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Open Access

IQABC-Based Hybrid Deployment Algorithm for Mobile Robotic Agents Providing Network Coverage

College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China
Pengcheng Laboratory, Shenzhen 518055, China
College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China
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Abstract

Working as aerial base stations, mobile robotic agents can be formed as a wireless robotic network to provide network services for on-ground mobile devices in a target area. Herein, a challenging issue is how to deploy these mobile robotic agents to provide network services with good quality for more users, while considering the mobility of on-ground devices. In this paper, to solve this issue, we decouple the coverage problem into the vertical dimension and the horizontal dimension without any loss of optimization and introduce the network coverage model with maximum coverage range. Then, we propose a hybrid deployment algorithm based on the improved quick artificial bee colony. The algorithm is composed of a centralized deployment algorithm and a distributed one. The proposed deployment algorithm deploy a given number of mobile robotic agents to provide network services for the on-ground devices that are independent and identically distributed. Simulation results have demonstrated that the proposed algorithm deploys agents appropriately to cover more ground area and provide better coverage uniformity.

Keywords

wireless robotic networksnetwork coveragedeployment algorithmimproved quick artificial bee colony

References

[1]
J. Li, A. M. V. V. Sai, X. Cheng, W. Cheng, Z. Tian, and Y. Li, Sampling-based approximate skyline query in sensor equipped IoT networks, Tsinghua Science and Technology, vol. 26, no. 2, pp. 219–229, 2020.
Crossref Google Scholar
[2]
J. Li, M. Siddula, X. Cheng, W. Cheng, Z. Tian, and Y. Li, Approximate data aggregation in sensor equipped IoT networks, Tsinghua Science and Technology, vol. 25, no. 1, pp. 44–55, 2019.
Crossref Google Scholar
[3]
R. Shahzadi, M. Ali, H. Z. Khan, and M. Naeem, UAV assisted 5G and beyond wireless networks: A survey, J. Netw. Comput. Appl., vol. 189, p. 103114, 2021.
Crossref Google Scholar
[4]
B. Li, Z. Fei, and Y. Zhang, UAV communications for 5G and beyond: Recent advances and future trends, IEEE Internet Things J., vol. 6, no. 2, pp. 2241–2263, 2019.
Crossref Google Scholar
[5]
A. D. Boursianis, M. S. Papadopoulou, P. Diamantoulakis, A. Liopa-Tsakalidi, P. Barouchas, G. Salahas, G. Karagiannidis, S. Wan, and S. K. Goudos, Internet of things (IoT) and agricultural unmanned aerial vehicles (UAVs) in smart farming: A comprehensive review, Internet of Things, vol. 18, p. 100187, 2022.
Crossref Google Scholar
[6]
S. Zhang and J. Liu, Analysis and optimization of multiple unmanned aerial vehicle-assisted communications in post-disaster areas, IEEE Trans. Veh. Technol., vol. 67, no. 12, pp. 12049–12060, 2018.
Crossref Google Scholar
[7]
X. Liu, X. Wang, J. Jia, and M. Huang, A distributed deployment algorithm for communication coverage in wireless robotic networks, J. Netw. Comput. Appl., vol. 180, p. 103019, 2021.
Crossref Google Scholar
[8]
S. Aslan, H. Badem, and D. Karaboga, Improved quick artificial bee colony (iqABC) algorithm for global optimization, Soft Comput., vol. 23, no. 24, pp. 13161–13182, 2019.
Crossref Google Scholar
[9]
X. Liu, X. Wang, M. Huang, J. Jia, N. Bartolini, Q. Li, and D. Zhao, Deployment of UAV-BSs for on-demand full communication coverage, Ad Hoc Netw., vol. 140, p. 103047, 2023.
Crossref Google Scholar
[10]
M. Alzenad, A. El-Keyi, F. Lagum, and H. Yanikomeroglu, 3-D placement of an unmanned aerial vehicle base station (UAV-BS) for energy-efficient maximal coverage, IEEE Wirel. Commun. Lett., vol. 6, no. 4, pp. 434–437, 2017.
Crossref Google Scholar
[11]
L. Yin, N. Zhang, and C. Tang, On-demand UAV base station deployment for wireless service of crowded tourism areas, Pers. Ubiquitous Comput., vol. 26, no. 4, pp. 1137–1149, 2022.
Crossref Google Scholar
[12]
J. Lyu, Y. Zeng, R. Zhang, and T. J. Lim, Placement optimization of UAV-mounted mobile base stations, IEEE Commun. Lett., vol. 21, no. 3, pp. 604–607, 2017.
Crossref Google Scholar
[13]
H. Zhao, H. Wang, W. Wu, and J. Wei, Deployment algorithms for UAV airborne networks toward on-demand coverage, IEEE J. Sel. Areas Commun., vol. 36, no. 9, pp. 2015–2031, 2018.
Crossref Google Scholar
[14]
A. Trotta, M. D. Felice, F. Montori, K. R. Chowdhury, and L. Bononi, Joint coverage, connectivity, and charging strategies for distributed UAV networks, IEEE Trans. Robot., vol. 34, no. 4, pp. 883–900, 2018.
Crossref Google Scholar
[15]
