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Optimization of Resource Allocation in Unmanned Aerial Vehicles Based on Swarm Intelligence Algorithms

Siling Feng1, Yinjie Chen1, Mengxing Huang1,2,*, Feng Shu1

1 School of Information and Communication Engineering, Hainan University, No.58 Renmin Avenue, Haikou, 570228, China
2 State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University, No.58 Renmin Avenue, Haikou, 570228, China

* Corresponding Author: Mengxing Huang. Email: email

Computers, Materials & Continua 2023, 75(2), 4341-4355. https://doi.org/10.32604/cmc.2023.037154

Abstract

Due to their adaptability, Unmanned Aerial Vehicles (UAVs) play an essential role in the Internet of Things (IoT). Using wireless power transfer (WPT) techniques, an UAV can be supplied with energy while in flight, thereby extending the lifetime of this energy-constrained device. This paper investigates the optimization of resource allocation in light of the fact that power transfer and data transmission cannot be performed simultaneously. In this paper, we propose an optimization strategy for the resource allocation of UAVs in sensor communication networks. It is a practical solution to the problem of marine sensor networks that are located far from shore and have limited power. A corresponding system model is summarized based on the scenario and existing theoretical works. The minimum throughput-maximizing object is then formulated as an optimization problem. As swarm intelligence algorithms are utilized effectively in numerous fields, this paper chose to solve the formed optimization problem using the Harris Hawks Optimization and Whale Optimization Algorithms. This paper introduces a method for translating multi-decisions into a row vector in order to adapt swarm intelligence algorithms to the problem, as joint time and energy optimization have two sets of variables. The proposed method performs well in terms of stability and duration. Finally, performance is evaluated through numerical experiments. Simulation results demonstrate that the proposed method performs admirably in the given scenario.

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APA Style
Feng, S., Chen, Y., Huang, M., Shu, F. (2023). Optimization of resource allocation in unmanned aerial vehicles based on swarm intelligence algorithms. Computers, Materials & Continua, 75(2), 4341-4355. https://doi.org/10.32604/cmc.2023.037154
Vancouver Style
Feng S, Chen Y, Huang M, Shu F. Optimization of resource allocation in unmanned aerial vehicles based on swarm intelligence algorithms. Comput Mater Contin. 2023;75(2):4341-4355 https://doi.org/10.32604/cmc.2023.037154
IEEE Style
S. Feng, Y. Chen, M. Huang, and F. Shu "Optimization of Resource Allocation in Unmanned Aerial Vehicles Based on Swarm Intelligence Algorithms," Comput. Mater. Contin., vol. 75, no. 2, pp. 4341-4355. 2023. https://doi.org/10.32604/cmc.2023.037154



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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