节点文献

一种基于节点移动倾向检测的社会网络机会转发机制

Opportunistic Forwarding Mechanism Based on Node Movement Tendencies Detecting

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【作者】 刘林峰严禹道吴国新

【Author】 LIU Lin-feng;YAN Yu-dao;WU Guo-xin;Laboratory of Computer Network and Information Integration(Southeast University),Ministry of Education;School of Computer,Nanjing University of Posts and Telecommunications;

【机构】 东南大学计算机网络和信息集成教育部重点实验室南京邮电大学计算机学院

【摘要】 社会网络中节点的移动特点可以归结为强移动性和弱移动性两种类型。提出的MTBR(Mobile-Tendency Based Routing)算法引入了移动倾向的概念,将人的移动习惯与节点的移动规律进行关联。该算法通过检测出社会网络中强移动性节点的移动倾向,并利用强移动节点来携带数据并进行数据转发。实验数据表明,节点移动性越强其移动倾向越明显;相较于同类算法,MTBR算法可以有效地将消息向较远的目的地转发,其产生的转发能耗较低,送达率更稳定。

【Abstract】 The nodes in the social network can be classified into two types as strong mobility and weak mobility.The MTBR(Mobile-Tendency Based Routing)algorithm was proposed.And MTBR introduces the concept of‘Movement Tendency’which associates the human movements with their behavior habits.The algorithm detects the movement tendencies of the strong mobility nodes and takes advantage of strong mobility nodes to forward the messages.The simulation results indicate that the movement tendency will be more apparent with a stronger mobility.Besides,compared with other algorithms,MTBR algorithm can effectively forward the messages to the ulterior area near the destination,and produce fewer message copies and achieve a higher delivery ratio.

【基金】 国家自然科学基金(61373139);中国博士后科学基金面上项目(2014M560379);中国博士后科学基金特别资助项目(2015T80484)资助
  • 【文献出处】 计算机科学 ,Computer Science , 编辑部邮箱 ,2017年07期
  • 【分类号】TN929.5;TP393.02
  • 【被引频次】4
  • 【下载频次】76
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