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Decision-based routing for unmanned aerial vehicles and internet of things networks

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posted on 2023-08-22, 13:48 authored by Maisam Ali, Kashif Naseer QureshiKashif Naseer Qureshi, THOMAS NEWETHOMAS NEWE, Kashif Aman, Ashraf Osman Ibrahim, Maha Almujaly, Wamda Nagmeldin

New technologies and communication standards have changed traditional network processes. Internet of Things (IoT) is one of the emerging technologies where devices are connected to facilitate the users. When the networks are more congested due to a large number of users then the existing routing protocol and communication channels suffer from congestion, disconnection, overhead, and packet drop issues. Unmanned Aerial Vehicles (UAVs) are adopted to support the ground networks for more feasible data communication. These networks provide coverage facilities to IoT networks and provide smooth data dissemination services. Through the use of relay and cooperative communication technologies, UAVs could enlarge the communication space for IoT networks. Traditional network routing protocols have been adopted for data communication in these networks. However, the adopted protocols are not able to handle mobility and uncertain network conditions. This paper proposes a Decision-based Routing for Unmanned Aerial Vehicles and Internet of Things (DR-UAVIoT) network. The proposed protocol is useful for UAV-to-IoT and UAV-to?UAV data communication. The performance of the proposed solution is evaluated with the existing protocols in terms of data delivery, delay, and network overhead. The experimental results indicate the better performance of the proposed protocol in terms of less delay, less overhead, and better data delivery ratio as compared with existing routing protocols.

Funding

Confirm Centre for Smart Manufacturing

Science Foundation Ireland

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History

Publication

Applied Sciences, 2023, 13, 2131

Publisher

MDPI

Other Funding information

The APC was funded by the Research Management Centre (RMC), Universiti Malaysia Sabah, through the UMS/PPI-DPJ1 Journal Article Fund. This work was supported, in part, by Science Foundation Ireland grant number 16/RC/3918 to the CONFIRM Science Foundation Ireland Research Centre for Smart Manufacturing and co-funded under the European Regional Devel?opment Fund. This work additionally received support from the Higher Education Authority (HEA) under the Human Capital Initiative-Pillar 3 project, Cyberskills.

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  • (9) Industry, Innovation and Infrastructure

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  • Electronic & Computer Engineering

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