基于节点社会性的无线网络编码传输策略研究
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摘要
延迟容忍网络是一种缺乏持续连接的新型网络体系结构,选择合适的转发节点是实现延迟容忍网络高效的转发和投递消息的关键问题。由于节点移动性和网络拓扑动态变化等会对延迟容忍网络的传输效率产生影响,提出了一种基于节点社会性和利用随机线性网络编码的DTN模型NSNC-DTN。NSNC-DTN模型利用网络中的社团结构、社团紧密度以及节点活跃度,选择出最合适的转发节点。离线计算节点的社会性,对源节点和center节点进行随机线性网络编码,在线完成转发,从而达到高效转发和投递的目的。仿真结果表明NSNC-DTN能够有效地提高信息投递成功率,减小端对端的网络延迟和网络开销。
Delay tolerant network(DTN) is a new network architecture which lacks continuous connectivity,choosing the appropriate forwarding node is a key of efficient forwarding and delivery. Due to the dynamic change of node mobility and network topology affect the transmission efficiency of DTN,this paper proposed a new DTN model NSNC-DTN based on nodal sociality and random linear network coding. NSNC-DTN model chose the most appropriate forwarding node by the community structure,the similarity of community and activity of the nodes in the network. It calculated nodal sociality in offline mode and used random linear network coding for source nodes and center nodes,implements messages forwarding online to reach the goal of efficient forwarding and delivery. The simulation result shows that NSNC-DTN model can effectively improve the success rate of information delivery and reduce network delay and network overhead.
Delay tolerant network(DTN) is a new network architecture which lacks continuous connectivity,choosing the appropriate forwarding node is a key of efficient forwarding and delivery. Due to the dynamic change of node mobility and network topology affect the transmission efficiency of DTN,this paper proposed a new DTN model NSNC-DTN based on nodal sociality and random linear network coding. NSNC-DTN model chose the most appropriate forwarding node by the community structure,the similarity of community and activity of the nodes in the network. It calculated nodal sociality in offline mode and used random linear network coding for source nodes and center nodes,implements messages forwarding online to reach the goal of efficient forwarding and delivery. The simulation result shows that NSNC-DTN model can effectively improve the success rate of information delivery and reduce network delay and network overhead.
引文
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[11]郭稳涛,李兵,何怡刚.基于社会活性和副本限制的DTN路由算法[J].电子测量与仪器学报,2017,31(7):1047-1052.(Guo Wentao,Li Bing,He Yigang. Social activity and copy-limited based DTN routing algorithm[J]. Journal of Electronic Measurement and Instrumentation,2017,31(7):1047-1052.)
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[14]Radicchi F,Castellano C,Cecconi F,et al. Defining and identifying communities in networks[J]. Proceedings of the National Academy of Science of the USA,2004,101(9):2658-2663.
[15]Wang Xiaofeng,Liu Gongshen,Pan Li,et al. Uncovering fuzzy communities in networks with structural similarity[J]. Neurocomputing,2016,210(1):26-33.
[16] Liu Weiping,Lu Linyuan. Link prediction based on local random walk[J]. Europhysics Letters,2010,89(5):58007-58012.
[17] Meyn S P,Tweedie R L. Markov chains and stochastic stability[M]. Berlin:Springer-Verlag,1993.
[18] Eagle N,Pentland A,Lazer D. Inferring social network structure using mobile phone data[J]. National Academy of Sciences,2009,106(36):15274-15278.
[2] Voyiatzis A G. A survey of delay-and disruption-tolerant networking applications[J]. Journal of Internet Engineering,2012,5(1):331-344.
[3]朱铁英,崔艳茹,李童,等.基于社会性的DTN网络路由算法研究[J].计算机工程,2012,38(14):96-98.(Zhu Tieying,Cui Yanru,Li Tong,et al. Research of DTN routing algorithm based on sociality[J]. Computer Engineering,2012,38(14):96-98.)
[4]刘唐,彭舰,杨进.异构延迟容忍传感器网络中基于转发概率的数据传输[J].软件学报,2013,24(2):215-229.(Liu Tang,Peng Jian,Yang Jin. Data delivery for heterogeneous delay tolerant mobile sensor networks based on forwarding probability[J]. Journal of Software,2013,24(2):215-229.)
[5]张振京,金志刚,舒炎泰.基于节点运动预测的社会性DTN高效路由[J].计算机学报,2013,36(3):626-635.(Zhang Zhenjing,Jin Zhigang,Shu Yantai. Efficient routing in social DTN based on nodes’movement prediction[J]. Chinese Journal of Computers,2013,36(3):626-635.)
[6] Hui Pan,Crowcroft J,Yoneki E. BUBBLE Rap:social-based forwarding in delay-tolerant networks[J]. Mobile Computing,2011,10(11):1576-1589.
[7] Dang Ha,Wu Hongyi. Clustering and cluster-based routing protocol for delay-tolerant mobile networks[J]. IEEE Trans on Wireless Communications,2010,9(6):1874-1881.
[8] Mei A,Morabito G,Santi P,et al. Social-aware stateless forwarding in pocket switched networks[C]//Proc of IEEE INFOCOM. Piscataway,NJ:IEEE Press,2011:251-255.
[9]贾建鑫,刘广忠,徐明. DTN中基于时空和社会性的概率路由算法[J].计算机科学,2016,43(6A):295-300,309.(Jia Jianxin,Liu Guangzhong,Xu Ming. Probability routing algorithm in DTN based on time and space and sociality[J]. Computer Science,2016,43(6A):295-300,309.)
[10]黄宏程,熊忠阳,胡敏,等.节点移动状态感知的社会化延迟容忍网络路由策略[J].计算机应用研究,2017,34(6):1826-1829.(Huang Hongcheng,Xiong Zhongyang,Hu Min,et al. Routing strategy based on change perception of node mobility characteristic in DTN[J]. Application Research of Computers,2017,34(6):1826-1829.)
[11]郭稳涛,李兵,何怡刚.基于社会活性和副本限制的DTN路由算法[J].电子测量与仪器学报,2017,31(7):1047-1052.(Guo Wentao,Li Bing,He Yigang. Social activity and copy-limited based DTN routing algorithm[J]. Journal of Electronic Measurement and Instrumentation,2017,31(7):1047-1052.)
[12]Newman M E J. Detecting community structure in networks[J]. The European Physical Journal B,2004,38(2):321-330.
[13]Girvan M,Newman M E J. Community structure in social and biological networks[J]. National Academy of Sciences,2002,99(12):7821-7826.
[14]Radicchi F,Castellano C,Cecconi F,et al. Defining and identifying communities in networks[J]. Proceedings of the National Academy of Science of the USA,2004,101(9):2658-2663.
[15]Wang Xiaofeng,Liu Gongshen,Pan Li,et al. Uncovering fuzzy communities in networks with structural similarity[J]. Neurocomputing,2016,210(1):26-33.
[16] Liu Weiping,Lu Linyuan. Link prediction based on local random walk[J]. Europhysics Letters,2010,89(5):58007-58012.
[17] Meyn S P,Tweedie R L. Markov chains and stochastic stability[M]. Berlin:Springer-Verlag,1993.
[18] Eagle N,Pentland A,Lazer D. Inferring social network structure using mobile phone data[J]. National Academy of Sciences,2009,106(36):15274-15278.