TY - GEN
T1 - A weighted clustering algorithm based on node energy for multi-UAV Ad Hoc networks
AU - Liu, Jinchao
AU - Zhang, Qi
AU - Xin, Xiangjun
AU - Tian, Qinghua
AU - Tao, Ying
AU - Ding, Rui
AU - Shen, Yufei
AU - Cao, Guixing
AU - Liu, Naijin
N1 - Publisher Copyright:
© 2018 SPIE.
PY - 2018
Y1 - 2018
N2 - In order to solve the problem of endurance of high-speed mobile multi-UAV in Ad Hoc networks with frequent network topology changing, this paper proposes a weighted clustering algorithm based on node energy (EWCA). In this algorithm, we use a multi-parameter weighted clustering algorithm, which improve the node degree difference and node residual energy calculation methods, and study the similarity between the adjacent nodes in terms of speed, direction, etc. The simulation studies the inter-cluster switching rate, the number of nodes and the performance of the minimum lifetime of network node. The results show that, compared with the highest node degree algorithm (HIGHD), adaptive security clustering algorithm (SWCA) and weighted clustering algorithm (WCA), the proposed algorithm can reduce the number of clusters, improve the stability of clustering, and the survival time of drones, and improve the network's endurance.
AB - In order to solve the problem of endurance of high-speed mobile multi-UAV in Ad Hoc networks with frequent network topology changing, this paper proposes a weighted clustering algorithm based on node energy (EWCA). In this algorithm, we use a multi-parameter weighted clustering algorithm, which improve the node degree difference and node residual energy calculation methods, and study the similarity between the adjacent nodes in terms of speed, direction, etc. The simulation studies the inter-cluster switching rate, the number of nodes and the performance of the minimum lifetime of network node. The results show that, compared with the highest node degree algorithm (HIGHD), adaptive security clustering algorithm (SWCA) and weighted clustering algorithm (WCA), the proposed algorithm can reduce the number of clusters, improve the stability of clustering, and the survival time of drones, and improve the network's endurance.
KW - Ad Hoc networks
KW - clustering algorithm
KW - node energy
UR - http://www.scopus.com/inward/record.url?scp=85059484005&partnerID=8YFLogxK
U2 - 10.1117/12.2505961
DO - 10.1117/12.2505961
M3 - Conference contribution
AN - SCOPUS:85059484005
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Tenth International Conference on Information Optics and Photonics
A2 - Huang, Yidong
PB - SPIE
T2 - 10th International Conference on Information Optics and Photonics
Y2 - 8 July 2018 through 11 July 2018
ER -