The Internet of Flying Things

Pigatto, Daniel Fernando; Rodrigues, Marcos Vinícius; Fontes, João Vitor de Carvalho; Pinto, Alex Sandro Roschildt; Smith, James E.; Branco, Kalinka Regina Lucas Jaquie Castelo

doi:10.1002/9781119456735.ch19

Cited by 15 publications

(10 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, we assume that there are four locations, whose coordinates are as follows: location 1 (-400, -400), location 2 (400, -400), location 3 (400, 400), and location 4 (-400, 400). Synchronously, every two UAVs fly from location n to (n mod 4) + 1, n ∈ [1,4]. Given the predefined path, if one UAV does not have sufficient time to reach the location of b, it will directly fly to the final location.…”

Section: Simulation Results and Performance Analysismentioning

confidence: 99%

“…The Flying Ad Hoc Networks (FANETs) paradigm has emerged by exploring the cooperation and collaboration between the UAVs [3]. Recently, some researchers have started to investigate the integration of FANETs into the IoT, which has led to the Internet of Flying Things (IoFT) [4]. The emergent IoFT aims at bringing the potential new degree of freedom into IoT, by utilizing the flexible mobility and deployment of UAVs.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Popular Matching for Security-Enhanced Resource Allocation in Social Internet of Flying Things

Wang

Sun

Duong

et al. 2020

IEEE Trans. Commun.

View full text Add to dashboard Cite

As the Internet of Things (IoT) is maturing and acquires its social flavor, the Social IoT enables smart devices to build inter-thing social networks without human intervention. As a new form of smart devices, unmanned aerial vehicles (UAVs) are finding their way into IoT applications. The integrated Social Internet of Flying Things (SIoFT) can provide the socialaware UAV-assisted services. However, the broadcast nature of air-to-ground (A2G) channels makes them vulnerable to being eavesdropped by terrestrial malicious users due to their strong line-of-sight (LoS) links. In this paper, we investigate to ensure the security of A2G communications when the location information of multiple potential eavesdroppers cannot be perfectly estimated. Following the "no pain no gain" principle, the terrestrial users who reuse the UAV cellular spectrum will act as friendly jammers to realize "win-win" situation. Hence, joint trajectory design, power control, and channel allocation optimization problem is formulated to maximize the average secrecy rate of UAVs in worst case. In the first stage, we utilize the block coordinate descent method and successive convex optimization method to solve the trajectory design and power control problems in an iterative manner. In the second stage, we convert the user pairing problem into a popular matching problem with externalities. Two distributed algorithms are proposed to maintain the popular matching under dynamics. Moreover, we conduct detailed analysis of the popularity, convergence, and computational complexity. Simulation results demonstrate the superiority of our proposed method in terms of different performance metrics.

show abstract

Section: Simulation Results and Performance Analysismentioning

confidence: 99%

mentioning

confidence: 99%

Popular Matching for Security-Enhanced Resource Allocation in Social Internet of Flying Things

Wang

Sun

Duong

et al. 2020

IEEE Trans. Commun.

View full text Add to dashboard Cite

show abstract

“…Jamming is an attack in the physical layer which causes a high interference to a spectrum band by overloading it. It may provoke the attacked devices to present an excessive energy consumption due to package retransmission, or even interrupt its communication channel [7]. When a CR is under a jamming attack, it simply understands that spectrum band as being busy or overcrowded, and then it switches its transmission to a new channel, thus avoiding the attack.…”

Section: Securitymentioning

confidence: 99%

“…Location spoofing attacks also happen in the physical layer, and they have become more frequent. It happens when an attacker uses a signal that is stronger than and mimics the attributes of a genuine location satellite signal to spoof the receiver [7]. By using a location spoofing attack, attackers may capture UAVs and/or take control of their flight path.…”

Section: Securitymentioning

confidence: 99%

“…Likewise, while performing their missions, the UAVs may work within an IoT [6] context when equipped with IoT devices. Herewith, the UAVs will form an innovative IoT platform operating in the skies, thus being part of a new concept known as the Internet of Flying Things (IoFT) [7]. For this purpose, UAVs need to support instantaneous and real-time communication, and offer access to high-resolution files (e.g., videos streaming and high-definition images), even if they are in an overcrowded area.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Integrating Cognitive Radio with Unmanned Aerial Vehicles: An Overview

Santana

Cristo

Branco

2021

Sensors

View full text Add to dashboard Cite

Unmanned Aerial Vehicles (UAVs) demand technologies so they can not only fly autonomously, but also communicate with base stations, flight controllers, computers, devices, or even other UAVs. Still, UAVs usually operate within unlicensed spectrum bands, competing against the increasing number of mobile devices and other wireless networks. Combining UAVs with Cognitive Radio (CR) may increase their general communication performance, thus allowing them to execute missions where the conventional UAVs face limitations. CR provides a smart wireless communication which, instead of using a transmission frequency defined in the hardware, uses software transmission. CR smartly uses free transmission channels and/or chooses them according to application’s requirements. Moreover, CR is considered a key enabler for deploying technologies that require high connectivity, such as Smart Cities, 5G, Internet of Things (IoT), and the Internet of Flying Things (IoFT). This paper presents an overview on the field of CR for UAV communications and its state-of-the-art, testbed alternatives for real data experiments, as well as specifications to build a simple and low-cost testbed, and indicates key opportunities and future challenges in the field.

show abstract