부산대학교 도서관

Drones, also known as unmanned aerial vehicles (UAVs), have become increasingly popular in the military and civil sectors. A swarm of UAVs (S-UAVs) is a group of UAVs that work together to complete a task. Because of the dynamic network topology of S-UAVs, routing schemes are complicated. Clustering is one of the most effective routing schemes for improving the performance of ad-hoc networks. The clustering scheme divides the network into groups known as clusters, each consisting of a cluster head (CH) and cluster members (CMs). The CH is a valuable element in the clustering scheme because it handles all inter- and intra-cluster communications. Proper selection of the CH is the key to enhancing the performance. Our study proposed a new clustering scheme for S-UAVs. Our scheme selects the CH and CMs based on a new weighted formula that consists of the following parameters: distance, speed, and reward index. The reward index is a newly calculated parameter based on latency. The weighted formula calculates the clustering index based on which CH and CMs are selected. This scheme was simulated using MATLAB to demonstrate its performance as a routing scheme. The simulation analyzed the latency due to the variation of the network’s parameters. In addition, the rewarding index and cluster index were analyzed. Finally, the proposed scheme was compared with an existing scheme known as the adaptive enhanced weighted clustering algorithm for UAV swarm. The comparison demonstrates that the proposed protocol is promising due to its lower-generated delays. The obtained results are displayed and analyzed towards the end of this paper, along with some ideas for future work.