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UAV Networks Challenges: Towards More Scalable, Secure, Energy-Efficient, and Smart IoT Networks

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Unmanned Aerial Vehicle (UAV) networks have become very popular for improving the flexibility of future wireless networks. However, despite the great attention from both the research community and the industry, UAV networks still face many challenges that may hinder their implementation in the near future. This article provides a review of the challenges that remain prominent in regard to UAV networks. The main argument here is that UAV networks are still facing major issues in terms of practical implementation and deployment, suggesting that alternative solutions are needed to complement UAVs to realize such networks while mitigating their problems. To better demonstrate this argument, after discussing the various difficulties facing the implementation of UAV networks, this study provides an example of a new framework to complement traditional UAV networks, namely, the Self-Organized Linearly Moving Transmitter-Assisted Serving and Sensing Network (SOLMTS2N). The suggested framework addresses some of the challenges inherent in UAV networks, such as the complexity of optimization, cost, service interruption, and acoustic noise. In the proposed framework, a group of Linearly Moving Sensing Transmitters (LMSTs) is sliding over a linear platform to cover a set of both normal users and/or IoT devices. LMSTs provide localization, computing, and communication services to all users in the covered area. The proposed framework is expected to improve several performance aspects of traditional UAV networks, such as scalability, security, cost, and service continuity, which makes it more suitable for IoT applications. The article provides an overview of the new framework, its advantages compared to UAV networks, the challenges that may still be facing the deployment of such a framework, and some applications.
Title: UAV Networks Challenges: Towards More Scalable, Secure, Energy-Efficient, and Smart IoT Networks
Description:
Unmanned Aerial Vehicle (UAV) networks have become very popular for improving the flexibility of future wireless networks.
However, despite the great attention from both the research community and the industry, UAV networks still face many challenges that may hinder their implementation in the near future.
This article provides a review of the challenges that remain prominent in regard to UAV networks.
The main argument here is that UAV networks are still facing major issues in terms of practical implementation and deployment, suggesting that alternative solutions are needed to complement UAVs to realize such networks while mitigating their problems.
To better demonstrate this argument, after discussing the various difficulties facing the implementation of UAV networks, this study provides an example of a new framework to complement traditional UAV networks, namely, the Self-Organized Linearly Moving Transmitter-Assisted Serving and Sensing Network (SOLMTS2N).
The suggested framework addresses some of the challenges inherent in UAV networks, such as the complexity of optimization, cost, service interruption, and acoustic noise.
In the proposed framework, a group of Linearly Moving Sensing Transmitters (LMSTs) is sliding over a linear platform to cover a set of both normal users and/or IoT devices.
LMSTs provide localization, computing, and communication services to all users in the covered area.
The proposed framework is expected to improve several performance aspects of traditional UAV networks, such as scalability, security, cost, and service continuity, which makes it more suitable for IoT applications.
The article provides an overview of the new framework, its advantages compared to UAV networks, the challenges that may still be facing the deployment of such a framework, and some applications.

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