4.7 Article

Cluster head selection method of multiple UAVs under COVID-19 situation

Journal

COMPUTER COMMUNICATIONS
Volume 196, Issue -, Pages 141-147

Publisher

ELSEVIER
DOI: 10.1016/j.comcom.2022.09.026

Keywords

Multi-UAVs cooperative; Cluster head selection; Mixed game theory

Funding

  1. National Natural Science Foundation of China [61872313]
  2. Key Research Projects in Education Informatization in Jiangsu Province [20180012]
  3. Postgraduate Research and Practice Innovation Program of Jiangsu Province, China [KYCX18_2366]
  4. Yangzhou Science and Technology, China [YZ2019133, YZ2020174]
  5. Science and Technology Project of Jiangsu Emergency Management Department, China [YJGL-YF-2021-3, YJGL-YF-2020-17]
  6. Yangzhou University Jiangdu High-End Equipment Engineering Technology Research Institute Open Project, China [YDJD201707]
  7. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, China [1907]

Ask authors/readers for more resources

As COVID-19 restricts movement and causes supply shortages in locked-down areas, unmanned aerial vehicle (UAV) deliveries have become a common solution. To improve cooperation efficiency and extend the lifespan of UAVs, a cluster head selection algorithm (CHSA) based on game theory is proposed. This algorithm uses a mixed game model to select cluster heads and reduces energy consumption between nodes.
As COVID-19 continues to spread, people are unable to move freely when their residence region is temporarily lockdown, supplies cannot normally enter into such zones, leading to the shortage of supplies in these areas. Thus to ensure the delivery of supplies while reducing contact, the unmanned aerial vehicle (UAV) deliveries have become a common way. In order to efficiently use UAV resources and reduce energy loss in data transmission while performing the tasks, clustering is often used for achieving the above objectives, where the selected cluster heads centrally plan tasks so that reduce the communication times. However, problems such as unreasonable clustering, high energy consumption of cluster heads, and high mortality of cluster heads, directly lead the low cooperation efficiency and short life cycle of UAVs. Considering the nodes often died earlier through the k-means algorithm and ant colony algorithm, and highly dependent on the base station, these factors affect the working cycle and coordination efficiency of the UAVs. Facing the issues above, the cluster head selection algorithm of UAV based on game (CHSA) is proposed, where the mixed game model is adopted to select cluster heads for each region after regional division, and selecting the representative node to perform the cluster head selection algorithm, which help to reduce the energy consumption of each round of communication between nodes. Moreover, the key properties of the CHSA algorithm are proved, and the comparison experiment are conducted to prove the CHSA algorithm can effectively reduce energy consumption and prolong the network life cycle.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available