Internet of Unmanned Aerial Vehicles: QoS Provisioning in Aerial Ad-Hoc Networks

Kumar, Kirshna; Kumar, Sushil; Kaiwartya, Omprakash; Sikandar, Ajay; Kharel, Rupak; Mauri, Jaime Lloret

doi:10.3390/s20113160

Cited by 30 publications

(23 citation statements)

References 41 publications

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“…The authors of [46,47] studied a drone's ad hoc network for mobility and serviceoriented modeling using various protocols and techniques, such as neuro-fuzzy, and a quality of service provisioning framework for UAV-assisted environments. The results of these innovative approaches have emphasized the significant potential of enabling smart services.…”

Section: Related Workmentioning

confidence: 99%

Modifying Hata-Davidson Propagation Model for Remote Sensing in Complex Environments Using a Multifactional Drone

Almalki

Soufiene

2022

Sensors

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The coupling of drones and IoT is a major topics in academia and industry since it significantly contributes towards making human life safer and smarter. Using drones is seen as a robust approach for mobile remote sensing operations, such as search-and-rescue missions, due to their speed and efficiency, which could seriously affect victims’ chances of survival. This paper aims to modify the Hata-Davidson empirical propagation model based on RF drone measurement to conduct searches for missing persons in complex environments with rugged areas after manmade or natural disasters. A drone was coupled with a thermal FLIR lepton camera, a microcontroller, GPS, and weather station sensors. The proposed modified model utilized the least squares tuning algorithm to fit the data measured from the drone communication system. This enhanced the RF connectivity between the drone and the local authority, as well as leading to increased coverage footprint and, thus, the performance of wider search-and-rescue operations in a timely fashion using strip search patterns. The development of the proposed model considered both software simulation and hardware implementations. Since empirical propagation models are the most adjustable models, this study concludes with a comparison between the modified Hata-Davidson algorithm against other well-known modified empirical models for validation using root mean square error (RMSE). The experimental results show that the modified Hata-Davidson model outperforms the other empirical models, which in turn helps to identify missing persons and their locations using thermal imaging and a GPS sensor.

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Section: Related Workmentioning

confidence: 99%

Modifying Hata-Davidson Propagation Model for Remote Sensing in Complex Environments Using a Multifactional Drone

Almalki

Soufiene

2022

Sensors

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“…Kumar et al [27] proposed a Quality of Service Provisioning framework for a UAV-assisted (QSPU) aerial ad-hoc network environment, focusing on reliable aerial communication. The UAV's aerial mobility and service parameters are modeled taking into consideration the highly dynamic aerial ad-hoc environments.…”

Section: Related Workmentioning

confidence: 99%

EMASS: A Novel Energy, Safety and Mobility Aware-Based Clustering Algorithm for FANETs

2021

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The Unmanned Aerial Vehicles (UAVs), organized as a Flying Ad-hoc NETwork (FANET), are used to make effective remote monitoring in diverse applications. Due to their high mobility, their energy consumption is increasingly affected leading to reduced network stability and communication efficiency. The design of node clustering of a FANET needs to consider the number of UAVs in the vicinity (transmission range) in order to ensure an adaptive reliable routing. Novel clustering schemes have been employed to deal with the highly dynamic flying behavior of UAVs and to maintain network stability. In this context, a new clustering algorithm is proposed to address the fast mobility of UAVs and provide safe inter-UAV distance, stable communication and extended network lifetime. The main contributions of this paper are first to extend and improve important metrics used in two well-known algorithms in the literature namely: The Bio-Inspired Clustering Scheme for FANETs (BICSF) and the Energy Aware Link-based Clustering (EALC). Then, exploiting the improved metrics, an Energy and Mobility-aware Stable and Safe Clustering (EMASS) algorithm, built upon new schemes useful for ensuring stability and safety in FANETs, is proposed. The simulation results showed that the EMASS algorithm outperformed the BICSF and the EALC algorithms in terms of better cluster stability, guaranteed safety, higher packet deliverability, improved energy saving and lower delays.

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“…Application of UAVs in sensor networks and as radio bridges is also of great interest. In [ 15 ], a platform for organizing an ad hoc network using UAVs to achieve the required QoS level and GPSR and AODV is considered. Additionally, the authors of [ 16 , 17 ] proposed using an ad hoc network for UAVs.…”

Section: Related Workmentioning

confidence: 99%

Evaluating the Quality of Experience Performance Metric for UAV-Based Networks

Khakimov

Mokrov

Poluektov

et al. 2021

Sensors

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In this work, we consider a UAV-assisted cell in a single user scenario. We consider the Quality of Experience (QoE) performance metric calculating it as a function of the packet loss ratio. In order to acquire this metric, a radio-channel emulation system was developed and tested under different conditions. The system consists of two independent blocks, separately emulating connections between the User Equipment (UE) and unmanned aerial vehicle (UAV) and between the UAV and Base station (BS). In order to estimate scenario usage constraints, an analytical model was developed. The results show that, in the described scenario, cell coverage can be enhanced with minimal impact on QoE.

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Internet of Unmanned Aerial Vehicles: QoS Provisioning in Aerial Ad-Hoc Networks

Cited by 30 publications

References 41 publications

Modifying Hata-Davidson Propagation Model for Remote Sensing in Complex Environments Using a Multifactional Drone

Modifying Hata-Davidson Propagation Model for Remote Sensing in Complex Environments Using a Multifactional Drone

EMASS: A Novel Energy, Safety and Mobility Aware-Based Clustering Algorithm for FANETs

Evaluating the Quality of Experience Performance Metric for UAV-Based Networks

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