Clustering algorithm for micro unmanned aerial vehicle networks with multi-task objectives

Abstract

To address the complex multi-tasking application scenarios and unstable network topology of micro Unmanned Aerial Vehicle (UAV) clusters, this paper proposes a clustering algorithm MT-WCA. Firstly, the UAV nodes calculate their weight based on average connectivity difference, transmission capability, relative mobility and energy consumption. Then, under the constraint of cluster membership, the most suitable cluster head is elected to prolong the network's integrity time as much as possible. MT-WCA partitions task clusters rationally based on task objective information in the scenario, enabling the UAV cluster to complete tasks more effectively. The paper simulates multi-tasking work scenarios by MATLAB and compares the integrity time of UAV networks using different algorithms.