基于ICT分布的容迟网络接触模型

doi:10.13700/j.bh.1001-5965.2014.0557

北京航空航天大学学报 ›› 2015, Vol. 41 ›› Issue (8): 1422-1429.doi: 10.13700/j.bh.1001-5965.2014.0557

基于ICT分布的容迟网络接触模型

王海泉¹, 马伟建^1,2, 顾娟娟^2,3, 刘丹^2,3, 王亚^1,4

1. 北京航空航天大学软件学院, 北京 100191;
2. 北京航空航天大学网络技术北京市重点实验室, 北京 100191;
3. 北京航空航天大学数学与系统科学学院, 北京 100191;
4. 北京航空航天大学计算机学院, 北京 100191

收稿日期:2014-09-11 出版日期:2015-08-20 发布日期:2015-09-08
通讯作者: 王海泉(1978-),男,云南昭通人,讲师,whq@buaa.edu.cn,主要研究方向为移动容迟网络. E-mail:whq@buaa.edu.cn
基金资助:
国家自然科学基金(61300173);国家部委基金(A212010006);航空科学基金(2013ZC51026);北京市教育委员会联合资助项目(JD100060630);中央高校基本科研业务费专项资金(YWF-12-LXGY-001)

ICT distribution-based contact model for delay tolerant networks

WANG Haiquan¹, MA Weijian^1,2, GU Juanjuan^2,3, LIU Dan^2,3, WANG Ya^1,4

1. School of Software, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
2. Beijing Key Laboratory of Network Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
3. School of Mathematics and System Science, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
4. School of Computer Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

Received:2014-09-11 Online:2015-08-20 Published:2015-09-08

摘要/Abstract

摘要： 在容迟网络中,掌握节点之间的接触间隔时间(ICT)的特性,能够为网络性能分析、路由协议设计以及算法优化等研究提供理论指导和帮助,但目前的ICT模型往往缺乏普适性.通过对节点运动做出一般性假设,基于可靠性数学方法,给出了一个基于ICT分布的接触模型——IDCM.该模型证明了两个移动节点之间的ICT服从指数分布,且指数分布的参数仅与两个节点的历史接触次数和累积ICT有关.在随机方向(RD)移动模型、随机路点(RWP)移动模型、北京市出租车网络、口袋交换网4个数据集上进行了仿真验证,并与基于统计拟合参数的指数分布模型进行对比.仿真实验结果表明,IDCM能够准确反映节点对之间的接触间隔时间分布,且模型准确性优于基于统计拟合参数的指数分布模型.

关键词: 容迟网络(DTN), 接触间隔时间(ICT), 指数分布, 参数估计, 可靠性数学

Abstract: Characteristics of inter contact time (ICT) are essential for delay tolerant networks (DTNs), which are beneficial to network performance analysis, routing protocol design and algorithm optimization, but existing ICT models lack general applicability. Based on the general assumptions, a reliability mathematical model was proposed, which is called ICT distribution-based contact model (IDCM), to demonstrate that the ICT between two mobile nodes was exponentially distributed and to verify that the exponential parameter of node pairs only related to the historical contact numbers and cumulative ICTs. Based on random direction (RD) mobility model dataset, random way point (RWP) mobility model dataset, Beijing taxi network dataset, pocket switch network dataset, extensive experimental simulations were conducted and comparison to parameter-aggregated exponential model was made. The simulation results show that IDCM characterizes contacts of node pairs accurately and have better accuracy than parameter-aggregated exponential model.

Key words: delay tolerant network (DTN), inter contact time (ICT), exponential distribution, parameter estimation, reliability mathematics.

中图分类号:

TP393.03

王海泉, 马伟建, 顾娟娟, 刘丹, 王亚. 基于ICT分布的容迟网络接触模型[J]. 北京航空航天大学学报, 2015, 41(8): 1422-1429.

WANG Haiquan, MA Weijian, GU Juanjuan, LIU Dan, WANG Ya. ICT distribution-based contact model for delay tolerant networks[J]. JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2015, 41(8): 1422-1429.

