Flying ad-hoc network application scenarios and mobility models

Bujari, Armir; Calafate, Carlos T.; Cano, Juan-Carlos; Manzoni, Pietro; Palazzi, Claudio E.; Ronzani, Daniele

doi:10.1177/1550147717738192

Cited by 121 publications

(62 citation statements)

References 46 publications

(52 reference statements)

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“…In FANET, the choice of suitable mobility model is essential to obtain results with maximum precision and conformity due to the agile motion of UAVs. In this context, mobility models are classified into five classes: purely randomized, time-dependent, path planned, group, and hybrid [45]. In order to patrol a specific region, there are many situations where a group of UAVs move together following a common point in the FANET system.…”

Section: Mobility Modelmentioning

confidence: 99%

A Hybrid Communication Scheme for Efficient and Low-Cost Deployment of Future Flying Ad-Hoc Network (FANET)

Khan

Qureshi

Khanzada³

2019

Drones

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In recent years, FANET-related research and development has doubled, due to the increased demands of unmanned aerial vehicles (UAVs) in both military and civilian operations. Equipped with more capabilities and unique characteristics, FANET is able to play a vital role in mission-critical applications. However, these distinctive features enforce a series of guidelines to be considered for its efficient deployment. Particularly, the use of FANET for on-time data communication services presents demanding challenges in terms of energy efficiency and quality of service (QoS). Proper use of communication architecture and wireless technology will assist to solve these challenges. Therefore, in this paper, we review different communication architectures, including the existing wireless technologies, in order to provide seamless wireless connectivity. Based on the discussions, we conclude that a multi-layer UAV ad-hoc network is the most suitable architecture for networking a group of heterogeneous UAVs, while Bluetooth 5 (802.15.1) is the most favored option because of its low-cost, low power consumption, and longer transmission range for FANET. However, 802.15.1 has the limitation of a lower data rate as compared to Wi-Fi (802.11). Therefore, we propose a hybrid wireless communication scheme so as to utilize the features of the high data transmission rate of 802.11 and the low-power consumption of 802.15.1. The proposed scheme significantly reduces communication cost and improves the network performance in terms of throughput and delay. Further, simulation results using the Optimized Network Engineering Tool (OPNET) further support the effectiveness of our proposed scheme.

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Section: Mobility Modelmentioning

confidence: 99%

A Hybrid Communication Scheme for Efficient and Low-Cost Deployment of Future Flying Ad-Hoc Network (FANET)

Khan

Qureshi

Khanzada³

2019

Drones

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“…Table 1 summarizes papers conducting surveys on FANETs, covering various foci, which are self-explanatory given examples, as follows: Open issues, such as enhancing QoS and addressing the dynamicity of network topology. Axel et al [2] 2010 × × × Bauer et al [28] 2011 × × × × Neji et al [29] 2013 × × × × × Bekmezci et al [7] 2013 × × × × × × × × × Ozgur et al [18] 2013 × × × × × × Xie et al [30] 2014 × × × × × × Naser et al [31] 2016 × × × × × × × Gupta et al [32] 2016 × × × × × × × × [34] 2017 × × × × × × Omar et al [35] 2017 × × × × × × × × Zeeshan et al [36] 2018 × × × × × × Khan et al [37] 2018 × × × × × × × Antonio et al [38] 2018 × × × × × × Kaur et al [39] 2018 × × × × × × × Otto et al [40] 2018 × × × × × × × × Jinfang et al [41] 2018 × × × × × × Our paper 2019 × × × × × × × × × × × × × A cross × indicates that the option, which is represented by the column, applies to the reference, which is represented by the row.…”

