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Quality, Reliability, Security and Robustness in Heterogeneous Systems. 19th EAI International Conference, QShine 2023, Shenzhen, China, October 8 – 9, 2023, Proceedings, Part II

Research Article

Bandwidth Resource Allocation and Uplink Optimization in MEC System Based on Multi-UAV Collaboration

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-65123-6_35,
        author={Na Yu and Xuehe Wang},
        title={Bandwidth Resource Allocation and Uplink Optimization in MEC System Based on Multi-UAV Collaboration},
        proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 19th EAI International Conference, QShine 2023, Shenzhen, China, October 8 -- 9, 2023, Proceedings, Part II},
        proceedings_a={QSHINE PART 2},
        year={2024},
        month={8},
        keywords={Mobile edge computing UAV Resource allocation},
        doi={10.1007/978-3-031-65123-6_35}
    }
    
  • Na Yu
    Xuehe Wang
    Year: 2024
    Bandwidth Resource Allocation and Uplink Optimization in MEC System Based on Multi-UAV Collaboration
    QSHINE PART 2
    Springer
    DOI: 10.1007/978-3-031-65123-6_35
Na Yu1, Xuehe Wang1,*
  • 1: School of Artificial Intelligence, Sun Yat-sen University
*Contact email: wangxuehe@mail.sysu.edu.cn

Abstract

Unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) has emerged as a promising solution to improve the performance of communication systems. In order to make use of UAVs to improve the performance of communication systems, this paper proposes an iterative optimization algorithm to meet the communication quality of mobile devices (MDs) in a multi-UAV-assisted MEC system under emergency situations. The algorithm jointly optimizes the number and deployment of UAVs in the system, the selection strategy of MD access links and the bandwidth allocation of each channel, so as to maximize the uplink transmission rate of all MDs in the entire communication system, as well as identify and cover isolated MDs. Through improved clustering algorithm and linear programming, the optimization problem is solved to maximize the uplink rate of the system. Finally, extensive evaluation results show that our proposed framework has superior performance.

Keywords
Mobile edge computing UAV Resource allocation
Published
2024-08-20
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-65123-6_35
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