一种基于访问密度的UAV三维移动优化模型
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- 英文论文题名：An Optimization of UAV 3D Mobility Model based on Visit Density
- 论文作者：张国敏 ; 王娜 ; 王睿 ; 陈秋丽 ; 刘方鑫
- 年：2016
- 论文关键词：移动自组织无线网络 ; UAV机载网 ; 移动模型 ; 访问密度 ; 高斯马尔科夫模型
- 英文论文关键词：MAWN ; airborne ; node mobility mode ; visit density ; GMM
- 会议召开时间：2016-06-24
- 会议录名称：2016年全国通信软件学术会议程序册与交流文集
- 语种：中文
- 分类号：V279;TN929.5
- 学会代码：ZGTH
- 会议名称：2016年全国通信软件学术会议
- 会议地点：中国陕西西安
- 主办单位：中国通信学会
- 学会名称：中国通信学会
- 页数：5
- 文件大小：1071k
- 原文格式：O
- 会议级别：全国
摘要
UAV机载网络的性能紧密的依赖于所采用的移动模型中节点的移动方式,移动模型及其参数的选择也对其仿真结果具有重要意义。本文在三维高斯马尔科夫移动模型(3D-GMM)的基础上增加了基于访问密度的移动牵引,提出了一种基于访问密度的新型三维高斯马尔科夫移动模型(3D-VDGMM)。仿真实验表明3D-VDGMM能够很好的对UAV的移动进行模拟,且相比于3D-GMM能够有更高的事件捕获率。
The network performance of UAV airborne is closely relied on the movement of the mobile nodes which is decided by the mobility mode.And the selection of mobility model and its parameters is of great significance to the simulation results.Based on the three-dimensional gauss markov mobility model(3D-GMM),this paper expand GM by using visit density,and propose a new three-dimensional gauss markov mobility model based on visit density(3D-VDGMM).The results show that 3D_VDGMM can simulate the movement of UAVs well and have higher event capture rate compared to 3D-GMM.
The network performance of UAV airborne is closely relied on the movement of the mobile nodes which is decided by the mobility mode.And the selection of mobility model and its parameters is of great significance to the simulation results.Based on the three-dimensional gauss markov mobility model(3D-GMM),this paper expand GM by using visit density,and propose a new three-dimensional gauss markov mobility model based on visit density(3D-VDGMM).The results show that 3D_VDGMM can simulate the movement of UAVs well and have higher event capture rate compared to 3D-GMM.
引文
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[2]M.Erturk,J.Haque,and H.Arslan.Challenges of Aeronautical Data Networks[C].Proc.IEEE Aerospace Conf.,Montana,Mar.2010,pp.1-7.
[3]Bekmezci I,Sahingoz O K,Temel S.Flying ad-hoc networks(FANETs):A survey[J].Ad Hoc Networks,2013,11(3):1254-1270.
[4]Xie J,Wan Y,Kim J H,et al.A survey and analysis of mobility models for airborne networks[J].Communications Surveys&Tutorials,IEEE,2014,16(3):1221-1238.
[5]Broyles D,Jabbar A,and Sterbenz D.Design and Analysis of a 3-D Gauss Markov Mobility Model for Highly-dynamic Airborne Networks[C].International Telemetering Conference,Las Vegas.NV,October 2009.
[6]Rohrer,J.P.AeroRP Performance in Highly-Dynamic Airborne Networks using 3D Gauss-Markov Mobility Model.MILCOM 2011Military Communications Conference,ISSN2155-7578,2011,ISBN 9781467300797,pp.834-841.
[7]Zhao M,Wang W.WSN03-4:A Novel Semi-Markov Smooth Mobility Model for Mobile Ad Hoc Networks[C]//Global Telecommunications Conference,2006.GLOBECOM'06.IEEE.IEEE,2006:1-5.
[8]Zheng B,Zhang H Y,Huang G C,et al.Design and implementation of a 3-D smooth mobility model[J].Journal of Xidian University,2011,38(6):179-184.
[9]何明,陈秋丽,陈希亮,等.鱼群启发的三维Ad hoc网络节点随机移动优化模型[J].仪器仪表学报,2014,35(12):2826-2834.He M,Chen Q L,Chen X L,et al.Fish swarm inspired Ad hoc networks node random mobility optimization model in 3D environment[J].ChineseJournal of Scientific Instrument,2014,35(12):2826-2834.
[10]魏达,王沿锡,王健,等.车载自组网移动模型综述[J].计算机学报,2013,36(4):677-700.Wei D,Wang Y X,Wang J,et al.A Survey on Mobility of Vehicular Ad Hoc Networks[J].Chinese Journal of Computers,2013,36(4):677-700.