CQUniversity
Browse
Computing in the sky_A survey on intelligent ubiquitous computing for UAV-assisted 6G networks and industry_CQU.pdf (1.34 MB)

Computing in the sky: A survey on intelligent ubiquitous computing for UAV-assisted 6G networks and industry 4.0/5.0

Download (1.34 MB)
journal contribution
posted on 2023-03-01, 04:20 authored by Saeed Alsamhi, Alexey V Shvetsov, Santosh Kumar, Jahan HassanJahan Hassan, Mohammed A Alhartomi, Svetlana V Shvetsova, Radhya Sahal, Ammar Hawbani
Unmanned Aerial Vehicles (UAVs) are increasingly being used in a high-computation paradigm enabled with smart applications in the Beyond Fifth Generation (B5G) wireless communication networks. These networks have an avenue for generating a considerable amount of heterogeneous data by the expanding number of Internet of Things (IoT) devices in smart environments. However, storing and processing massive data with limited computational capability and energy availability at local nodes in the IoT network has been a significant difficulty, mainly when deploying Artificial Intelligence (AI) techniques to extract discriminatory information from the massive amount of data for different tasks.Therefore, Mobile Edge Computing (MEC) has evolved as a promising computing paradigm leveraged with efficient technology to improve the quality of services of edge devices and network performance better than cloud computing networks, addressing challenging problems of latency and computation-intensive offloading in a UAV-assisted framework. This paper provides a comprehensive review of intelligent UAV computing technology to enable 6G networks over smart environments. We highlight the utility of UAV computing and the critical role of Federated Learning (FL) in meeting the challenges related to energy, security, task offloading, and latency of IoT data in smart environments. We present the reader with an insight into UAV computing, advantages, applications, and challenges that can provide helpful guidance for future research.

History

Volume

6

Issue

7

Start Page

1

End Page

29

Number of Pages

29

eISSN

2504-446X

Publisher

MDPI AG

Additional Rights

CC BY 4.0

Language

en

Peer Reviewed

  • Yes

Open Access

  • Yes

Acceptance Date

2022-07-01

Era Eligible

  • Yes

Journal

Drones

Article Number

177

Usage metrics

    CQUniversity

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC