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中国工业与应用数学学会会刊
主管:中华人民共和国教育部
主办:西安交通大学
ISSN 1005-3085  CN 61-1269/O1

工程数学学报 ›› 2017, Vol. 34 ›› Issue (5): 449-457.doi: 10.3969/j.issn.1005-3085.2017.05.001

• •    下一篇

车载自组织网络信息流量特性分析

张   宏1,   吕悦晶2   

  1. 1- 内蒙古大学交通学院,呼和浩特  010021
    2- 武汉科技大学汽车与交通工程学院,武汉  430081
  • 收稿日期:2015-10-26 接受日期:2016-12-28 出版日期:2017-10-15 发布日期:2017-12-15
  • 通讯作者: 张 宏 E-mail: zhang2001hong@126.com
  • 基金资助:
    国家自然科学基金(51508428);中国新能源汽车产品检测工况研究和开发.

Information Flow Characteristics Analysis of Vehicular Ad-hoc Network

ZHANG Hong1,   LV Yue-jing2   

  1. 1- School of Transportation, Institute of Inner Mongolia University, Hohhot 010021
    2- School of Automotive and Traffic Engineering, Wuhan University of Science and Technology, Wuhan 430081
  • Received:2015-10-26 Accepted:2016-12-28 Online:2017-10-15 Published:2017-12-15
  • Contact: H. Zhang. E-mail address: zhang2001hong@126.com
  • Supported by:
    The National Natural Science Foundation of China (51508428); China Automotive Test Cycles.

摘要: 为了揭示车载自组织网络动态拓扑特性,预测车载自组织网络行为和缓解网络拥堵,本文从微观角度分析了信息流量分布的一般特性,研究了在不同交通需求下车载自组织网络信息流量分布特性及信息流量与节点度值之间的关系.首先提出度、度分布指数与信息流量的关系,用复杂网络理论以静态、动态两种方式建立无容量限制的无标度网络模型,采用数值模拟实验和仿真实验方法讨论了参数变化时车载自组织网络信息流量变化规律;其次,借助非线性动力学理论研究了考虑容量限制的信息流量分布特性.研究结果表明,信息流量分布指数是无标度网络的通用特征参数,度值大的节点对网络影响较大,传播信息更快,信息流量与度值之间满足幂律分布规律;当信息流量需求增大时,Hub节点可能负担过重,许多信息流量可能会选择其他节点避免与Hub节点连通,这时较小度值的节点承担这部分信息流量.

关键词: 智能交通, 信息流量特性, 幂律分布, 复杂网络, 车载自组织网络

Abstract: In order to reveal the dynamic topological characteristics of Vehicular Ad-hoc Network (VANET), predict the behavior of VANET and alleviate the traffic congestion, extensive simulations of information propagation under normal circumstances from the microscopic point of view, we investigate the information flow distribution characteristics of VANET and the relationship between its information flow and degree of the node under different traffic demands in VANET. Firstly, the relationships among the degree, the degree distribution index and the information flow are proposed, and then scale-free network model is established with static and dynamic methods based on complex network theory, and when the parameters are varied, the change law of information flow is discussed by numerical simulation. Furthermore, the characteristics of information flow in capacity constraints are studied by means of nonlinear dynamics theory. Numerical results show that the information flow index is a general characteristic parameter of the scale-free network, and those larger degree nodes have a greater effect on the network and which also have faster propagation speed. We also find that the relationship of information flow and nodes degree obeys the power law distribution. Hub nodes may be overburdened when the information flow demand increases, and many information flows may choose other nodes to avoid communicating with the Hubs nodes, then the smaller degree of nodes will undertake this part of the information flow.

Key words: intelligent transportation, information flow characteristics, power-law distribution, complex network, VANET

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