Emerging drone trends for blockchain-based 5G networks: open issues and future perspectives

Han, Tao, Ribeiro, Igor de L, Magaia, Naercio, Preto, Joäo, Segundo, Afonso H Fontes N, De Macedo, Antônio Roberto L, Muhammad, Khan and De Albuquerque, Victor Hugo C (2021) Emerging drone trends for blockchain-based 5G networks: open issues and future perspectives. IEEE Network, 35 (1). pp. 38-43. ISSN 0890-8044

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Unmanned aerial vehicles, commonly known as drones, are receiving growing research interest due to their ability to carry a multitude of sensors and to connect to mobile networks. They are also able to move freely across the air, which enables the creation of numerous applications that were until now considered impracticable. However, such applications may require high computational resources, reliable connection, and high data transmission rates to accomplish different tasks. Therefore, in this work, first, we discuss 5G communication networks and mobile edge computing (MEC) as promising technologies that can provide several benefits to drone-enabled environments and solve some of the presented issues. We also comment on 5G and MEC approaches, presenting the state of the art and seeking to solve each of the latter issues presented. Afterward, we introduce new security concerns of drone communication networks, given their recent popularity. These concerns are related to the possibility of malicious users taking advantage of this brand new technology, which has made many governments ban drones due to public safety. Next, blockchain technology is brought in as a novel solution to the security issues due to its decentralized nature, making it inherently safe. This article also surveys contributions that make use of each of the technologies mentioned to improve the emerging drone industry. Subsequently, we discuss open issues and future perspectives.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 28 Oct 2021 08:01
Last Modified: 28 Oct 2021 11:07
URI: http://sro.sussex.ac.uk/id/eprint/102537

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