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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

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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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