Section: Our Contributionmentioning

confidence: 99%

Routing Schemes in FANETs: A Survey

Khan

Yau

Noor

et al. 2019

Sensors

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Flying ad hoc network (FANET) is a self-organizing wireless network that enables inexpensive, flexible, and easy-to-deploy flying nodes, such as unmanned aerial vehicles (UAVs), to communicate among themselves in the absence of fixed network infrastructure. FANET is one of the emerging networks that has an extensive range of next-generation applications. Hence, FANET plays a significant role in achieving application-based goals. Routing enables the flying nodes to collaborate and coordinate among themselves and to establish routes to radio access infrastructure, particularly FANET base station (BS). With a longer route lifetime, the effects of link disconnections and network partitions reduce. Routing must cater to two main characteristics of FANETs that reduce the route lifetime. Firstly, the collaboration nature requires the flying nodes to exchange messages and to coordinate among themselves, causing high energy consumption. Secondly, the mobility pattern of the flying nodes is highly dynamic in a three-dimensional space and they may be spaced far apart, causing link disconnection. In this paper, we present a comprehensive survey of the limited research work of routing schemes in FANETs. Different aspects, including objectives, challenges, routing metrics, characteristics, and performance measures, are covered. Furthermore, we present open issues.

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“…However, today, the potential uses and applicability of drones in civilian application domains such as air pollution monitoring, 1 package delivery (e.g. Amazon Prime Air), 2 healthcare delivery, 3 environmental monitoring, 4 surveillance, 5 disaster management, [6][7][8][9] search and rescue missions, [10][11][12][13] agriculture (crop and soil condition inspection), 14 industrial service automations, weather, archeology, sport, forest fire monitoring and detection, [15][16][17] traffic monitoring, 18,19 security, tourism (guiding tourists in video recording from different view and photograph taking), remote exploration, mining and infrastructure (geospatial data gathering), illegal fishing monitoring (hunt down illegal boats netting fish), and helping the disabled (through utilizing drone-based audio and video streaming services) are becoming a fast-growing phenomenon.…”

Section: Introductionmentioning

confidence: 99%

Predictive geographic multicast routing protocol in flying ad hoc networks

Hussen

Choi

Park

et al. 2019

International Journal of Distributed Sensor Networks

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In the past decades, the unmanned aerial systems have been utilized only for military operations. However, recently, the potential uses and applicability of unmanned aerial vehicles (commonly known as drones) in civilian application domains are becoming a fast-growing phenomenon. A flying ad hoc network is a wireless ad hoc network specifically designed for the communication of unmanned aerial vehicles. Multicast routing is one of the vital aspects in wireless ad hoc networks. Using multicast transmission approaches, flying ad hoc network applications may need to send the same message to a specific group of flying nodes. The multicast communication approaches can benefit flying ad hoc network applications in conserving the scarce resources of flying nodes. Research works have been proposed to tackle the challenges in multicast routing with multi-hop communication in ad hoc network environments. Nevertheless, the conventional multicast routing mechanisms incur excessive control message overhead when a large number of nodes experience frequent topological changes. A scalable geographic multicast routing mechanism, which specially require localized operation and reduced control packet overhead, is necessary. Multicast routing in flying ad hoc networks is extremely challenging because of the dynamic topology changes and network disconnection resulted from frequent mobility of nodes. In this article, we present and implement a scalable and predictive geographic multicast routing mechanism in flying ad hoc networks. In uniform and random deployment scenarios, the MATLAB-based evaluation result has revealed that when the communication range increases, the probability of finding one-hop predicted forwarders to reach multicast destinations also increases. The implementation of scalable and predictive geographic multicast routing mechanism in flying ad hoc network is done using Optimizing Network Engineering Tools Modeler 16.0. We have added the scalable and predictive geographic multicast routing mechanism in flying ad hoc network as a new routing scheme in the Mobile Ad hoc Network routing protocol groups of the Optimizing Network Engineering Tools Modeler. Then, the performance of scalable and predictive geographic multicast routing mechanism in flying ad hoc network is compared with two of the existing Mobile Ad hoc Network routing protocols (Geographic Routing Protocol and Dynamic Source Routing). Eventually, we present two instance scenarios regarding the integration of scalable and predictive geographic multicast routing mechanism in flying ad hoc network scheme in the Internet of Things platform.

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Flying ad-hoc network application scenarios and mobility models

Cited by 121 publications

References 46 publications

A Hybrid Communication Scheme for Efficient and Low-Cost Deployment of Future Flying Ad-Hoc Network (FANET)

A Hybrid Communication Scheme for Efficient and Low-Cost Deployment of Future Flying Ad-Hoc Network (FANET)

Routing Schemes in FANETs: A Survey

Predictive geographic multicast routing protocol in flying ad hoc networks

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