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一种基于轨迹预测的机会网络路由协议 被引量:3

An opportunistic network routing protocol based on trajectory prediction
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摘要 为解决机会网络(opportunistic networks,ONs)中链路的频繁断开、节点的高速移动以及稀疏的网络密度等问题,提出了基于节点移动的历史数据和节点的社会性预测节点轨迹的方法,选取中继节点完成消息传递的机会网络路由协议。首先利用条件熵分析节点轨迹的可预测性;然后根据速度和预测单元,对节点进行单位活动区域的划分;最后利用节点移动概率及其社会性,对节点的下一位置进行预测。仿真结果表明:轨迹预测可以有效解决因节点高速移动,位置不断变化而导致的网络连通性时好时坏、极易断开的问题;基于轨迹预测的通信协议达到了较好的传递成功率,实现了对消息的高效传递。 According to the characteristics such as frequent disconnection of links,the high-speed movement of nodes and the density of sparse network in opportunistic networks(ONs),this paper proposes a method based on the historical data of node movement and the nodes’sociality to predict trajectory of nodes,and then to select relay nodes to complete the routing protocol of the opportunity network for message transmission.First,conditional entropy is used to analyze the predictability of node trajectories.Then,the node’s unit active area is divided according to the node’s speed and prediction unit.Finally,using the node movement probability and its sociality,the next position of the node is predicted.The simulation results show that the trajectory prediction can effectively solve the problem that the network connectivity is easily disconnected due to the high-speed movement of the nodes and the constant change of nodes’position.The communication protocol based on trajectory prediction has a good delivery success rate and achieves high-efficiecy delivery of messages.
作者 王桐 单欣 郑欣蕊 WANG Tong;SHAN Xin;ZHENG Xinrui(College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China;Department of Mechanical and Industrial Engineering,University of Toronto,Toronto M5S 1A1,Canada)
出处 《应用科技》 CAS 2020年第3期94-99,共6页 Applied Science and Technology
基金 国家自然科学基金项目(51779050)。
关键词 机会网络 轨迹预测 历史数据 条件熵 网格划分 社会性 概率计算 消息传递 opportunity network trajectory prediction historical data conditional entropy meshing sociality probability calculation message delivery
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  • 1徐中明,陈旭,贺岩松,文琍.智能交通系统(ITS)中的智能汽车技术[J].重庆大学学报(自然科学版),2005,28(8):17-21. 被引量:21
  • 2常促宇,向勇,史美林.车载自组网的现状与发展[J].通信学报,2007,28(11):116-126. 被引量:191
  • 3刘云浩.群智感知计算.中国计算机学会通讯.2012年10月.第8卷.第10期.
  • 4刘云浩.从普适计算、CPS到物联网:下一代互联网的视界中国计算机学会通讯,2009,5(12):66-69.
  • 5Haerri J,Filali F,Bonnet C.Modles for vehicular Ad Hoc network:a survey and taxonomy,research report RR-06-168[R].2006.
  • 6Sun Bo.Highly-safe intelligent vehicle based on trajectoryprediction[D].2011.
  • 7Liu Tong,Bahl P.Mobility modeling,location tracking,andtrajectory prediction in wireless ATM networks[J].IEEEJournal on Selected Areas in Communications,1998,16(6).
  • 8Morzy M.Prediction of moving object location based onfrequent trajectories[C].Proceedings of the 21st InternationalConference on Computer and Information Sciences,ISCIS’06,2006.
  • 9Remagnino P,Tan Y,Baker K.Multi-agent visual surveillanceof dynamic scenes[J].Image and Vision Computing,1998,16(8):529-532.
  • 10Chari K,Hevner A.System test planning of software:anoptimization approach[J].IEEE Transactions on SoftwareEngineering,2006,32(7).

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