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

作　　者：苑毅 黄珍 YUAN Yi;HUANG Zhen(School of Media Engineering,Lanzhou University of Arts and Science,Lanzhou 730000,China;School of Digital Media,Lanzhou University of Arts and Science,Lanzhou 730000,China)

机构地区：[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

出　　处：《吉林大学学报（信息科学版）》2024年第3期387-392,共6页Journal of Jilin University（Information Science Edition）

基　　金：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)。

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。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 

分 类 号：TN911[电子电信—通信与信息系统]