6Se3x Te3(1−x) Hexagonal Rods

In the current study, novel hexagonal rods based on Bi_0.4Sb_1.6Te₃ ingots dispersed with x amount of Se (x = 0.0, 0.2, 0.4, 0.6, 0.8, and 1.0) in the form Bi_0.4Sb_1.6Se_3x Te_3(1?x) were synthesized via a standard solid-state microwave route. The morphologies of these rods were explored using field-emission scanning electron microscopy (FESEM). The crystal structure of the powders was examined by x-ray diffraction (XRD) analysis, which showed that powders of the 0.0 ≤ x ≤ 0.8 samples could be indexed to the rhombohedral phase, whereas the sample with x = 1.0 had an orthorhombic phase structure. The influence of variations in the Se content on the thermoelectric properties was studied in the temperature range from 300 K to 523 K. Alloying of Se into Bi_0.4Sb_1.6Te₃ effectively caused a decrease in the hole concentration and, thus, a decrease in the electrical conductivity and an increase in the Seebeck coefficient. The maximal power factor measured in the present work was 7.47 mW/mK² at 373 K for the x = 0.8 sample.     

Exact Error Rate Analysis of MIMO-MRC System under Cochannel Interference and Imperfect Channel State Information

In this paper, we derive closed-form solution for the bit error rate of multi-input multi-output (MIMO) system with maximum ratio combining. We consider binary PSK modulation suffers from cochannel interference (CCI) and imperfect channel state information (CSI). We assume a propagation model wherein the desired and interfering signals undergo independent and identically distributed (i.i.d.) Rayleigh fading channels. Furthermore, the signal-to-noise ratio (SNR) gain penalty caused by the interference signals and the root mean square of the CSI were demonstrated. The numerical results presented in this paper demonstrate the system performance under very realistic propagation and detection conditions including MIMO system, CCI, imperfect CSI, generalized fading channels, and AWGN. Hence our results are expected to be of significant practical use for such scenarios.     

Fabrication and characterization of Pb1−xYbxTe-based alloy thin-film thermoelectric generators grown by thermal evaporation technique

In this study p-Pb_0.925Yb_0.075Te:Te and n-Pb_0.94Yb_0.06Te powders synthesized by solid-state microwave technique were used to fabricate thermally evaporated thin films. The nanostructure and composition of the films were studied using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectroscopy (EDX). Electrical characterizations of the as-deposited films in terms of the Seebeck coefficient and electrical conductivity and power factor were conducted at a range of 298 K to 523 K. The microthermoelectric devices were composed of 20-pair and 10-pair p-Pb_0.925Yb_0.075Te:Te and n-Pb_0.94Yb_0.06Te thin films on glass substrates. The dimensions of the thin-film thermoelectric generators, which consisted of 20-pair and 10-pair legs connected by aluminum electrodes, were 23 mm×20 mm and 12 mm×10 mm, respectively. The 20-pair p–n thermocouples in series generated a maximum open-circuit voltage output (V_oc) of 0.581 V and a maximum output power of 25.87×10^?8 W at a temperature difference ΔT=164 K, whereas the 10-pair p–n thermocouples generated 0.311 V and 13.71×10^?8 W maximum V_oc and maximum output power, respectively, at ΔT=164 K.     

A fuzzy logic approach to beaconing for vehicular ad hoc networks

Vehicular Ad Hoc Network (VANET) is an emerging field of technology that allows vehicles to communicate together in the absence of fixed infrastructure. The basic premise of VANET is that in order for a vehicle detect other vehicles in the vicinity. This cognizance, awareness of other vehicles, can be achieved through beaconing. In the near future, many VANET applications will rely on beaconing to enhance information sharing. Further, the uneven distribution of vehicles, ranging from dense rush hour traffic to sparse late night volumes creates a pressing need for an adaptive beaconing rate control mechanism to enable a compromise between network load and precise awareness between vehicles. To this end, we propose an intelligent Adaptive Beaconing Rate (ABR) approach based on fuzzy logic to control the frequency of beaconing by taking traffic characteristics into consideration. The proposed ABR considers the percentage of vehicles traveling in the same direction, and status of vehicles as inputs of the fuzzy decision making system, in order to tune the beaconing rate according to the vehicular traffic characteristics. To achieve a fair comparison with fixed beaconing schemes, we have implemented ABR approach in JIST/SWANs. Our simulation shows that the proposed ABR approach is able to improve channel load due to beaconing, improve cooperative awareness between vehicles and reduce average packet delay in lossy/lossless urban vehicular scenarios.