参考文献

[1] Ahmed S A, Salil S K S.Characterization of a large-scale delay tolerant network[C]//Local Computer Networks (LCN).Piscataway,NJ:IEEE Press,2010:56-63.
[2] Karagiannis T, le Boudec J,Vojnovic M.Power law and exponential decay of intercontact times between mobile devices[J].IEEE Transactions on Mobile Computing,2010,9(10):1377-1390.
[3] Zhu H Z, Li M L,Fu L Y,et al.Impact of traffic influxes:Revealing exponential intercontact time in urban VANETs[J].IEEE Transactions on Parallel and Distributed Systems,2011,22(8):1258-1266.
[4] Li Y, Jiang Y R,Jin D P,et al.Energy-efficient optimal opportunistic forwarding for delay-tolerant networks[J].IEEE Transactions on Vehicular Technology,2010,59(9):4500-4512.
[5] Sharma G, Mazumdar R R.Delay and capacity tradeoffs for wireless ad hoc networks with random mobility[J].IEEE/ACM Transactions on Networking,2007,15(5):981-992.
[6] Muhammad A, Simon R.A simulation study of common mobility models for opportunistic networks[C]//Simulation Symposium.Piscataway,NJ:IEEE Press,2008:43-50.
[7] Muhammad A, Simon R.Characteristics of common mobility models for opportunistic networks[C]//ACM Second Workshop Performance Monitoring and Measurement of Heterogeneous Wireless and Wired Networks.New York:ACM,2007:105-109.
[8] Zhang X L, Kurose J,Levine B N,et al.Study of a bus-based disruption-tolerant network:Mobility modeling and impact on routing[C]//Proceedings of the Annual International Conference on Mobile Computing and Networking.New York:ACM,2007:195-206.
[9] Hu Y T, Wang H Q,Xia C H,et al.On the distribution of inter contact time for DTNs[C]//Local Computer Networks (LCN).Piscataway,NJ:IEEE Press,2012:152-155.
[10] Sharma G, Mazumdar R R.Scaling laws for capacity and delay in wireless ad hoc networks with random mobility[C]//IEEE International Conference on Communications.Piscataway,NJ:IEEE Press,2004:3869-3873.
[11] Spyropoulos T, Psounis K,Raghavendra C S.Performance analysis of mobility-assisted routing[C]//Proceedings of the International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc).New York:ACM,2006:49-60.
[12] Li Y,Hui P, Jin D P,et al.Evaluating the impact of social selfishness on the epidemic routing in delay tolerant networks[J].IEEE Communications Letters,2010,14(11):1026-1028.
[13] Niu J W,Guo J K, Cai Q S,et al.Predict and spread:An efficient routing algorithm for opportunistic networking[C]//Wireless Communications and Networking Conference.Piscataway,NJ:IEEE Press,2011:498-503.
[14] James S, Richard G,Jon C,et al.The Cambridge/haggle dataset[EB/OL].Cambridge:Cambridge University,2005(2013-01-15).http://crawdad.cs.dartmouth.edu/cambridge/haggle/.
[15] Erdds P, R Wi A.On random graphs[J].Computer Engineering,1959,109(4):339-340.
[16] 戴冠中,王林. 复杂网络的Scale-free性、Scale-free现象及其控制[M].北京:科学出版社,2009:1-5. Dai G Z,Wang L.Scale-free property,Scale-free phenomenon and control of complex network[M].Beijing:Science Press,2009:1-5(in Chinese).
[17] 冯允成,吕春连, 杜瑞甫.随机网络及其应用[M].北京:北京航空学院出版社,1987:1-8. Feng Y C,Lv C L,Du R F.Random network and its application[M].Beijing:Beihang University Press,1987:1-8(in Chinese).
[18] Erd s P, Rényi A.On the existence of a factor of degree one of a connected random graph[J].Acta Mathematica Academiae Scientiarum Hungarica,1966,17(3-4):359-368.
[19] Cai H, Eun D Y.Crossing over the bounded domain:From exponential to power-law intermeeting time in mobile ad hoc networks[J].IEEE/ACM Transactions on Networking,2009,17(5):1578-1591.
[20] Zhu H Z, Fu L Y,Xue G T,et al.Recognizing exponential inter-contact time in VANETs[C]//2010 Proceedings IEEE INFOCOM.Piscataway,NJ:IEEE Press,2010:101-105.

基于ICT分布的容迟网络接触模型

ICT distribution-based contact model for delay tolerant networks

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	陈尔康, 荆武兴, 高长生. 弹性高速飞行器的状态/参数滚动时域估计[J]. 北京航空航天大学学报, 2019, 45(2): 291-298.
[2]	刘科生, 王思洋. 含函数型自变量回归模型中的变量选择[J]. 北京航空航天大学学报, 2019, 45(10): 1990-1994.
[3]	雷梦颖, 魏彦兆, 李阳, 王丽娜. 稀疏多小波时变系统辨识及脑电信号时频分析[J]. 北京航空航天大学学报, 2018, 44(6): 1312-1320.
[4]	葛承垄, 朱元昌, 邸彦强. 面向装备RUL预测的平行仿真技术[J]. 北京航空航天大学学报, 2018, 44(4): 725-736.
[5]	谌炳汉, 左峥嵘, 夏鲁瑞. 单平台成像目标运动特性反演方法[J]. 北京航空航天大学学报, 2018, 44(12): 2528-2535.
[6]	王鑫, 张晓林, 曹晏波. 一种基于迭代的多音干扰消除方案[J]. 北京航空航天大学学报, 2017, 43(3): 573-582.
[7]	郑明国, 吴成东, 陈东岳, 贾同, 金勇虎. 基于非参数边缘积分估计的局部特征描述子[J]. 北京航空航天大学学报, 2016, 42(3): 497-505.
[8]	王晓红, 李宇翔, 余闯, 王立志. 基于β似然函数的参数估计方法[J]. 北京航空航天大学学报, 2016, 42(1): 41-46.
[9]	李强, 王中宇, 王卓然, 燕虎. 压力传感器激波管校准条件下的动态参数估计[J]. 北京航空航天大学学报, 2015, 41(7): 1223-1230.
[10]	张洪礼, 罗钦钦, 韩潮. UKF参数估计在三体Lambert问题中的应用[J]. 北京航空航天大学学报, 2015, 41(2): 228-233.
[11]	梁子璇, 任章. 基于在线气动参数修正的预测制导方法[J]. 北京航空航天大学学报, 2013, 39(7): 853-857.
[12]	马纪明, 万蔚, 王法岩. 基于模型诊断技术的神经网络实现方法[J]. 北京航空航天大学学报, 2013, 39(2): 178-183.
[13]	和丽清, 孙先仿, 邱红专. 非线性系统的结构选择及其参数的集员辨识[J]. 北京航空航天大学学报, 2010, 36(10): 1189-1193.
[14]	韩轶峰, 闫照文. 电离层拟合方法及路径参数量化分析[J]. 北京航空航天大学学报, 2009, 35(9): 1113-1116.
[15]	王冬青. 一类有色噪声干扰随机系统最小二乘递推辨识[J]. 北京航空航天大学学报, 2008, 34(8): 935-939.