Distributed multi-hop clustering algorithm for aeronautical ad-hoc network

Abstract

The aeronautical ad-hoc network (AANET) aims to provide a wider network connection for aircraft by creating links between them. However, the high speed of flight of aircraft leads to poor sustainability of AANET topology. In order to solve the problem of poor network topological stability, this study proposes a clustering method, called distributed multi-hop clustering algorithm (DMCA), for AANET. DMCA is based on the defined node stability weight and the concept of multi-hop clustering, which can effectively ensure the coverage and stability of clustering. In this study, we divided DMCA into three phases: information table generation stage, cluster head selection and cluster formation stage, and cluster maintenance stage. In order to verify the effectiveness of the proposed method, we compare the proposed method with N-hop, DMCNF, and K-means algorithms from four aspects: average cluster head duration, average cluster member duration, number of cluster head changes, and average number of link broken. According to the simulation results, it can be concluded that the proposed method has improved in these four performance indicators.