L. Ruan, J. Wang, J. Chen, Y. Xu, Y. Yang, H. Jiang, Y. Zhang, and Y. Xu, Energy-efficient multi-UAV coverage deployment in UAV networks: A game-theoretic framework, China Commun., vol. 15, no. 10, pp. 194–209, 2018.
Crossref Google Scholar
[16]
X. Zhang and L. Duan, Optimization of emergency UAV deployment for providing wireless coverage, in Proc. GLOBECOM 2017 - 2017 IEEE Global Communications Conf., Singapore, 2018, pp. 1–6.
Crossref Google Scholar
[17]
X. Zhang and L. Duan, Fast deployment of UAV networks for optimal wireless coverage, IEEE Trans. Mob. Comput., vol. 18, no. 3, pp. 588–601, 2019.
Crossref Google Scholar
[18]
N. T. Hanh, H. T. T. Binh, N. X. Hoai, and M. S. Palaniswami, An efficient genetic algorithm for maximizing area coverage in wireless sensor networks, Inf. Sci., vol. 488, pp. 58–75, 2019.
Crossref Google Scholar
[19]
D. G. Reina, H. Tawfik, and S. L. Toral, Multi-subpopulation evolutionary algorithms for coverage deployment of UAV-networks, Ad Hoc Netw., vol. 68, pp. 16–32, 2018.
Crossref Google Scholar
[20]
B. Cao, J. Zhao, Z. Lv, X. Liu, X. Kang, and S. Yang, Deployment optimization for 3D industrial wireless sensor networks based on particle swarm optimizers with distributed parallelism, J. Netw. Comput. Appl., vol. 103, pp. 225–238, 2018.
Crossref Google Scholar
[21]
J. Wang, C. Ju, Y. Gao, A. K. Sangaiah, and G. Kim, A PSO based energy efficient coverage control algorithm for wireless sensor networks, Comput., Mater. Contin., no. 9, pp. 433–446, 2018.
Google Scholar
[22]
W. Du, W. Ying, P. Yang, X. Cao, G. Yan, K. Tang, and D. Wu, Network-based heterogeneous particle swarm optimization and its application in UAV communication coverage, IEEE Trans. Emerg. Top. Comput. Intell., vol. 4, no. 3, pp. 312–323, 2020.
Crossref Google Scholar
[23]
T. Qasim, M. Zia, Q. A. Minhas, N. Bhatti, K. Saleem, T. Qasim, and H. Mahmood, An ant colony optimization based approach for minimum cost coverage on 3-D grid in wireless sensor networks, IEEE Commun. Lett., vol. 22, no. 6, pp. 1140–1143, 2018.
Crossref Google Scholar
[24]
J. Li, D. Lu, G. Zhang, J. Tian, and Y. Pang, Post-disaster unmanned aerial vehicle base station deployment method based on artificial bee colony algorithm, IEEE Access, vol. 7, pp. 168327–168336, 2019.
Crossref Google Scholar
[25]
X. Liu, X. Wang, J. Jia, J. Lv, and N. Bartolini, Distributed deployment in UAV-assisted networks for a long-lasting communication coverage, IEEE Syst. J., vol. 16, no. 3, pp. 4130–4138, 2022.
Crossref Google Scholar
[26]
A. Al-Hourani, S. Kandeepan, and S. Lardner, Optimal LAP altitude for maximum coverage, IEEE Wirel. Commun. Lett., vol. 3, no. 6, pp. 569–572, 2014.
Crossref Google Scholar
[27]
F. Aurenhammer and R. Klein, Voronoi diagrams, in Handbook of Computational Geometry, J. R. Sack and J. Urrutia, eds. Amsterdam, the Netherlands: North-Holland Publishing Co., 2000, pp. 201–290.
Crossref
[28]
M. Mozaffari, W. Saad, M. Bennis, and M. Debbah, Unmanned aerial vehicle with underlaid device-to-device communications: Performance and tradeoffs, IEEE Trans. Wirel. Commun., vol. 15, no. 6, pp. 3949–3963, 2016.
Crossref Google Scholar
[29]
D. Karaboga, B. Gorkemli, C. Ozturk, and N. Karaboga, A comprehensive survey: Artificial bee colony (ABC) algorithm and applications, Artif. Intell. Rev., vol. 42, no. 1, pp. 21–57, 2014.
Crossref Google Scholar
[30]
D. Karaboga and B. Basturk, A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm, J. Glob. Optim., vol. 39, no. 3, pp. 459–471, 2007.
Crossref Google Scholar
[31]
D. Karaboga and B. Gorkemli, A quick artificial bee colony (qABC) algorithm and its performance on optimization problems, Appl. Soft Comput., vol. 23, pp. 227–238, 2014.
Crossref Google Scholar
[32]
H. Mahboubi and A. G. Aghdam, Distributed deployment algorithms for coverage improvement in a network of wireless mobile sensors: Relocation by virtual force, IEEE Trans. Control Netw. Syst., vol. 4, no. 4, pp. 736–748, 2017.
Crossref Google Scholar
[33]
H. Mahboubi, K. Moezzi, A. G. Aghdam, K. Sayrafian-Pour, and V. Marbukh, Distributed deployment algorithms for improved coverage in a network of wireless mobile sensors, IEEE Trans. Ind. Inform., vol. 10, no. 1, pp. 163–174, 2014.
Crossref Google Scholar
Tsinghua Science and Technology
Volume 29 Issue 2,
April 2024
Pages 589-604
DOI: 10.26599/TST.2023.9010074
Cite this article:
Xu S, Liu X, Li D, et al. IQABC-Based Hybrid Deployment Algorithm for Mobile Robotic Agents Providing Network Coverage. Tsinghua Science and Technology, 2024, 29(2): 589-604. https://doi.org/10.26599/TST.2023.9010074

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Received: 18 May 2023
Revised: 01 July 2023
Accepted: 20 July 2023
Published: 22 September 2023
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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