吉林大学学报(信息科学版)2024,Vol.42Issue(3) :387-392.

基于MEC-UAV的海域物联网设备的覆盖优化算法

Coverage Optimization Algorithm in UAV-Aided Maritime Internet-of-Things

苑毅 黄珍
吉林大学学报(信息科学版)2024,Vol.42Issue(3) :387-392.

基于MEC-UAV的海域物联网设备的覆盖优化算法

Coverage Optimization Algorithm in UAV-Aided Maritime Internet-of-Things

苑毅 1黄珍2
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作者信息

  • 1. 兰州文理学院传媒工程学院,兰州 730000
  • 2. 兰州文理学院数字媒体学院,兰州 730000
  • 折叠

摘要

为增强对海域物联网(MIoT:Maritime Internet-of-Things)设备的覆盖,提出基于移动边缘计算(MEC:Mobile Edge Computing)的无人机(UAV:Unmanned Aerial Vehicle)部署的 MIoTs 的覆盖优化算法(UMCO:MEC-UAV-based Coverage Optimization algorithm).UMCO 算法通过部署配备 MEC-UAV,从而满足日益增加 MIoTs 的覆盖需求,提升网络增益.先将MEC-UAVs的部署以及其关联的MIoT设备问题形成联合问题,并将其转换成线性规划问题,最后利用基于Bender分解法的迭代算法求解该线性规划问题.仿真结果表明,该UMCO算法能获取逼近穷尽搜索算法的最优解.

Abstract

To increase the coverage of MIoTs(Maritime Internet-of-Things)devices,a coverage Optimization algorithm based on Deployment of MEC-UAV(UMCO:MEC-UAV-based Coverage Optimization algorithm)is proposed.In UMCO,MEC(Mobile Edge Computing)empowered UAVs(Unmanned Aerial Vehicles)is used to meet the network coverage demand for MIoT,and to maximize the network profit.We formulate a problem of joint MEC-UAVs deployment and their association with MIoT devices as an ILP(Integer Linear Programming)to maximize the network profit.An iterative algorithm is developed based on the Bender decomposition to solve the ILP.Finally,numerical results demonstrate that the proposed UMCO algorithm achieves a near-optimal solution.

关键词

海域物联网/无人机/移动边缘计算/Benders分解法/网络增益

Key words

maritime internet-of-things(MIoTs)/unmanned aerial vehicle(UAV)/mobile edge computing(MEC)/benders decomposition/network profit

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基金项目

兰州文理学院科研攻关专项基金资助项目(2020YQZX01)

甘肃省高等学校创新基金资助项目(2023A-180)

出版年

2024
吉林大学学报(信息科学版)
吉林大学

吉林大学学报(信息科学版)

CSTPCD
影响因子:0.607
ISSN:1671-5896
参考文献量11
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