Optimal UAV Deployment for Data Collection in Deadline-based IoT Applications

The deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming model (MILP) and then we used a heuristic to solve the time complexity problem. The results obtained in the simulation results indicate the optimal performance of the proposed scheme in terms of energy consumption and the number of used UAVs

Micro air vehicles energy transportation for a wireless power transfer system

The aim of this work is to demonstrate the feasibility use of an Micro air vehicles (MAV) in order to power wirelessly an electric system, for example, a sensor network, using low-cost and open-source elements. To achieve this objective, an inductive system has been modelled and validated to power wirelessly a sensor node using a Crazyflie 2.0 as MAV. The design of the inductive system must be small and light enough to fulfil the requirements of the Crazyflie. An inductive model based on two resonant coils is presented. Several coils are defined to be tested using the most suitable resonant configuration. Measurements are performed to validate the model and to select the most suitable coil. While attempting to minimize the weight at transmitter’s side, on the receiver side it is intended to efficiently acquire and manage the power obtained from the transmitter. In order to prove its feasibility, a temperature sensor node is used as demonstrator. The experiment results show successfully energy transportation by MAV, and wireless power transfer for the resonant configuration, being able to completely charge the node battery and to power the temperature sensor.Peer ReviewedPostprint (published version

Multi-UAV Data Collection Framework for Wireless Sensor Networks

In this paper, we propose a framework design for wireless sensor networks based on multiple unmanned aerial vehicles (UAVs). Specifically, we aim to minimize deployment and operational costs, with respect to budget and power constraints. To this end, we first optimize the number and locations of cluster heads (CHs) guaranteeing data collection from all sensors. Then, to minimize the data collection flight time, we optimize the number and trajectories of UAVs. Accordingly, we distinguish two trajectory approaches: 1) where a UAV hovers exactly above the visited CH; and 2) where a UAV hovers within a range of the CH. The results of this include guidelines for data collection design. The characteristics of sensor nodes' K-means clustering are then discussed. Next, we illustrate the performance of optimal and heuristic solutions for trajectory planning. The genetic algorithm is shown to be near-optimal with only $3.5\%$ degradation. The impacts of the trajectory approach, environment, and UAVs' altitude are investigated. Finally, fairness of UAVs trajectories is discussed.Comment: To be presented at 2019 IEEE Global Communications Conference (Globecom

Mobile Unmanned Aerial Vehicles (UAVs) for Energy-Efficient Internet of Things Communications

In this paper, the efficient deployment and mobility of multiple unmanned aerial vehicles (UAVs), used as aerial base stations to collect data from ground Internet of Things (IoT) devices, is investigated. In particular, to enable reliable uplink communications for IoT devices with a minimum total transmit power, a novel framework is proposed for jointly optimizing the three-dimensional (3D) placement and mobility of the UAVs, device-UAV association, and uplink power control. First, given the locations of active IoT devices at each time instant, the optimal UAVs' locations and associations are determined. Next, to dynamically serve the IoT devices in a time-varying network, the optimal mobility patterns of the UAVs are analyzed. To this end, based on the activation process of the IoT devices, the time instances at which the UAVs must update their locations are derived. Moreover, the optimal 3D trajectory of each UAV is obtained in a way that the total energy used for the mobility of the UAVs is minimized while serving the IoT devices. Simulation results show that, using the proposed approach, the total transmit power of the IoT devices is reduced by 45% compared to a case in which stationary aerial base stations are deployed. In addition, the proposed approach can yield a maximum of 28% enhanced system reliability compared to the stationary case. The results also reveal an inherent tradeoff between the number of update times, the mobility of the UAVs, and the transmit power of the IoT devices. In essence, a higher number of updates can lead to lower transmit powers for the IoT devices at the cost of an increased mobility for the UAVs.Comment: Accepted in IEEE Transactions on Wireless Communications, Sept. 201

