ORIGINAL RESEARCH article
Front. Comput. Sci.
Sec. Networks and Communications
Volume 7 - 2025 | doi: 10.3389/fcomp.2025.1565716
Network Optimization by Regional Computing for UAVs' Big Data
Provisionally accepted
- 1University of Sargodha, Sargodha, Pakistan
- 2Rabdan Academy, Abu Dhabi, United Arab Emirates
- 3University of Jeddah, Jeddah, Saudi Arabia
- 4King Saud University, Riyadh, Riyadh, Saudi Arabia
- 5Skyline University College, Sharjah, United Arab Emirates
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Unmanned Aerial Vehicles (UAVs) are increasingly used in sectors such as surveillance, agriculture, and disaster response, generating massive volumes of real-time big data. Traditional cloud computing introduces high latency, while edge computing suffers from limited scalability. This paper proposes a novel three-layer computing framework incorporating a Regional Computing (RC) layer between UAVs and the cloud. A dynamic offloading strategy is designed to select the optimal computing tier based on network conditions and resource availability. To validate the proposal, we used EdgeCloudSim. Simulation results demonstrate that the RC layer reduces end-to-end processing delays by approximately 80%, lowers operational costs by up to 5× compared to cloud computing, and achieves lower task failure rates relative to edge computing. These findings establish Regional Computing as an efficient and scalable solution bridging the gap between edge and cloud paradigms for UAV big data management.
Keywords: Cloud computing, Edge computing, Offloading, UAV ( unmanned aerial vehicle), Computer network
Received: 27 Jan 2025; Accepted: 23 May 2025.
Copyright: © 2025 Badshah, Daud, Aboulola, Bukhari, Alshemaimri and Dawood. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Afzal Badshah, University of Sargodha, Sargodha, Pakistan
Ali Daud, Rabdan Academy, Abu Dhabi, United Arab Emirates
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.