Joint Position and Travel Path Optimization for Energy Efficient Wireless Data Gathering Using Unmanned Aerial Vehicles
Author | Ghorbel, Mahdi Ben |
Author | Rodríguez-Duarte, David |
Author | Ghazzai, Hakim |
Author | Hossain, Md. Jahangir |
Author | Menouar, Hamid |
Available date | 2024-10-20T10:43:21Z |
Publication Date | 2019 |
Publication Name | IEEE Transactions on Vehicular Technology |
Resource | Scopus |
ISSN | 189545 |
Abstract | Unnamed aerial vehicles (UAVs) or drones have attracted growing interest in the last few years for multiple applications; thanks to their advantages in terms of mobility, easy movement, and flexible positioning. In UAV-based communications, mobility and higher line-of-sight probability represent opportunities for the flying UAVs while the limited battery capacity remains its major challenge. Thus, they can be employed for specific applications where their permanent presence is not mandatory. Data gathering from wireless sensor networks is one of these applications. This paper proposes an energy-efficient solution minimizing the UAV and/or sensors energy consumption while accomplishing a tour to collect data from the spatially distributed wireless sensors. The objective is to determine the positions of the UAV 'stops' from which it can collect data from a subset of sensors located in the same neighborhood and find the path that the UAV should follow to complete its data gathering tour in an energy-efficient manner. A non-convex optimization problem is first formulated then, an efficient and low-complex technique is proposed to iteratively achieve a sub-optimal solution. The initial problem is decomposed into three sub-problems: The first sub-problem optimizes the positioning of the stops using linearization. The second one determines the sensors assignment to stops using clustering. Finally, the path among these stops is optimized using the travel salesman problem. Selected numerical results show the behavior of the UAV versus various system parameters and that the achieved energy is considerably reduced compared to the one of existing approaches. |
Sponsor | Manuscript received June 8, 2018; revised November 1, 2018; accepted January 11, 2019. Date of publication January 16, 2019; date of current version March 14, 2019. This work was supported by Grant NPRP#9-257-1-056 from the Qatar National Research Fund (a member of The Qatar Foundation). This paper was presented in part at the IEEE 87th Vehicular Technology Conference, Porto, Portugal, June 2018. The review of this paper was coordinated by Prof. W. Song. (Corresponding author: Mahdi Ben Ghorbel.) M. Ben Ghorbel was with the School of Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada, and now with the Exfo Inc., Quebec City, QC G1M 2K2, Canada (e-mail:,mahdi.ben-ghorbel@exfo.com). |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | 3D positioning path planning unmanned aerial vehicle-based communications wireless sensors |
Type | Conference |
Pagination | 2165-2175 |
Issue Number | 3 |
Volume Number | 68 |
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