298 research outputs found
On the Convergence of Blockchain and Internet of Things (IoT) Technologies
The Internet of Things (IoT) technology will soon become an integral part of
our daily lives to facilitate the control and monitoring of processes and
objects and revolutionize the ways that human interacts with the physical
world. For all features of IoT to become fully functional in practice, there
are several obstacles on the way to be surmounted and critical challenges to be
addressed. These include, but are not limited to cybersecurity, data privacy,
energy consumption, and scalability. The Blockchain decentralized nature and
its multi-faceted procedures offer a useful mechanism to tackle several of
these IoT challenges. However, applying the Blockchain protocols to IoT without
considering their tremendous computational loads, delays, and bandwidth
overhead can let to a new set of problems. This review evaluates some of the
main challenges we face in the integration of Blockchain and IoT technologies
and provides insights and high-level solutions that can potentially handle the
shortcomings and constraints of both IoT and Blockchain technologies.Comment: Includes 11 Pages, 3 Figures, To publish in Journal of Strategic
Innovation and Sustainability for issue JSIS 14(1
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
Drone Small Cells in the Clouds: Design, Deployment and Performance Analysis
The use of drone small cells (DSCs) which are aerial wireless base stations
that can be mounted on flying devices such as unmanned aerial vehicles (UAVs),
is emerging as an effective technique for providing wireless services to ground
users in a variety of scenarios. The efficient deployment of such DSCs while
optimizing the covered area is one of the key design challenges. In this paper,
considering the low altitude platform (LAP), the downlink coverage performance
of DSCs is investigated. The optimal DSC altitude which leads to a maximum
ground coverage and minimum required transmit power for a single DSC is
derived. Furthermore, the problem of providing a maximum coverage for a certain
geographical area using two DSCs is investigated in two scenarios; interference
free and full interference between DSCs. The impact of the distance between
DSCs on the coverage area is studied and the optimal distance between DSCs
resulting in maximum coverage is derived. Numerical results verify our
analytical results on the existence of optimal DSCs altitude/separation
distance and provide insights on the optimal deployment of DSCs to supplement
wireless network coverage
Efficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage
In this paper, the efficient deployment of multiple unmanned aerial vehicles
(UAVs) with directional antennas acting as wireless base stations that provide
coverage for ground users is analyzed. First, the downlink coverage probability
for UAVs as a function of the altitude and the antenna gain is derived. Next,
using circle packing theory, the three-dimensional locations of the UAVs is
determined in a way that the total coverage area is maximized while maximizing
the coverage lifetime of the UAVs. Our results show that, in order to mitigate
interference, the altitude of the UAVs must be properly adjusted based on the
beamwidth of the directional antenna as well as coverage requirements.
Furthermore, the minimum number of UAVs needed to guarantee a target coverage
probability for a given geographical area is determined. Numerical results
evaluate the various tradeoffs involved in various UAV deployment scenarios.Comment: Accepted in the IEEE Communications Letter
Wireless Communication using Unmanned Aerial Vehicles (UAVs): Optimal Transport Theory for Hover Time Optimization
In this paper, the effective use of flight-time constrained unmanned aerial
vehicles (UAVs) as flying base stations that can provide wireless service to
ground users is investigated. In particular, a novel framework for optimizing
the performance of such UAV-based wireless systems in terms of the average
number of bits (data service) transmitted to users as well as UAVs' hover
duration (i.e. flight time) is proposed. In the considered model, UAVs hover
over a given geographical area to serve ground users that are distributed
within the area based on an arbitrary spatial distribution function. In this
case, two practical scenarios are considered. In the first scenario, based on
the maximum possible hover times of UAVs, the average data service delivered to
the users under a fair resource allocation scheme is maximized by finding the
optimal cell partitions associated to the UAVs. Using the mathematical
framework of optimal transport theory, a gradient-based algorithm is proposed
for optimally partitioning the geographical area based on the users'
distribution, hover times, and locations of the UAVs. In the second scenario,
given the load requirements of ground users, the minimum average hover time
that the UAVs need for completely servicing their ground users is derived. To
this end, first, an optimal bandwidth allocation scheme for serving the users
is proposed. Then, given this optimal bandwidth allocation, the optimal cell
partitions associated with the UAVs are derived by exploiting the optimal
transport theory. Results show that our proposed cell partitioning approach
leads to a significantly higher fairness among the users compared to the
classical weighted Voronoi diagram. In addition, our results reveal an inherent
tradeoff between the hover time of UAVs and bandwidth efficiency while serving
the ground users
Optimal Transport Theory for Cell Association in UAV-Enabled Cellular Networks
In this paper, a novel framework for delay-optimal cell association in
unmanned aerial vehicle (UAV)-enabled cellular networks is proposed. In
particular, to minimize the average network delay under any arbitrary spatial
distribution of the ground users, the optimal cell partitions of UAVs and
terrestrial base stations (BSs) are determined. To this end, using the powerful
mathematical tools of optimal transport theory, the existence of the solution
to the optimal cell association problem is proved and the solution space is
completely characterized. The analytical and simulation results show that the
proposed approach yields substantial improvements of the average network delay.Comment: Accepted in IEEE Communications Letter
Unmanned Aerial Vehicle with Underlaid Device-to-Device Communications: Performance and Tradeoffs
In this paper, the deployment of an unmanned aerial vehicle (UAV) as a flying
base station used to provide on the fly wireless communications to a given
geographical area is analyzed. In particular, the co-existence between the UAV,
that is transmitting data in the downlink, and an underlaid device-todevice
(D2D) communication network is considered. For this model, a tractable
analytical framework for the coverage and rate analysis is derived. Two
scenarios are considered: a static UAV and a mobile UAV. In the first scenario,
the average coverage probability and the system sum-rate for the users in the
area are derived as a function of the UAV altitude and the number of D2D users.
In the second scenario, using the disk covering problem, the minimum number of
stop points that the UAV needs to visit in order to completely cover the area
is computed. Furthermore, considering multiple retransmissions for the UAV and
D2D users, the overall outage probability of the D2D users is derived.
Simulation and analytical results show that, depending on the density of D2D
users, optimal values for the UAV altitude exist for which the system sum-rate
and the coverage probability are maximized. Moreover, our results also show
that, by enabling the UAV to intelligently move over the target area, the total
required transmit power of UAV while covering the entire area, is minimized.
Finally, in order to provide a full coverage for the area of interest, the
tradeoff between the coverage and delay, in terms of the number of stop points,
is discussed.Comment: accepted in the IEEE Transactions on Wireless Communication
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