Title :
Mobility prediction clustering algorithm for UAV networking
Author :
Zang, Chunhua ; Zang, Shouhong
Author_Institution :
Coll. of Electron. & Inf. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
Abstract :
In recent years, with the increasingly widespread application of unmanned aerial vehicle (UAV), the network technology of UAV has also caused for concern. In this paper, according to the background of related technologies of UAV, a mobility prediction clustering algorithm (MPCA) relying on the attributes of UAV is proposed. The dictionary Trie structure prediction algorithm and link expiration time mobility model are applied in this clustering algorithm to solve the difficulty of high mobility of UAV. The simulation shows that the reasonable clusterhead electing algorithm and on-demand cluster maintenance mechanism guarantee the stability of the cluster structure and the performance of the network.
Keywords :
autonomous aerial vehicles; mobility management (mobile radio); pattern clustering; UAV networking; dictionary trie structure prediction; link expiration time mobility model; mobility prediction clustering; network technology; on-demand cluster maintenance mechanism; reasonable clusterhead electing algorithm; unmanned aerial vehicle; Ad hoc networks; Clustering algorithms; Dictionaries; High definition video; Maintenance engineering; Mobile communication; Prediction algorithms; Clustering algorithm; Dictionary Trie; Mobility prediction; UAV;
Conference_Titel :
GLOBECOM Workshops (GC Wkshps), 2011 IEEE
Conference_Location :
Houston, TX
Print_ISBN :
978-1-4673-0039-1
Electronic_ISBN :
978-1-4673-0038-4
DOI :
10.1109/GLOCOMW.2011.6162360