Performance of Integrated IoT Network with Hybrid mmWave/FSO/THz Backhaul Link

Establishing end-to-end connectivity of Internet of Things (IoT) network with the core for collecting sensing data from remote and hard-to-reach terrains is a challenging task. In this article, we analyze the performance of an IoT network integrated with wireless backhaul link for data collection. We propose a solution that involves a self-configuring protocol for aggregate node (AN) selection in an IoT network, which sends the data packet to an unmanned aerial vehicle (UAV) over radio frequency (RF) channels. We adopt a novel hybrid transmission technique for wireless backhaul employing opportunistic selections combining (OSC) and maximal ratio combining (MRC) that simultaneously transmits the data packet on mmWave (mW), free space optical (FSO), and terahertz (THz) technologies to take advantage of their complementary characteristics. We employ the decode-and-forward (DF) protocol to integrate the IoT and backhaul links and provide physical layer performance assessment using outage probability and average bit-error-rate (BER) under diverse channel conditions. We also develop simplified expressions to gain a better understanding of the system's performance at high signal-to-noise ratio (SNR). We provide computer simulations to compare different wireless backhaul technologies under various channel and SNR scenarios and demonstrate the performance of the data collection using the integrated link.Comment: This work has been submitted to IEEE for possible publicatio

Efficient Deployment of Small Cell Base Stations Mounted on Unmanned Aerial Vehicles for the Internet of Things Infrastructure

In the Internet of Things networks deploying fixed infrastructure is not always the best and most economical solution. Advances in efficiency and durability of Unmanned Aerial Vehicles (UAV) made flying small cell base stations (BS) a promising approach by providing coverage and capacity in environments where using fixed infrastructure is not economically justified. A key challenge in covering an area with UAV-based small cell BSs is optimal positioning the UAVs to maximize the coverage and minimize the number of required UAVs. In this paper, we propose an optimization problem that helps to determine the number and position of the UAVs. Moreover, to have efficient results in a reasonable time, we propose complementary heuristic methods that effectively reduce the search space. The simulation results show that our proposed method performs better than genetic algorithms

A Survey on Mobile Charging Techniques in Wireless Rechargeable Sensor Networks

The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the MCTs. Next, we introduce an exhaustive taxonomy of the MCTs based on various design attributes and then review the literature by categorizing it into periodic and on-demand charging techniques. In addition, we compare the state-of-the-art MCTs in terms of objectives, constraints, solution approaches, charging options, design issues, performance metrics, evaluation methods, and limitations. Finally, we highlight some potential directions for future research

Data collection of mobile sensor networks by drones

Data collection by autonomous mobile sensor arrays can be coupled with the use of drones which provide a low-cost, easily deployable backhauling solution. These means of collection can be used to organize temporary events (sporting or cultural) or to carry out operations in difficult or hostile terrain. The aim of this thesis is to propose effective solutions for communication between both mobile sensors on the ground and on the edge-to-ground link. For this purpose, we are interested in scheduling communications, routing and access control on the sensor / drone link, the mobile collector. We propose an architecture that meets the constraints of the network. The main ones are the intermittence of the links and therefore the lack of connectivity for which solutions adapted to the networks tolerant to the deadlines are adopted. Given the limited opportunities for communication with the drone and the significant variation in the physical data rate, we proposed scheduling solutions that take account of both the contact time and the physical flow rate. Opportunistic routing is also based on these two criteria both for the selection of relay nodes and for the management of queues. We wanted to limit the overhead and propose efficient and fair solutions between mobile sensors on the ground. The proposed solutions have proved superior to conventional scheduling and routing solutions. Finally, we proposed a method of access combining a random access with contention as well as an access with reservation taking into account the aforementioned criteria. This flexible solution allows a network of dense mobile sensors to get closer to the performance obtained in an oracle mode. The proposed solutions can be implemented and applied in different application contexts for which the ground nodes are mobile or easily adapted to the case where the nodes are static