.png){kind=icon}
返回
An evolutionary trajectory planning algorithm for multi-UAV-assisted MEC system
.png){kind=icon}
OA
AI
DOI：10.1007/s00500-021-06465-y.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper presents a multi-unmanned aerial vehicle (UAV)-assisted mobile edge computing system, where multiple UAVs are used to serve mobile users. We aim to minimize the overall energy consumption of the system by planning the trajectories of UAVs. To plan the trajectories of UAVs, we need to consider the deployment of hovering points (HPs) of UAVs, their association with UAVs, and their order for each UAV. Therefore, the problem is very complicated, as it is non-convex, nonlinear, NP-hard, and mixed-integer. To solve the problem, this paper proposed an evolutionary trajectory planning algorithm (ETPA), which comprises four phases. In the first phase, a variable-length GA is adopted to update the deployments of HPs for UAVs. Accordingly, redundant HPs are removed by the remove operator. Subsequently, a differential evolution clustering algorithm is adopted to cluster HPs into different clusters without knowing the number of HPs in advance. Finally, a GA is proposed to construct the order of HPs for UAVs. The experimental results on a set of eight instances show that the proposed ETPA outperforms other compared algorithms in terms of the energy consumption of the system.
Keyword:
Mobile edge computing
Unmanned aerial vehicle
Evolutionary algorithm
Genetic algorithm
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
机构
引用论文
Completion Time Minimization for UAV-Assisted Mobile-Edge Computing Systems无人机辅助移动边缘计算系统的完成时间最小化OAAI
.png){kind=icon}
OAAI分享收藏Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization求解全局数值优化问题的策略自适应差分进化算法OAAI
OAAI分享收藏Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges无人机无线通信: 机遇与挑战
OAAI
OAAI分享收藏Energy Efficient Resource Allocation in UAV-Enabled Mobile Edge Computing Networks支持无人机的移动边缘计算网络中的节能资源分配OAAI
OAAI分享收藏分享收藏Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path PlanningOAAI
OAAI分享收藏
查看更多内容