.png){kind=icon}
返回
UAVs Deployment Algorithms for Maximizing Backhaul Flow
.png){kind=icon}
PRE
AI
DOI：10.1109/JSYST.2023.3267447.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This article considers topology construction or design using unmanned aerial vehicles (UAVs) in order to maximize the traffic flow from a given source to a destination node. To this end, it outlines a mixed-integer linear program (MILP) to optimize the placement of UAVs and the routing of flow from the said source to the destination. The problem is very challenging because the MILP requires an exhaustive collection of topologies, which increases exponentially with the number of UAVs and potential UAVs placement locations. To this end, this article outlines two novel methods. The first is a heuristic centralized method called distance-based location selection (DBLS) that generates a subset of topologies to reduce the search space of the said MILP. The second method is a distributed Gibbs-sampling-based protocol (DGSP) that allows each UAV to determine its location iteratively and independently. Our results show that DBLS and DGSP achieve, respectively, 85% and 72% of the optimal maximum flow.
Keyword:
Topology
Backhaul networks
Network topology
Wireless communication
Autonomous aerial vehicles
Logic gates
Wireless sensor networks
Distributed protocol
drones
maximum flow
optimization
routing
topology construction
期刊
I
IF:
2.4
论文数:
4.5K
被引数:
387
机构
引用论文
Sodium Ion-Selective Electrodes Based on Dibenzo-16-crown-5 Compounds with Pendent Ester Groups
PREAI
分享收藏
(S)-Mandelic acid enolate as a chiral benzoyl anion equivalent for the enantioselective synthesis of non-symmetrically substituted benzoins.png)
Tetrahedron
TetrahedronIF0
PREAI
分享收藏On Nodes Placement in Energy Harvesting Wireless Sensor Networks for Coverage And Connectivity能量收集无线传感器网络中覆盖和连通性的节点放置研究
PREAI
分享收藏
查看更多内容