Title
Distributed Topology Control Based On Swarm Intelligence In Unmanned Aerial Vehicles Networks
Abstract
Unmanned aerial vehicles (UAVs) have shown enormous potential in both public and civil domains. Although multiUAV systems can collaboratively accomplish missions efficiently, UAV network(UAVNET) design faces many challenging issues, such as high mobility, dynamic topology, power constraints, and varying quality of communication links. Topology control plays a key role for providing high network connectivity while conserving power in UAVNETs. In this paper, we propose a distributed topology control algorithm based on discrete particle swarm optimization with articulation points(AP-DPSO). To reduce signaling overhead and facilitate distributed control, we first identify a set of articulation points (APs) to partition the network into multiple segments. The local topology control problem for individual segments is formulated as a degree-constrained minimum spanning tree problem. Each node collects local topology information and adjusts its transmit power to minimize power consumption. We conduct simulation experiments to evaluate the performance of the proposed AP-DPSO algorithm. Numerical results show that AP-DPSO outperforms some known algorithms including LMST and LSP, in terms of network connectivity, average link length and network robustness for a dynamic UAVNET.
Year
DOI
Venue
2020
10.1109/WCNC45663.2020.9120571
2020 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC)
DocType
ISSN
Citations 
Conference
1525-3511
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Qianyi Zhang100.34
Gang Feng213416.96
Shuang Qin3568.72
Yao Sun417938.32